notebooks/03_clip_embed.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Process the Unsplash dataset with CLIP\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# About"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook processes all the downloaded photos using OpenAI's [CLIP neural network](https://github.com/openai/CLIP). \n",
    "\n",
    "\n",
    "`CLIP` (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs.\n",
    "\n",
    "CLIP is a multi-modal vision and language model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load all photos from the folder they were stored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:57:50.717120Z",
     "iopub.status.busy": "2023-04-26T12:57:50.716480Z",
     "iopub.status.idle": "2023-04-26T12:57:52.483618Z",
     "shell.execute_reply": "2023-04-26T12:57:52.482811Z",
     "shell.execute_reply.started": "2023-04-26T12:57:50.717087Z"
    }
   },
   "outputs": [],
   "source": [
    "import datasets\n",
    "from sentence_transformers import SentenceTransformer\n",
    "import rich\n",
    "from IPython.display import Image, JSON\n",
    "from IPython.core.display import HTML\n",
    "import numpy as np\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "import torch\n",
    "import os\n",
    "import ipyplot\n",
    "from ipywidgets import interact, interact_manual\n",
    "from transformers import AutoTokenizer\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:57:52.485471Z",
     "iopub.status.busy": "2023-04-26T12:57:52.484998Z",
     "iopub.status.idle": "2023-04-26T12:57:52.497575Z",
     "shell.execute_reply": "2023-04-26T12:57:52.496579Z",
     "shell.execute_reply.started": "2023-04-26T12:57:52.485433Z"
    }
   },
   "outputs": [],
   "source": [
    "dset = datasets.load_from_disk(\"../data/processed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:57:52.499140Z",
     "iopub.status.busy": "2023-04-26T12:57:52.498860Z",
     "iopub.status.idle": "2023-04-26T12:57:52.504774Z",
     "shell.execute_reply": "2023-04-26T12:57:52.504100Z",
     "shell.execute_reply.started": "2023-04-26T12:57:52.499115Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset({\n",
       "    features: ['photo_id', 'photo_url', 'photo_image_url', 'photo_submitted_at', 'photo_featured', 'photo_width', 'photo_height', 'photo_aspect_ratio', 'photo_description', 'photographer_username', 'photographer_first_name', 'photographer_last_name', 'exif_camera_make', 'exif_camera_model', 'exif_iso', 'exif_aperture_value', 'exif_focal_length', 'exif_exposure_time', 'photo_location_name', 'photo_location_latitude', 'photo_location_longitude', 'photo_location_country', 'photo_location_city', 'stats_views', 'stats_downloads', 'ai_description', 'ai_primary_landmark_name', 'ai_primary_landmark_latitude', 'ai_primary_landmark_longitude', 'ai_primary_landmark_confidence', 'blur_hash', 'description_final', 'image', 'image_path_local'],\n",
       "    num_rows: 24992\n",
       "})"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:57:52.506702Z",
     "iopub.status.busy": "2023-04-26T12:57:52.506450Z",
     "iopub.status.idle": "2023-04-26T12:57:52.634952Z",
     "shell.execute_reply": "2023-04-26T12:57:52.634057Z",
     "shell.execute_reply.started": "2023-04-26T12:57:52.506680Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Woman exploring a forest\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x427>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f\"{dset[0]['photo_description']}\")\n",
    "dset[0]['image']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use Clip model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "<a href=\"https://huggingface.co/sentence-transformers/clip-ViT-B-32\">clip-ViT-B-32</a>    \n",
    "\n",
    "This is an Image and Text model that maps text and images to a shared vector space. \n",
    "\n",
    "OpenClip Model was trainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:57:52.636177Z",
     "iopub.status.busy": "2023-04-26T12:57:52.635940Z",
     "iopub.status.idle": "2023-04-26T12:57:52.639982Z",
     "shell.execute_reply": "2023-04-26T12:57:52.639219Z",
     "shell.execute_reply.started": "2023-04-26T12:57:52.636155Z"
    }
   },
   "outputs": [],
   "source": [
    "model_name = 'sentence-transformers/clip-ViT-B-32'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:57:52.641164Z",
     "iopub.status.busy": "2023-04-26T12:57:52.640928Z",
     "iopub.status.idle": "2023-04-26T12:58:02.602677Z",
     "shell.execute_reply": "2023-04-26T12:58:02.601853Z",
     "shell.execute_reply.started": "2023-04-26T12:57:52.641141Z"
    }
   },
   "outputs": [],
   "source": [
    "model = SentenceTransformer(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:02.603854Z",
     "iopub.status.busy": "2023-04-26T12:58:02.603633Z",
     "iopub.status.idle": "2023-04-26T12:58:02.608940Z",
     "shell.execute_reply": "2023-04-26T12:58:02.607874Z",
     "shell.execute_reply.started": "2023-04-26T12:58:02.603833Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SentenceTransformer(\n",
       "  (0): CLIPModel()\n",
       ")"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:02.610311Z",
     "iopub.status.busy": "2023-04-26T12:58:02.609999Z",
     "iopub.status.idle": "2023-04-26T12:58:02.621440Z",
     "shell.execute_reply": "2023-04-26T12:58:02.620508Z",
     "shell.execute_reply.started": "2023-04-26T12:58:02.610286Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CLIPModel(\n",
       "  (text_model): CLIPTextTransformer(\n",
       "    (embeddings): CLIPTextEmbeddings(\n",
       "      (token_embedding): Embedding(49408, 512)\n",
       "      (position_embedding): Embedding(77, 512)\n",
       "    )\n",
       "    (encoder): CLIPEncoder(\n",
       "      (layers): ModuleList(\n",
       "        (0): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (1): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (2): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (3): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (4): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (5): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (6): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (7): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (8): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (9): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (10): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (11): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (v_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (q_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "            (out_proj): Linear(in_features=512, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=512, out_features=2048, bias=True)\n",
       "            (fc2): Linear(in_features=2048, out_features=512, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "      )\n",
       "    )\n",
       "    (final_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)\n",
       "  )\n",
       "  (vision_model): CLIPVisionTransformer(\n",
       "    (embeddings): CLIPVisionEmbeddings(\n",
       "      (patch_embedding): Conv2d(3, 768, kernel_size=(32, 32), stride=(32, 32), bias=False)\n",
       "      (position_embedding): Embedding(50, 768)\n",
       "    )\n",
       "    (pre_layrnorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "    (encoder): CLIPEncoder(\n",
       "      (layers): ModuleList(\n",
       "        (0): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (1): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (2): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (3): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (4): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (5): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (6): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (7): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (8): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (9): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (10): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "        (11): CLIPEncoderLayer(\n",
       "          (self_attn): CLIPAttention(\n",
       "            (k_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (v_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (q_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "            (out_proj): Linear(in_features=768, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "          (mlp): CLIPMLP(\n",
       "            (activation_fn): QuickGELUActivation()\n",
       "            (fc1): Linear(in_features=768, out_features=3072, bias=True)\n",
       "            (fc2): Linear(in_features=3072, out_features=768, bias=True)\n",
       "          )\n",
       "          (layer_norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "        )\n",
       "      )\n",
       "    )\n",
       "    (post_layernorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)\n",
       "  )\n",
       "  (visual_projection): Linear(in_features=768, out_features=512, bias=False)\n",
       "  (text_projection): Linear(in_features=512, out_features=512, bias=False)\n",
       ")"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model[0].model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:02.623187Z",
     "iopub.status.busy": "2023-04-26T12:58:02.622932Z",
