Summer of code anay293 ML

Week 3 Image Alignment.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "8f72856b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e21dbb7d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def align_image(image):\n",
+    "    \n",
+    "    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
+    "\n",
+    " \n",
+    "    sift = cv2.SIFT_create()\n",
+    "\n",
+    "\n",
+    "    keypoints, descriptors = sift.detectAndCompute(gray, None)\n",
+    "\n",
+    "\n",
+    "    matcher = cv2.BFMatcher()\n",
+    "\n",
+    "\n",
+    "    matches = matcher.knnMatch(descriptors, descriptors, k=2)\n",
+    "    \n",
+    "    good_matches = []\n",
+    "    for m, n in matches:\n",
+    "        if m.distance < 0.75 * n.distance:\n",
+    "            good_matches.append(m)\n",
+    "\n",
+    "    src_points = np.float32([keypoints[m.queryIdx].pt for m in good_matches]).reshape(-1, 1, 2)\n",
+    "    dst_points = np.float32([keypoints[m.trainIdx].pt for m in good_matches]).reshape(-1, 1, 2)\n",
+    "\n",
+    "\n",
+    "    M, mask = cv2.findHomography(src_points, dst_points, cv2.RANSAC, 5.0)\n",
+    "\n",
+    "\n",
+    "    aligned_image = cv2.warpPerspective(image, M, (image.shape[1], image.shape[0]))\n",
+    "\n",
+    "    return aligned_image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "5ad7015f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "image = cv2.imread(\"C:\\\\Users\\\\91740\\\\OneDrive\\\\Desktop\\\\g.jpg\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2361d9d7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "81e03c86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))\n",
+    "enhanced_image = cv2.cvtColor(image1, cv2.COLOR_BGR2LAB)\n",
+    "enhanced_image[:, :, 0] = clahe.apply(enhanced_image1[:, :, 0])\n",
+    "enhanced_image = cv2.cvtColor(enhanced_image1, cv2.COLOR_LAB2BGR)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "b2a89ab1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "d8c5e61e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "aligned_image = align_image(enhanced_image)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f2e30048",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cv2.imshow('Aligned Image', aligned_image)\n",
+    "cv2.waitKey(0)\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f9fbe637",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}