     "iopub.status.idle": "2023-04-26T12:58:02.649291Z",
     "shell.execute_reply": "2023-04-26T12:58:02.648250Z",
     "shell.execute_reply.started": "2023-04-26T12:58:02.623166Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cuda')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:02.652497Z",
     "iopub.status.busy": "2023-04-26T12:58:02.652165Z",
     "iopub.status.idle": "2023-04-26T12:58:12.788705Z",
     "shell.execute_reply": "2023-04-26T12:58:12.787811Z",
     "shell.execute_reply.started": "2023-04-26T12:58:02.652474Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a3c09c68a3694c0dbf4bccfff5ffe3d3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/4 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.25 s, sys: 1.36 s, total: 5.61 s\n",
      "Wall time: 10.1 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Dataset({\n",
       "    features: ['photo_id', 'photo_url', 'photo_image_url', 'photo_submitted_at', 'photo_featured', 'photo_width', 'photo_height', 'photo_aspect_ratio', 'photo_description', 'photographer_username', 'photographer_first_name', 'photographer_last_name', 'exif_camera_make', 'exif_camera_model', 'exif_iso', 'exif_aperture_value', 'exif_focal_length', 'exif_exposure_time', 'photo_location_name', 'photo_location_latitude', 'photo_location_longitude', 'photo_location_country', 'photo_location_city', 'stats_views', 'stats_downloads', 'ai_description', 'ai_primary_landmark_name', 'ai_primary_landmark_latitude', 'ai_primary_landmark_longitude', 'ai_primary_landmark_confidence', 'blur_hash', 'description_final', 'image', 'image_path_local', 'embeddings'],\n",
       "    num_rows: 100\n",
       "})"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "dset.select( range(100)).map(\n",
    "    lambda example: {'embeddings':model.encode(example['image'], device=device, normalize_embeddings=False)}, batched=True, batch_size=32)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "computing the embeddings for this model takes longer than the previous text embedding model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tokenizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.790318Z",
     "iopub.status.busy": "2023-04-26T12:58:12.789909Z",
     "iopub.status.idle": "2023-04-26T12:58:12.844131Z",
     "shell.execute_reply": "2023-04-26T12:58:12.843397Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.790280Z"
    },
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 512)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.encode(sentences = [\"men shoes\"]).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.845260Z",
     "iopub.status.busy": "2023-04-26T12:58:12.845013Z",
     "iopub.status.idle": "2023-04-26T12:58:12.879358Z",
     "shell.execute_reply": "2023-04-26T12:58:12.878404Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.845238Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(512,)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.encode(dset[0]['image']).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.880658Z",
     "iopub.status.busy": "2023-04-26T12:58:12.880392Z",
     "iopub.status.idle": "2023-04-26T12:58:12.884601Z",
     "shell.execute_reply": "2023-04-26T12:58:12.883728Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.880634Z"
    }
   },
   "outputs": [],
   "source": [
    "tokenizer = model._first_module().processor.tokenizer\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.886210Z",
     "iopub.status.busy": "2023-04-26T12:58:12.885834Z",
     "iopub.status.idle": "2023-04-26T12:58:12.896880Z",
     "shell.execute_reply": "2023-04-26T12:58:12.896147Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.886154Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CLIPTokenizerFast(name_or_path='/home/jupyter/.cache/torch/sentence_transformers/sentence-transformers_clip-ViT-B-32/0_CLIPModel', vocab_size=49408, model_max_length=77, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'bos_token': AddedToken(\"<|startoftext|>\", rstrip=False, lstrip=False, single_word=False, normalized=True), 'eos_token': AddedToken(\"<|endoftext|>\", rstrip=False, lstrip=False, single_word=False, normalized=True), 'unk_token': AddedToken(\"<|endoftext|>\", rstrip=False, lstrip=False, single_word=False, normalized=True), 'pad_token': '<|endoftext|>'}, clean_up_tokenization_spaces=True)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.898144Z",
     "iopub.status.busy": "2023-04-26T12:58:12.897824Z",
     "iopub.status.idle": "2023-04-26T12:58:12.908231Z",
     "shell.execute_reply": "2023-04-26T12:58:12.907529Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.898115Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a</w>',\n",
       " 'man</w>',\n",
       " 'and</w>',\n",
       " 'his</w>',\n",
       " 'pet</w>',\n",
       " 'dog</w>',\n",
       " 'per',\n",
       " 'rito</w>',\n",
       " 'play',\n",
       " 'ding',\n",
       " 'd</w>',\n",
       " 'catch</w>',\n",
       " 'in</w>',\n",
       " 'the</w>',\n",
       " 'beach</w>',\n",
       " '.</w>']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text = \"A man and his pet dog Perrito playdingd catch in the beach.\"\n",
    "tokenizer.tokenize(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.909563Z",
     "iopub.status.busy": "2023-04-26T12:58:12.909240Z",
     "iopub.status.idle": "2023-04-26T12:58:12.917617Z",
     "shell.execute_reply": "2023-04-26T12:58:12.916723Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.909540Z"
    }
   },
   "outputs": [],
   "source": [
    "text = f\"\"\"\n",
    "Puss in Boots: The Last Wish is a 2022 American computer-animated adventure film produced by DreamWorks Animation and distributed by Universal Pictures. \n",
    "The sequel to the spin-off film Puss in Boots (2011) and the sixth installment in the Shrek franchise. \n",
    "The film was directed by Joel Crawford and co-directed by Januel Mercado. Based on the character from Shrek 2 (2004) and inspired by the eponymous fairy tale, the film's screenplay was written by Paul Fisher and Tommy Swerdlow, with a story by Swerdlow and Tom Wheeler (the latter of whom wrote the 2011 film). \n",
    "The voice cast of Puss in Boots: The Last Wish includes Antonio Banderas and Salma Hayek Pinault reprising their respective roles as the titular character and Kitty Softpaws, and are joined by Harvey Guillén, Florence Pugh, Olivia Colman, Ray Winstone, Samson Kayo, John Mulaney, Wagner Moura, Da'Vine Joy Randolph, and Anthony Mendez, who voice new\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.919016Z",
     "iopub.status.busy": "2023-04-26T12:58:12.918743Z",
     "iopub.status.idle": "2023-04-26T12:58:12.932735Z",
     "shell.execute_reply": "2023-04-26T12:58:12.931881Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.918992Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Token indices sequence length is longer than the specified maximum sequence length for this model (220 > 77). Running this sequence through the model will result in indexing errors\n"
     ]
    }
   ],
   "source": [
    "tokens = tokenizer.tokenize(text) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.934123Z",
     "iopub.status.busy": "2023-04-26T12:58:12.933800Z",
     "iopub.status.idle": "2023-04-26T12:58:12.941430Z",
     "shell.execute_reply": "2023-04-26T12:58:12.940643Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.934100Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(921, 77)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(text), tokenizer.model_max_length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.942613Z",
     "iopub.status.busy": "2023-04-26T12:58:12.942369Z",
     "iopub.status.idle": "2023-04-26T12:58:12.950479Z",
     "shell.execute_reply": "2023-04-26T12:58:12.949746Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.942590Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pu ss</w> in</w> boots</w> :</w> the</w> last</w> wish</w> is</w> a</w> 2</w> 0</w> 2</w> 2</w> american</w> compu ter</w> -</w> animated</w> adventure</w> film</w> produced</w> by</w> dream works</w> animation</w> and</w> distributed</w> by</w> universal</w> pictures</w> .</w> the</w> sequel</w> to</w> the</w> spin</w> -</w> off</w> film</w> pu ss</w> in</w> boots</w> (</w> 2</w> 0</w> 1</w> 1</w> )</w> and</w> the</w> sixth</w> installment</w> in</w> the</w> shrek</w> franchise</w> .</w> the</w> film</w> was</w> directed</w> by</w> joel</w> crawford</w> and</w> co</w> -</w> directed</w> by</w> janu el</w> mercado</w> .</w> based</w> on</w> the</w> character</w> from</w> shrek</w> 2</w> (</w> 2</w> 0</w> 0</w> 4</w> )</w> and</w> inspired</w> by</w> the</w> ep onymous</w> fairy</w> tale</w> ,</w> the</w> film</w> 's</w> screenplay</w> was</w> written</w> by</w> paul</w> fisher</w> and</w> tommy</w> swer d low</w> ,</w> with</w> a</w> story</w> by</w> swer d low</w> and</w> tom</w> wheeler</w> (</w> the</w> latter</w> of</w> whom</w> wrote</w> the</w> 2</w> 0</w> 1</w> 1</w> film</w> ).</w> the</w> voice</w> cast</w> of</w> pu ss</w> in</w> boots</w> :</w> the</w> last</w> wish</w> includes</w> antonio</w> b ander as</w> and</w> sal ma</w> haye k</w> pin ault</w> repri sing</w> their</w> respective</w> roles</w> as</w> the</w> t itu lar</w> character</w> and</w> kitty</w> soft paws</w> ,</w> and</w> are</w> joined</w> by</w> harvey</w> gu ill Ã© n</w> ,</w> florence</w> pugh</w> ,</w> olivia</w> col man</w> ,</w> ray</w> win stone</w> ,</w> samson</w> kayo</w> ,</w> john</w> mu laney</w> ,</w> wagner</w> mour a</w> ,</w> da</w> '</w> vine</w> joy</w> randolph</w> ,</w> and</w> anthony</w> mendez</w> ,</w> who</w> voice</w> new</w>\n"
     ]
    }
   ],
   "source": [
    "print (\" \".join( tokens ))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "use cached embeddings or compute embeddings if don't exist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.952489Z",
     "iopub.status.busy": "2023-04-26T12:58:12.952273Z",
     "iopub.status.idle": "2023-04-26T12:58:12.959651Z",
     "shell.execute_reply": "2023-04-26T12:58:12.959034Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.952469Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "path_existing_embedding = \"../data/processed_embeddings\"\n",
    "\n",
    "if not os.path.exists(path_existing_embedding):\n",
    "\n",
    "    ds_with_embeddings = dset.map(\n",
    "         lambda example: {'embeddings':model.encode(example['image'], device=device, normalize_embeddings=True)}, batched=True, batch_size=32)\n",
    "\n",
    "    ds_with_embeddings.save_to_disk(path_existing_embedding)\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:12.960712Z",
     "iopub.status.busy": "2023-04-26T12:58:12.960463Z",
     "iopub.status.idle": "2023-04-26T12:58:14.226186Z",
     "shell.execute_reply": "2023-04-26T12:58:14.225283Z",
     "shell.execute_reply.started": "2023-04-26T12:58:12.960689Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ds_with_embeddings = datasets.load_from_disk(path_existing_embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:14.227498Z",
     "iopub.status.busy": "2023-04-26T12:58:14.227250Z",
     "iopub.status.idle": "2023-04-26T12:58:20.205392Z",
     "shell.execute_reply": "2023-04-26T12:58:20.204385Z",
     "shell.execute_reply.started": "2023-04-26T12:58:14.227476Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "corpus = ds_with_embeddings['embeddings']\n",
    "corpus = np.array(corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.206795Z",
     "iopub.status.busy": "2023-04-26T12:58:20.206524Z",
     "iopub.status.idle": "2023-04-26T12:58:20.212763Z",
     "shell.execute_reply": "2023-04-26T12:58:20.211765Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.206771Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24992"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.214284Z",
     "iopub.status.busy": "2023-04-26T12:58:20.213913Z",
     "iopub.status.idle": "2023-04-26T12:58:20.222621Z",
     "shell.execute_reply": "2023-04-26T12:58:20.221926Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.214259Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset({\n",
       "    features: ['photo_id', 'photo_url', 'photo_image_url', 'photo_submitted_at', 'photo_featured', 'photo_width', 'photo_height', 'photo_aspect_ratio', 'photo_description', 'photographer_username', 'photographer_first_name', 'photographer_last_name', 'exif_camera_make', 'exif_camera_model', 'exif_iso', 'exif_aperture_value', 'exif_focal_length', 'exif_exposure_time', 'photo_location_name', 'photo_location_latitude', 'photo_location_longitude', 'photo_location_country', 'photo_location_city', 'stats_views', 'stats_downloads', 'ai_description', 'ai_primary_landmark_name', 'ai_primary_landmark_latitude', 'ai_primary_landmark_longitude', 'ai_primary_landmark_confidence', 'blur_hash', 'description_final', 'image', 'image_path_local', 'embeddings'],\n",
       "    num_rows: 24992\n",
       "})"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_with_embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.223750Z",
     "iopub.status.busy": "2023-04-26T12:58:20.223463Z",
     "iopub.status.idle": "2023-04-26T12:58:20.232634Z",
     "shell.execute_reply": "2023-04-26T12:58:20.232035Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.223729Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "dset = ds_with_embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.234532Z",
     "iopub.status.busy": "2023-04-26T12:58:20.233712Z",
     "iopub.status.idle": "2023-04-26T12:58:20.245136Z",
     "shell.execute_reply": "2023-04-26T12:58:20.244251Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.234499Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:21:06.291413Z",
     "iopub.status.busy": "2023-04-26T13:21:06.290645Z",
     "iopub.status.idle": "2023-04-26T13:21:06.299016Z",
     "shell.execute_reply": "2023-04-26T13:21:06.298135Z",
     "shell.execute_reply.started": "2023-04-26T13:21:06.291381Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def find_results(query:str=None , k =5 , image_path_local_dir = \"../data/raw/images\",query_features=None):\n",
    "    \"\"\"\n",
    "    Prints K nearest neighbors similar to the input query.\n",
    "    Parameters\n",
    "    ------------\n",
    "    query: str\n",
    "        Input query.\n",
    "    k: int\n",
    "        Nearest neighbors to fetch.\n",
    "    \"\"\"\n",
    "    \n",
    "    if query_features is None:\n",
    "        # Generate the embeddings for the query.\n",
    "        query_features = model.encode(query, normalize_embeddings=True)\n",
    "    \n",
    "    \n",
    "    # Perform the dot product between query embeddings and image embeddings \n",
    "    doc_scores = query_features @ corpus.T\n",
    "    # query_features =np.expand_dims(query_features, axis=0)\n",
    "    #doc_scores = cosine_similarity(query_features, corpus).squeeze()\n",
    "\n",
    "    top_items_idx = doc_scores.argsort()[-k:][::-1]\n",
    "    \n",
    "\n",
    "    degug_info = {\n",
    "         \"query_original\":  query \n",
    "         , \"query_processed\" : query_features\n",
    "        , \"doc_scores\":  doc_scores \n",
    "        , \"top_items\":  top_items_idx \n",
    "    }\n",
    "    \n",
    "\n",
    "    display(HTML(f\"<h4>Query: {query} </h4>\"))\n",
    "    \n",
    "    images = []\n",
    "    labels = []\n",
    "    \n",
    "\n",
    "    # Iterate over the top k results\n",
    "    for idx, photo_data in enumerate( ds_with_embeddings.select(top_items_idx)):\n",
    "\n",
    "        doc_idx = top_items_idx[idx]\n",
    "        photo_id = photo_data['photo_id']\n",
    "        \n",
    "        image_path_local = f\"{image_path_local_dir}/{photo_id}.jpg\"\n",
    "\n",
    "            \n",
    "        if os.path.exists(image_path_local):\n",
    "            image_path = image_path_local\n",
    "        else:\n",
    "            image_path = photo_data[\"photo_image_url\"]\n",
    "        \n",
    "        images.append(image_path) \n",
    "        \n",
    "        \n",
    "        score = \"{:.5f}\".format(doc_scores[doc_idx])\n",
    "\n",
    "        labels.append (f\"\"\"\n",
    "                     Photo title: {photo_data[\"description_final\"]}   <br/>\n",
    "                     Distance: {score}\n",
    "            \n",
    "                     \"\"\")\n",
    "            \n",
    "\n",
    "    ipyplot.plot_images(images=images, labels=labels, img_width=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test semantic retrieval based on clip model\n",
    "\n",
    "Note Distance represents the dot product between query embedding and image embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:21:07.849509Z",
     "iopub.status.busy": "2023-04-26T13:21:07.848816Z",
     "iopub.status.idle": "2023-04-26T13:21:07.970487Z",
     "shell.execute_reply": "2023-04-26T13:21:07.968945Z",
     "shell.execute_reply.started": "2023-04-26T13:21:07.849477Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h4>Query: Two dogs playing in the snow </h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "        #ipyplot-html-viewer-toggle-nrTcAMJjsbYUbuzuw7ir82 {\n",
       "            position: absolute;\n",
       "            top: -9999px;\n",
       "            left: -9999px;\n",
       "            visibility: hidden;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-label-nrTcAMJjsbYUbuzuw7ir82 { \n",
       "            position: relative;\n",
       "            display: inline-block;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-textarea-nrTcAMJjsbYUbuzuw7ir82 {\n",
       "            background: lightgrey;\n",
       "            width: 100%;\n",
       "            height: 0px;\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-nrTcAMJjsbYUbuzuw7ir82:checked ~ #ipyplot-html-viewer-textarea-nrTcAMJjsbYUbuzuw7ir82 {\n",
       "            height: 200px;\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-nrTcAMJjsbYUbuzuw7ir82:checked + #ipyplot-html-viewer-label-nrTcAMJjsbYUbuzuw7ir82:after {\n",
       "            content: \"hide html\";\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            right: 0;\n",
       "            bottom: 0;\n",
       "            background: white;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <input type=\"checkbox\" id=\"ipyplot-html-viewer-toggle-nrTcAMJjsbYUbuzuw7ir82\">\n",
       "        <label id=\"ipyplot-html-viewer-label-nrTcAMJjsbYUbuzuw7ir82\" for=\"ipyplot-html-viewer-toggle-nrTcAMJjsbYUbuzuw7ir82\">show html</label>\n",
       "        <textarea id=\"ipyplot-html-viewer-textarea-nrTcAMJjsbYUbuzuw7ir82\" readonly>\n",
       "            \n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-8FAUqNw7sBdL3yxnbeVswF {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-jiSfNkCGXe9vFCtjatuR4d\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: brown and black dogs running on snow   <br/>\n",
       "                     Distance: 0.31937\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/FAcSe7SjDUU.jpg</h4><img src=\"../data/raw/images/FAcSe7SjDUU.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-jiSfNkCGXe9vFCtjatuR4d\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-NmxBynGXFMw5APGqFbiTp4\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Friends will be friends   <br/>\n",
       "                     Distance: 0.30999\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/lyStEjlKNSw.jpg</h4><img src=\"../data/raw/images/lyStEjlKNSw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-NmxBynGXFMw5APGqFbiTp4\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-csVF4e2BAtjGT4b8GJBfLa\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Caramel-brown-white-coloured dog in the snow.   <br/>\n",
       "                     Distance: 0.30256\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/JAjrbewMbFQ.jpg</h4><img src=\"../data/raw/images/JAjrbewMbFQ.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-csVF4e2BAtjGT4b8GJBfLa\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-QszY8Dy2uk8mN8nbjAcqdb\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: arctic fox fight...   <br/>\n",
       "                     Distance: 0.30226\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/Hb6nGDgWztE.jpg</h4><img src=\"../data/raw/images/Hb6nGDgWztE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-QszY8Dy2uk8mN8nbjAcqdb\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-WGRB9nBQ4pwHdvqdnoBq3Q\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Snowy Australian Shepherd.   <br/>\n",
       "                     Distance: 0.29796\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/7I-1Ba5Psxs.jpg</h4><img src=\"../data/raw/images/7I-1Ba5Psxs.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-WGRB9nBQ4pwHdvqdnoBq3Q\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>\n",
       "        </textarea>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-8FAUqNw7sBdL3yxnbeVswF {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-jiSfNkCGXe9vFCtjatuR4d\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: brown and black dogs running on snow   <br/>\n",
       "                     Distance: 0.31937\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/FAcSe7SjDUU.jpg</h4><img src=\"../data/raw/images/FAcSe7SjDUU.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-jiSfNkCGXe9vFCtjatuR4d\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-NmxBynGXFMw5APGqFbiTp4\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Friends will be friends   <br/>\n",
       "                     Distance: 0.30999\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/lyStEjlKNSw.jpg</h4><img src=\"../data/raw/images/lyStEjlKNSw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-NmxBynGXFMw5APGqFbiTp4\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-csVF4e2BAtjGT4b8GJBfLa\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Caramel-brown-white-coloured dog in the snow.   <br/>\n",
       "                     Distance: 0.30256\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/JAjrbewMbFQ.jpg</h4><img src=\"../data/raw/images/JAjrbewMbFQ.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-csVF4e2BAtjGT4b8GJBfLa\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-QszY8Dy2uk8mN8nbjAcqdb\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: arctic fox fight...   <br/>\n",
       "                     Distance: 0.30226\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/Hb6nGDgWztE.jpg</h4><img src=\"../data/raw/images/Hb6nGDgWztE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-QszY8Dy2uk8mN8nbjAcqdb\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "        <div id=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-WGRB9nBQ4pwHdvqdnoBq3Q\" class=\"ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Snowy Australian Shepherd.   <br/>\n",
       "                     Distance: 0.29796\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/7I-1Ba5Psxs.jpg</h4><img src=\"../data/raw/images/7I-1Ba5Psxs.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-8FAUqNw7sBdL3yxnbeVswF-WGRB9nBQ4pwHdvqdnoBq3Q\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "find_results('Two dogs playing in the snow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.396678Z",
     "iopub.status.busy": "2023-04-26T12:58:20.395918Z",
     "iopub.status.idle": "2023-04-26T12:58:20.521141Z",
     "shell.execute_reply": "2023-04-26T12:58:20.519788Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.396606Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h4>Query: boy and girl on a beach </h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "        #ipyplot-html-viewer-toggle-2AxqzJSPeWu9ENGnUHytMV {\n",
       "            position: absolute;\n",
       "            top: -9999px;\n",
       "            left: -9999px;\n",
       "            visibility: hidden;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-label-2AxqzJSPeWu9ENGnUHytMV { \n",
       "            position: relative;\n",
       "            display: inline-block;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-textarea-2AxqzJSPeWu9ENGnUHytMV {\n",
       "            background: lightgrey;\n",
       "            width: 100%;\n",
       "            height: 0px;\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-2AxqzJSPeWu9ENGnUHytMV:checked ~ #ipyplot-html-viewer-textarea-2AxqzJSPeWu9ENGnUHytMV {\n",
       "            height: 200px;\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-2AxqzJSPeWu9ENGnUHytMV:checked + #ipyplot-html-viewer-label-2AxqzJSPeWu9ENGnUHytMV:after {\n",
       "            content: \"hide html\";\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            right: 0;\n",
       "            bottom: 0;\n",
       "            background: white;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <input type=\"checkbox\" id=\"ipyplot-html-viewer-toggle-2AxqzJSPeWu9ENGnUHytMV\">\n",
       "        <label id=\"ipyplot-html-viewer-label-2AxqzJSPeWu9ENGnUHytMV\" for=\"ipyplot-html-viewer-toggle-2AxqzJSPeWu9ENGnUHytMV\">show html</label>\n",
       "        <textarea id=\"ipyplot-html-viewer-textarea-2AxqzJSPeWu9ENGnUHytMV\" readonly>\n",
       "            \n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-UNB9grXncGAkmACfZ3Fify {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-UNB9grXncGAkmACfZ3Fify]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-UNB9grXncGAkmACfZ3Fify]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-UNB9grXncGAkmACfZ3Fify]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-BxdVCAq7ShD2uybfyV4kyF\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: White sands   <br/>\n",
       "                     Distance: 0.30794\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/3xUnaShh5SQ.jpg</h4><img src=\"../data/raw/images/3xUnaShh5SQ.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-BxdVCAq7ShD2uybfyV4kyF\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-jHSvdFt4tWrzbnihXVmues\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: aerial view of seashore   <br/>\n",
       "                     Distance: 0.30317\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/dNyPi0PKWo0.jpg</h4><img src=\"../data/raw/images/dNyPi0PKWo0.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-jHSvdFt4tWrzbnihXVmues\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnztoBS7eEzQaRnMrTGLiJ\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: children enjoying the beach   <br/>\n",
       "                     Distance: 0.30200\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/pV87YnElHow.jpg</h4><img src=\"../data/raw/images/pV87YnElHow.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnztoBS7eEzQaRnMrTGLiJ\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnVG53RXLDcK5GrCUK5Nwm\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Dusk on beach shore   <br/>\n",
       "                     Distance: 0.29762\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/vCIoc-Wha1Q.jpg</h4><img src=\"../data/raw/images/vCIoc-Wha1Q.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnVG53RXLDcK5GrCUK5Nwm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-QKPzFuQEKsgpwUB4hRwm3L\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: couple holding hands at beach   <br/>\n",
       "                     Distance: 0.29627\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/Fu_WwKclRjE.jpg</h4><img src=\"../data/raw/images/Fu_WwKclRjE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-QKPzFuQEKsgpwUB4hRwm3L\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>\n",
       "        </textarea>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-UNB9grXncGAkmACfZ3Fify {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-UNB9grXncGAkmACfZ3Fify span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-UNB9grXncGAkmACfZ3Fify]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-UNB9grXncGAkmACfZ3Fify]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-UNB9grXncGAkmACfZ3Fify]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-BxdVCAq7ShD2uybfyV4kyF\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: White sands   <br/>\n",
       "                     Distance: 0.30794\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/3xUnaShh5SQ.jpg</h4><img src=\"../data/raw/images/3xUnaShh5SQ.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-BxdVCAq7ShD2uybfyV4kyF\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-jHSvdFt4tWrzbnihXVmues\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: aerial view of seashore   <br/>\n",
       "                     Distance: 0.30317\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/dNyPi0PKWo0.jpg</h4><img src=\"../data/raw/images/dNyPi0PKWo0.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-jHSvdFt4tWrzbnihXVmues\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnztoBS7eEzQaRnMrTGLiJ\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: children enjoying the beach   <br/>\n",
       "                     Distance: 0.30200\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/pV87YnElHow.jpg</h4><img src=\"../data/raw/images/pV87YnElHow.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnztoBS7eEzQaRnMrTGLiJ\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnVG53RXLDcK5GrCUK5Nwm\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Dusk on beach shore   <br/>\n",
       "                     Distance: 0.29762\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/vCIoc-Wha1Q.jpg</h4><img src=\"../data/raw/images/vCIoc-Wha1Q.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-DnVG53RXLDcK5GrCUK5Nwm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "        <div id=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-QKPzFuQEKsgpwUB4hRwm3L\" class=\"ipyplot-content-div-UNB9grXncGAkmACfZ3Fify\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: couple holding hands at beach   <br/>\n",
       "                     Distance: 0.29627\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/Fu_WwKclRjE.jpg</h4><img src=\"../data/raw/images/Fu_WwKclRjE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-UNB9grXncGAkmACfZ3Fify-QKPzFuQEKsgpwUB4hRwm3L\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "find_results('boy and girl on a beach')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.524534Z",
     "iopub.status.busy": "2023-04-26T12:58:20.523150Z",
     "iopub.status.idle": "2023-04-26T12:58:20.633917Z",
     "shell.execute_reply": "2023-04-26T12:58:20.632650Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.524468Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h4>Query: image of a man in a desert </h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "        #ipyplot-html-viewer-toggle-4rbYftEXuCvooASTwXW6Np {\n",
       "            position: absolute;\n",
       "            top: -9999px;\n",
       "            left: -9999px;\n",
       "            visibility: hidden;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-label-4rbYftEXuCvooASTwXW6Np { \n",
       "            position: relative;\n",
       "            display: inline-block;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-textarea-4rbYftEXuCvooASTwXW6Np {\n",
       "            background: lightgrey;\n",
       "            width: 100%;\n",
       "            height: 0px;\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-4rbYftEXuCvooASTwXW6Np:checked ~ #ipyplot-html-viewer-textarea-4rbYftEXuCvooASTwXW6Np {\n",
       "            height: 200px;\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-4rbYftEXuCvooASTwXW6Np:checked + #ipyplot-html-viewer-label-4rbYftEXuCvooASTwXW6Np:after {\n",
       "            content: \"hide html\";\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            right: 0;\n",
       "            bottom: 0;\n",
       "            background: white;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <input type=\"checkbox\" id=\"ipyplot-html-viewer-toggle-4rbYftEXuCvooASTwXW6Np\">\n",
       "        <label id=\"ipyplot-html-viewer-label-4rbYftEXuCvooASTwXW6Np\" for=\"ipyplot-html-viewer-toggle-4rbYftEXuCvooASTwXW6Np\">show html</label>\n",
       "        <textarea id=\"ipyplot-html-viewer-textarea-4rbYftEXuCvooASTwXW6Np\" readonly>\n",
       "            \n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-juiKbs4fESCmnHJNc5kEuK {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-BfcyfSTez4rErMfBFdUvgJ\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Sunset in Abu Dhabi Desert   <br/>\n",
       "                     Distance: 0.33820\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/gvEDvSXQhRw.jpg</h4><img src=\"../data/raw/images/gvEDvSXQhRw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-BfcyfSTez4rErMfBFdUvgJ\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-NpaRNLggYwVU3obEb3Mizm\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Sandsurfing in the Sahara.   <br/>\n",
       "                     Distance: 0.33295\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/u9Z5p-N-DSc.jpg</h4><img src=\"../data/raw/images/u9Z5p-N-DSc.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-NpaRNLggYwVU3obEb3Mizm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-h7PGQ3GQBKiNmXrKisRejH\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: man sitting down on sand   <br/>\n",
       "                     Distance: 0.33150\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/-N-O19tUMlE.jpg</h4><img src=\"../data/raw/images/-N-O19tUMlE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-h7PGQ3GQBKiNmXrKisRejH\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-RcrrYd96eQK3rLqBsG8gdU\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: three person standing on desert sand during daytime   <br/>\n",
       "                     Distance: 0.33023\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/601J978TjQo.jpg</h4><img src=\"../data/raw/images/601J978TjQo.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-RcrrYd96eQK3rLqBsG8gdU\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-3sLWzZeLGoPoqAM85dDTrB\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: silhouette of person standing on brown sand   <br/>\n",
       "                     Distance: 0.32915\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/aZT031Rw5F8.jpg</h4><img src=\"../data/raw/images/aZT031Rw5F8.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-3sLWzZeLGoPoqAM85dDTrB\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>\n",
       "        </textarea>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-juiKbs4fESCmnHJNc5kEuK {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-BfcyfSTez4rErMfBFdUvgJ\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Sunset in Abu Dhabi Desert   <br/>\n",
       "                     Distance: 0.33820\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/gvEDvSXQhRw.jpg</h4><img src=\"../data/raw/images/gvEDvSXQhRw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-BfcyfSTez4rErMfBFdUvgJ\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-NpaRNLggYwVU3obEb3Mizm\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Sandsurfing in the Sahara.   <br/>\n",
       "                     Distance: 0.33295\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/u9Z5p-N-DSc.jpg</h4><img src=\"../data/raw/images/u9Z5p-N-DSc.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-NpaRNLggYwVU3obEb3Mizm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-h7PGQ3GQBKiNmXrKisRejH\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: man sitting down on sand   <br/>\n",
       "                     Distance: 0.33150\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/-N-O19tUMlE.jpg</h4><img src=\"../data/raw/images/-N-O19tUMlE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-h7PGQ3GQBKiNmXrKisRejH\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-RcrrYd96eQK3rLqBsG8gdU\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: three person standing on desert sand during daytime   <br/>\n",
       "                     Distance: 0.33023\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/601J978TjQo.jpg</h4><img src=\"../data/raw/images/601J978TjQo.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-RcrrYd96eQK3rLqBsG8gdU\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "        <div id=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-3sLWzZeLGoPoqAM85dDTrB\" class=\"ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: silhouette of person standing on brown sand   <br/>\n",
       "                     Distance: 0.32915\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/aZT031Rw5F8.jpg</h4><img src=\"../data/raw/images/aZT031Rw5F8.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-juiKbs4fESCmnHJNc5kEuK-3sLWzZeLGoPoqAM85dDTrB\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "find_results('image of a man in a desert')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.637182Z",
     "iopub.status.busy": "2023-04-26T12:58:20.636282Z",
     "iopub.status.idle": "2023-04-26T12:58:20.774735Z",
     "shell.execute_reply": "2023-04-26T12:58:20.773886Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.637131Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h4>Query: light at the end of the tunnel </h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "        #ipyplot-html-viewer-toggle-QrhbhmMFpdmSZDE4M2hczv {\n",
       "            position: absolute;\n",
       "            top: -9999px;\n",
       "            left: -9999px;\n",
       "            visibility: hidden;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-label-QrhbhmMFpdmSZDE4M2hczv { \n",
       "            position: relative;\n",
       "            display: inline-block;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-textarea-QrhbhmMFpdmSZDE4M2hczv {\n",
       "            background: lightgrey;\n",
       "            width: 100%;\n",
       "            height: 0px;\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-QrhbhmMFpdmSZDE4M2hczv:checked ~ #ipyplot-html-viewer-textarea-QrhbhmMFpdmSZDE4M2hczv {\n",
       "            height: 200px;\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-QrhbhmMFpdmSZDE4M2hczv:checked + #ipyplot-html-viewer-label-QrhbhmMFpdmSZDE4M2hczv:after {\n",
       "            content: \"hide html\";\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            right: 0;\n",
       "            bottom: 0;\n",
       "            background: white;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <input type=\"checkbox\" id=\"ipyplot-html-viewer-toggle-QrhbhmMFpdmSZDE4M2hczv\">\n",
       "        <label id=\"ipyplot-html-viewer-label-QrhbhmMFpdmSZDE4M2hczv\" for=\"ipyplot-html-viewer-toggle-QrhbhmMFpdmSZDE4M2hczv\">show html</label>\n",
       "        <textarea id=\"ipyplot-html-viewer-textarea-QrhbhmMFpdmSZDE4M2hczv\" readonly>\n",
       "            \n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-99LesFw6uy6yTFiwzxa3xq {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-CS9jFNQLVeTvL66s7iojVm\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Gateway to heaven   <br/>\n",
       "                     Distance: 0.29487\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/epC_9-DibEI.jpg</h4><img src=\"../data/raw/images/epC_9-DibEI.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-CS9jFNQLVeTvL66s7iojVm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-584FqXub6RZZk3jyGCrLPJ\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: cave during golden hour   <br/>\n",
       "                     Distance: 0.29211\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/5vV1xgPPdoI.jpg</h4><img src=\"../data/raw/images/5vV1xgPPdoI.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-584FqXub6RZZk3jyGCrLPJ\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-Uny7rPyt8WY5kiDBmtn4xq\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Hobbit Shire   <br/>\n",
       "                     Distance: 0.29125\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/VivzPEYabew.jpg</h4><img src=\"../data/raw/images/VivzPEYabew.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-Uny7rPyt8WY5kiDBmtn4xq\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-cKQDzbkVjGKXnb5ZwERuDy\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: green and brown trees on forest during daytime   <br/>\n",
       "                     Distance: 0.29041\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/319NRzUxJUw.jpg</h4><img src=\"../data/raw/images/319NRzUxJUw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-cKQDzbkVjGKXnb5ZwERuDy\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-dGKZzWpoDhPsoSE2t7mt72\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: https://www.instagram.com/mikita.yo/   <br/>\n",
       "                     Distance: 0.28854\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/-xR3CRfkgwI.jpg</h4><img src=\"../data/raw/images/-xR3CRfkgwI.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-dGKZzWpoDhPsoSE2t7mt72\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>\n",
       "        </textarea>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-99LesFw6uy6yTFiwzxa3xq {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-CS9jFNQLVeTvL66s7iojVm\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Gateway to heaven   <br/>\n",
       "                     Distance: 0.29487\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/epC_9-DibEI.jpg</h4><img src=\"../data/raw/images/epC_9-DibEI.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-CS9jFNQLVeTvL66s7iojVm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-584FqXub6RZZk3jyGCrLPJ\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: cave during golden hour   <br/>\n",
       "                     Distance: 0.29211\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/5vV1xgPPdoI.jpg</h4><img src=\"../data/raw/images/5vV1xgPPdoI.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-584FqXub6RZZk3jyGCrLPJ\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-Uny7rPyt8WY5kiDBmtn4xq\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Hobbit Shire   <br/>\n",
       "                     Distance: 0.29125\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/VivzPEYabew.jpg</h4><img src=\"../data/raw/images/VivzPEYabew.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-Uny7rPyt8WY5kiDBmtn4xq\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-cKQDzbkVjGKXnb5ZwERuDy\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: green and brown trees on forest during daytime   <br/>\n",
       "                     Distance: 0.29041\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/319NRzUxJUw.jpg</h4><img src=\"../data/raw/images/319NRzUxJUw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-cKQDzbkVjGKXnb5ZwERuDy\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "        <div id=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-dGKZzWpoDhPsoSE2t7mt72\" class=\"ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: https://www.instagram.com/mikita.yo/   <br/>\n",
       "                     Distance: 0.28854\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/-xR3CRfkgwI.jpg</h4><img src=\"../data/raw/images/-xR3CRfkgwI.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-99LesFw6uy6yTFiwzxa3xq-dGKZzWpoDhPsoSE2t7mt72\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "find_results( \"light at the end of the tunnel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.777517Z",
     "iopub.status.busy": "2023-04-26T12:58:20.776587Z",
     "iopub.status.idle": "2023-04-26T12:58:20.785296Z",
     "shell.execute_reply": "2023-04-26T12:58:20.784098Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.777443Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sample_queries = [\n",
    "\"person on top of mountain\"\n",
    ", \"picture of a man in a desert\"\n",
    ", \"person in a desert\"    \n",
    "\n",
    ", \"the boy and girl on a beach\"\n",
    ", \"children in beach\"    \n",
    "\n",
    ", \"Two dogs playing in the snow\"\n",
    "\n",
    ", \"light at the end of the tunnel\"\n",
    ", \"seven wonders of the world\"\n",
    "    \n",
    "    \n",
    ", \"water droplets on a leaf\"\n",
    "    \n",
    ", \"ripley's aquarium of canada, toronto, canada\"\n",
    ", \"the butterfly atrium at hershey gardens\"\n",
    "    \n",
    ", \"salar de uyuni uyuni bolivia\"\n",
    ", \"沙漠青蛙 沙漠青蛙\" #(desert frog)\n",
    ", \"por do sol no mar\"\n",
    ", \"conhece te a ti mesmo\" #\t ( Greek for know thyself)\n",
    "\n",
    "\n",
    ", \"there is no planet b\"\n",
    "\n",
    "\n",
    ", \"nova scotia duck tolling retriever\"\n",
    "    \n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:20.788291Z",
     "iopub.status.busy": "2023-04-26T12:58:20.787284Z",
     "iopub.status.idle": "2023-04-26T12:58:21.278451Z",
     "shell.execute_reply": "2023-04-26T12:58:21.277666Z",
     "shell.execute_reply.started": "2023-04-26T12:58:20.788239Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e99db45941a941ab9a064c73e90c8ef7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='query', options=('person on top of mountain', 'picture of a man in…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#@interact_manual\n",
    "@interact\n",
    "def interact_find_results(query=sample_queries, k =5):\n",
    "    find_results( query=query, k =k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Searching by image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since this is a multimodal model, we should alos be able to search by images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:04:03.572242Z",
     "iopub.status.busy": "2023-04-26T13:04:03.571592Z",
     "iopub.status.idle": "2023-04-26T13:04:03.581738Z",
     "shell.execute_reply": "2023-04-26T13:04:03.580973Z",
     "shell.execute_reply.started": "2023-04-26T13:04:03.572210Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "query_image = dset[70]['image']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:04:13.506377Z",
     "iopub.status.busy": "2023-04-26T13:04:13.506043Z",
     "iopub.status.idle": "2023-04-26T13:04:13.634992Z",
     "shell.execute_reply": "2023-04-26T13:04:13.633577Z",
     "shell.execute_reply.started": "2023-04-26T13:04:13.506353Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h4>Query: <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x427 at 0x7F458A164890> </h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "        #ipyplot-html-viewer-toggle-bHLzqrKpQ8Q4sUt6o3Vkop {\n",
       "            position: absolute;\n",
       "            top: -9999px;\n",
       "            left: -9999px;\n",
       "            visibility: hidden;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-label-bHLzqrKpQ8Q4sUt6o3Vkop { \n",
       "            position: relative;\n",
       "            display: inline-block;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-textarea-bHLzqrKpQ8Q4sUt6o3Vkop {\n",
       "            background: lightgrey;\n",
       "            width: 100%;\n",
       "            height: 0px;\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-bHLzqrKpQ8Q4sUt6o3Vkop:checked ~ #ipyplot-html-viewer-textarea-bHLzqrKpQ8Q4sUt6o3Vkop {\n",
       "            height: 200px;\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-bHLzqrKpQ8Q4sUt6o3Vkop:checked + #ipyplot-html-viewer-label-bHLzqrKpQ8Q4sUt6o3Vkop:after {\n",
       "            content: \"hide html\";\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            right: 0;\n",
       "            bottom: 0;\n",
       "            background: white;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <input type=\"checkbox\" id=\"ipyplot-html-viewer-toggle-bHLzqrKpQ8Q4sUt6o3Vkop\">\n",
       "        <label id=\"ipyplot-html-viewer-label-bHLzqrKpQ8Q4sUt6o3Vkop\" for=\"ipyplot-html-viewer-toggle-bHLzqrKpQ8Q4sUt6o3Vkop\">show html</label>\n",
       "        <textarea id=\"ipyplot-html-viewer-textarea-bHLzqrKpQ8Q4sUt6o3Vkop\" readonly>\n",
       "            \n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-YfxewhpvUzpxSTqyhSK7KC {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-PjvuS9X82CbUUZoxyKzu8o\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Swim   <br/>\n",
       "                     Distance: 1.00000\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/QqRuDeIXb5I.jpg</h4><img src=\"../data/raw/images/QqRuDeIXb5I.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-PjvuS9X82CbUUZoxyKzu8o\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-4JsbC8ePuFbxrNqcjS9pkR\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Poppy the labrador during her pet photoshoot at Crawfordsburn beach, Northern Ireland.   <br/>\n",
       "                     Distance: 0.89668\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/0ARZS-6Q5OA.jpg</h4><img src=\"../data/raw/images/0ARZS-6Q5OA.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-4JsbC8ePuFbxrNqcjS9pkR\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-YZ5oQDE6oPgW7WLQ9tkwGu\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: shallow focus photo of brown dog running on body of water   <br/>\n",
       "                     Distance: 0.89278\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/uHXvkxCft7Y.jpg</h4><img src=\"../data/raw/images/uHXvkxCft7Y.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-YZ5oQDE6oPgW7WLQ9tkwGu\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-GmDPPePaFwz5rd7co36TBD\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: short-coated black dog standing beside a swimming pool   <br/>\n",
       "                     Distance: 0.86591\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/UJ3RrDd09Dg.jpg</h4><img src=\"../data/raw/images/UJ3RrDd09Dg.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-GmDPPePaFwz5rd7co36TBD\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-itd4XALcCiW37cw86KRrjg\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: short-coated black and white dog selective focus photography   <br/>\n",
       "                     Distance: 0.86094\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/xQSLtWJqJ14.jpg</h4><img src=\"../data/raw/images/xQSLtWJqJ14.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-itd4XALcCiW37cw86KRrjg\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>\n",
       "        </textarea>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-YfxewhpvUzpxSTqyhSK7KC {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-PjvuS9X82CbUUZoxyKzu8o\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Swim   <br/>\n",
       "                     Distance: 1.00000\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/QqRuDeIXb5I.jpg</h4><img src=\"../data/raw/images/QqRuDeIXb5I.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-PjvuS9X82CbUUZoxyKzu8o\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-4JsbC8ePuFbxrNqcjS9pkR\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Poppy the labrador during her pet photoshoot at Crawfordsburn beach, Northern Ireland.   <br/>\n",
       "                     Distance: 0.89668\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/0ARZS-6Q5OA.jpg</h4><img src=\"../data/raw/images/0ARZS-6Q5OA.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-4JsbC8ePuFbxrNqcjS9pkR\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-YZ5oQDE6oPgW7WLQ9tkwGu\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: shallow focus photo of brown dog running on body of water   <br/>\n",
       "                     Distance: 0.89278\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/uHXvkxCft7Y.jpg</h4><img src=\"../data/raw/images/uHXvkxCft7Y.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-YZ5oQDE6oPgW7WLQ9tkwGu\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-GmDPPePaFwz5rd7co36TBD\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: short-coated black dog standing beside a swimming pool   <br/>\n",
       "                     Distance: 0.86591\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/UJ3RrDd09Dg.jpg</h4><img src=\"../data/raw/images/UJ3RrDd09Dg.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-GmDPPePaFwz5rd7co36TBD\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "        <div id=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-itd4XALcCiW37cw86KRrjg\" class=\"ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: short-coated black and white dog selective focus photography   <br/>\n",
       "                     Distance: 0.86094\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/xQSLtWJqJ14.jpg</h4><img src=\"../data/raw/images/xQSLtWJqJ14.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-YfxewhpvUzpxSTqyhSK7KC-itd4XALcCiW37cw86KRrjg\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "find_results( query=query_image, k =5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T12:58:21.279569Z",
     "iopub.status.busy": "2023-04-26T12:58:21.279331Z",
     "iopub.status.idle": "2023-04-26T12:58:24.984337Z",
     "shell.execute_reply": "2023-04-26T12:58:24.983071Z",
     "shell.execute_reply.started": "2023-04-26T12:58:21.279547Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "46 ms ± 2.62 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "search_query = \"Two dogs playing in the snow\"\n",
    "k=5\n",
    "query_features = model.encode(search_query, normalize_embeddings=True)\n",
    "doc_scores = query_features @ corpus.T\n",
    "\n",
    "top_items = doc_scores.argsort()[-k:][::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multilingual Search"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is a multilingual text model that is mapped to the same embedding space as original clip model.\n",
    "\n",
    "This model allows you to use multilingual search in 50+ languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:21:12.836111Z",
     "iopub.status.busy": "2023-04-26T13:21:12.835446Z",
     "iopub.status.idle": "2023-04-26T13:21:13.996149Z",
     "shell.execute_reply": "2023-04-26T13:21:13.995376Z",
     "shell.execute_reply.started": "2023-04-26T13:21:12.836079Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "multilingual_text_model = SentenceTransformer('sentence-transformers/clip-ViT-B-32-multilingual-v1')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:30:55.293312Z",
     "iopub.status.busy": "2023-04-26T13:30:55.292653Z",
     "iopub.status.idle": "2023-04-26T13:30:55.297511Z",
     "shell.execute_reply": "2023-04-26T13:30:55.296481Z",
     "shell.execute_reply.started": "2023-04-26T13:30:55.293279Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sample_query = \"一个人在沙漠中的形象\" # Google Translate of \"image of a man in a desert\" in chinese\n",
    "\n",
    "sample_query = \"Bild eines Mannes in einer Wüste\" # Google Translate of \"image of a man in a desert\" in German\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:30:55.592477Z",
     "iopub.status.busy": "2023-04-26T13:30:55.591627Z",
     "iopub.status.idle": "2023-04-26T13:30:55.604023Z",
     "shell.execute_reply": "2023-04-26T13:30:55.603325Z",
     "shell.execute_reply.started": "2023-04-26T13:30:55.592444Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "query_features = multilingual_text_model.encode(sample_query, normalize_embeddings=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-26T13:30:55.825960Z",
     "iopub.status.busy": "2023-04-26T13:30:55.825171Z",
     "iopub.status.idle": "2023-04-26T13:30:55.922679Z",
     "shell.execute_reply": "2023-04-26T13:30:55.921311Z",
     "shell.execute_reply.started": "2023-04-26T13:30:55.825928Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h4>Query: None </h4>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "        #ipyplot-html-viewer-toggle-TxYnMVGYCH4dFci95DZ3Vm {\n",
       "            position: absolute;\n",
       "            top: -9999px;\n",
       "            left: -9999px;\n",
       "            visibility: hidden;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-label-TxYnMVGYCH4dFci95DZ3Vm { \n",
       "            position: relative;\n",
       "            display: inline-block;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-textarea-TxYnMVGYCH4dFci95DZ3Vm {\n",
       "            background: lightgrey;\n",
       "            width: 100%;\n",
       "            height: 0px;\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-TxYnMVGYCH4dFci95DZ3Vm:checked ~ #ipyplot-html-viewer-textarea-TxYnMVGYCH4dFci95DZ3Vm {\n",
       "            height: 200px;\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        #ipyplot-html-viewer-toggle-TxYnMVGYCH4dFci95DZ3Vm:checked + #ipyplot-html-viewer-label-TxYnMVGYCH4dFci95DZ3Vm:after {\n",
       "            content: \"hide html\";\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            right: 0;\n",
       "            bottom: 0;\n",
       "            background: white;\n",
       "            cursor: pointer;\n",
       "            color: blue;\n",
       "            text-decoration: underline;\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <input type=\"checkbox\" id=\"ipyplot-html-viewer-toggle-TxYnMVGYCH4dFci95DZ3Vm\">\n",
       "        <label id=\"ipyplot-html-viewer-label-TxYnMVGYCH4dFci95DZ3Vm\" for=\"ipyplot-html-viewer-toggle-TxYnMVGYCH4dFci95DZ3Vm\">show html</label>\n",
       "        <textarea id=\"ipyplot-html-viewer-textarea-TxYnMVGYCH4dFci95DZ3Vm\" readonly>\n",
       "            \n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-bWKXhHFSpirToiQdypohzj {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-bWKXhHFSpirToiQdypohzj]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-bWKXhHFSpirToiQdypohzj]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-bWKXhHFSpirToiQdypohzj]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-bWKXhHFSpirToiQdypohzj\">\n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-XrPF3PhEix5bfF45juvdVS\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: three person standing on desert sand during daytime   <br/>\n",
       "                     Distance: 0.35393\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/601J978TjQo.jpg</h4><img src=\"../data/raw/images/601J978TjQo.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-XrPF3PhEix5bfF45juvdVS\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-CSvUe3FyUNqLEoFQoyXPMh\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Sunset in Abu Dhabi Desert   <br/>\n",
       "                     Distance: 0.34643\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/gvEDvSXQhRw.jpg</h4><img src=\"../data/raw/images/gvEDvSXQhRw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-CSvUe3FyUNqLEoFQoyXPMh\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-8B4Bp9SPCdWFdmv9NwbBNd\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title:     <br/>\n",
       "                     Distance: 0.34640\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/ZkCVqkwlUGE.jpg</h4><img src=\"../data/raw/images/ZkCVqkwlUGE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-8B4Bp9SPCdWFdmv9NwbBNd\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-n5RwRPLhQmasHifSQrv9Nt\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: silhouette of person standing on brown sand   <br/>\n",
       "                     Distance: 0.34616\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/aZT031Rw5F8.jpg</h4><img src=\"../data/raw/images/aZT031Rw5F8.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-n5RwRPLhQmasHifSQrv9Nt\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-FWhufzUrMXKR9Z55tkMFjm\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: man sitting down on sand   <br/>\n",
       "                     Distance: 0.34588\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/-N-O19tUMlE.jpg</h4><img src=\"../data/raw/images/-N-O19tUMlE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-FWhufzUrMXKR9Z55tkMFjm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>\n",
       "        </textarea>\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        #ipyplot-imgs-container-div-bWKXhHFSpirToiQdypohzj {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            margin: 0%;\n",
       "            overflow: auto;\n",
       "            position: relative;\n",
       "            overflow-y: scroll;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj {\n",
       "            width: 200px;\n",
       "            display: inline-block;\n",
       "            margin: 3px;\n",
       "            position: relative;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj {\n",
       "            width: 200px;\n",
       "            background: white;\n",
       "            display: inline-block;\n",
       "            vertical-align: top;\n",
       "            text-align: center;\n",
       "            position: relative;\n",
       "            border: 2px solid #ddd;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span.ipyplot-img-close {\n",
       "            display: none;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span {\n",
       "            width: 100%;\n",
       "            height: 100%;\n",
       "            position: absolute;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj img {\n",
       "            width: 200px;\n",
       "        }\n",
       "\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span.ipyplot-img-close:hover {\n",
       "            cursor: zoom-out;\n",
       "        }\n",
       "        div.ipyplot-content-div-bWKXhHFSpirToiQdypohzj span.ipyplot-img-expand:hover {\n",
       "            cursor: zoom-in;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-bWKXhHFSpirToiQdypohzj]:target {\n",
       "            transform: scale(2.5);\n",
       "            transform-origin: left top;\n",
       "            z-index: 5000;\n",
       "            top: 0;\n",
       "            left: 0;\n",
       "            position: absolute;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-bWKXhHFSpirToiQdypohzj]:target span.ipyplot-img-close {\n",
       "            display: block;\n",
       "        }\n",
       "\n",
       "        div[id^=ipyplot-content-div-bWKXhHFSpirToiQdypohzj]:target span.ipyplot-img-expand {\n",
       "            display: none;\n",
       "        }\n",
       "        </style>\n",
       "    <div id=\"ipyplot-imgs-container-div-bWKXhHFSpirToiQdypohzj\">\n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-XrPF3PhEix5bfF45juvdVS\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: three person standing on desert sand during daytime   <br/>\n",
       "                     Distance: 0.35393\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/601J978TjQo.jpg</h4><img src=\"../data/raw/images/601J978TjQo.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-XrPF3PhEix5bfF45juvdVS\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-CSvUe3FyUNqLEoFQoyXPMh\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: Sunset in Abu Dhabi Desert   <br/>\n",
       "                     Distance: 0.34643\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/gvEDvSXQhRw.jpg</h4><img src=\"../data/raw/images/gvEDvSXQhRw.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-CSvUe3FyUNqLEoFQoyXPMh\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-8B4Bp9SPCdWFdmv9NwbBNd\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title:     <br/>\n",
       "                     Distance: 0.34640\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/ZkCVqkwlUGE.jpg</h4><img src=\"../data/raw/images/ZkCVqkwlUGE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-8B4Bp9SPCdWFdmv9NwbBNd\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-n5RwRPLhQmasHifSQrv9Nt\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: silhouette of person standing on brown sand   <br/>\n",
       "                     Distance: 0.34616\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/aZT031Rw5F8.jpg</h4><img src=\"../data/raw/images/aZT031Rw5F8.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-n5RwRPLhQmasHifSQrv9Nt\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-bWKXhHFSpirToiQdypohzj\">\n",
       "        <div id=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj-FWhufzUrMXKR9Z55tkMFjm\" class=\"ipyplot-content-div-bWKXhHFSpirToiQdypohzj\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">\n",
       "                     Photo title: man sitting down on sand   <br/>\n",
       "                     Distance: 0.34588\n",
       "            \n",
       "                     </h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">../data/raw/images/-N-O19tUMlE.jpg</h4><img src=\"../data/raw/images/-N-O19tUMlE.jpg\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-bWKXhHFSpirToiQdypohzj-FWhufzUrMXKR9Z55tkMFjm\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "find_results( query_features=query_features, k =5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "environment": {
   "kernel": "python3",
   "name": "pytorch-gpu.1-13.m107",
   "type": "gcloud",
   "uri": "gcr.io/deeplearning-platform-release/pytorch-gpu.1-13:m107"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}