From f84fae431589c0201623f7c344e9f7b9997a83d7 Mon Sep 17 00:00:00 2001 From: Lemorra Date: Thu, 7 Apr 2022 20:44:43 +0530 Subject: [PATCH 1/7] Added feature for erasure of objects in Images --- .pre-commit-config.yaml | 8 +- albumentations/augmentations/__init__.py | 14 +- .../augmentations/dropout/channel_dropout.py | 7 +- .../augmentations/dropout/coarse_dropout.py | 3 +- .../augmentations/dropout/cutout.py | 7 +- .../augmentations/dropout/functional.py | 3 +- .../augmentations/dropout/grid_dropout.py | 4 +- .../augmentations/dropout/mask_dropout.py | 5 +- .../augmentations/eraser/__init__.py | 1 + .../augmentations/eraser/functional.py | 204 ++++++++++++++++++ albumentations/augmentations/functional.py | 2 +- albumentations/augmentations/transforms.py | 6 +- albumentations/random_utils.py | 2 +- benchmark/benchmark.py | 33 +-- docs/conf.py | 7 +- tests/conftest.py | 3 +- tests/test_bbox.py | 14 +- tests/test_functional.py | 4 +- tests/test_imgaug.py | 15 +- tests/test_imgaug_imports.py | 2 +- tests/test_keypoint.py | 7 +- tests/test_pytorch.py | 3 +- tools/make_transforms_docs.py | 3 +- 23 files changed, 277 insertions(+), 80 deletions(-) create mode 100644 albumentations/augmentations/eraser/__init__.py create mode 100644 albumentations/augmentations/eraser/functional.py diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index f09f8859f..cb3a5231f 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,6 +1,6 @@ repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v3.4.0 + rev: v4.1.0 hooks: - id: trailing-whitespace - id: end-of-file-fixer @@ -8,17 +8,17 @@ repos: - id: check-json - id: check-yaml - repo: https://github.com/pre-commit/mirrors-isort - rev: 1ba6bfc # Use the revision sha / tag you want to point at + rev: v5.10.1 # Use the revision sha / tag you want to point at hooks: - id: isort args: [ "--profile", "black" ] - repo: https://github.com/psf/black - rev: 21.9b0 + rev: 22.3.0 hooks: - id: black args: [ --config=black.toml ] - repo: https://github.com/pre-commit/mirrors-mypy - rev: v0.910 + rev: v0.942 hooks: - id: mypy additional_dependencies: [ types-PyYAML ] diff --git a/albumentations/augmentations/__init__.py b/albumentations/augmentations/__init__.py index 72b482f1b..2a22822f3 100644 --- a/albumentations/augmentations/__init__.py +++ b/albumentations/augmentations/__init__.py @@ -5,20 +5,18 @@ # New transformations goes to individual files listed below from .domain_adaptation import * -from .functional import * - -from .geometric.functional import * -from .geometric.resize import * -from .geometric.rotate import * -from .geometric.transforms import * - from .dropout.channel_dropout import * from .dropout.coarse_dropout import * from .dropout.cutout import * from .dropout.functional import * from .dropout.grid_dropout import * from .dropout.mask_dropout import * - +from .eraser.functional import * +from .functional import * +from .geometric.functional import * +from .geometric.resize import * +from .geometric.rotate import * +from .geometric.transforms import * from .keypoints_utils import * from .transforms import * from .utils import * diff --git a/albumentations/augmentations/dropout/channel_dropout.py b/albumentations/augmentations/dropout/channel_dropout.py index 45d42c76d..48b4707ce 100644 --- a/albumentations/augmentations/dropout/channel_dropout.py +++ b/albumentations/augmentations/dropout/channel_dropout.py @@ -1,11 +1,10 @@ import random -from typing import Union, Tuple, Any, Mapping +from typing import Any, Mapping, Tuple, Union import numpy as np -from albumentations.core.transforms_interface import ( - ImageOnlyTransform, -) +from albumentations.core.transforms_interface import ImageOnlyTransform + from .functional import channel_dropout __all__ = ["ChannelDropout"] diff --git a/albumentations/augmentations/dropout/coarse_dropout.py b/albumentations/augmentations/dropout/coarse_dropout.py index a82d05e48..c6b1d5cbc 100644 --- a/albumentations/augmentations/dropout/coarse_dropout.py +++ b/albumentations/augmentations/dropout/coarse_dropout.py @@ -1,13 +1,12 @@ import random import typing -from typing import Optional, List, Tuple, Iterable, Union +from typing import Iterable, List, Optional, Tuple, Union import numpy as np from ...core.transforms_interface import DualTransform from .functional import cutout - __all__ = ["CoarseDropout"] diff --git a/albumentations/augmentations/dropout/cutout.py b/albumentations/augmentations/dropout/cutout.py index 206f171e3..c781c97bb 100644 --- a/albumentations/augmentations/dropout/cutout.py +++ b/albumentations/augmentations/dropout/cutout.py @@ -1,12 +1,11 @@ import random import warnings -from typing import Union, Any, Dict, Tuple +from typing import Any, Dict, Tuple, Union import numpy as np -from albumentations.core.transforms_interface import ( - ImageOnlyTransform, -) +from albumentations.core.transforms_interface import ImageOnlyTransform + from .functional import cutout __all__ = ["Cutout"] diff --git a/albumentations/augmentations/dropout/functional.py b/albumentations/augmentations/dropout/functional.py index 759bc4d0c..d40b51665 100644 --- a/albumentations/augmentations/dropout/functional.py +++ b/albumentations/augmentations/dropout/functional.py @@ -1,6 +1,7 @@ -from typing import List, Tuple, Union, Iterable +from typing import Iterable, List, Tuple, Union import numpy as np + from ..functional import preserve_shape __all__ = ["cutout", "channel_dropout"] diff --git a/albumentations/augmentations/dropout/grid_dropout.py b/albumentations/augmentations/dropout/grid_dropout.py index de7321a74..eeeeafdad 100644 --- a/albumentations/augmentations/dropout/grid_dropout.py +++ b/albumentations/augmentations/dropout/grid_dropout.py @@ -1,10 +1,10 @@ import random -from typing import Tuple, Iterable +from typing import Iterable, Tuple import numpy as np -from . import functional as F from ...core.transforms_interface import DualTransform +from . import functional as F __all__ = ["GridDropout"] diff --git a/albumentations/augmentations/dropout/mask_dropout.py b/albumentations/augmentations/dropout/mask_dropout.py index af69ad181..25cfd17a2 100644 --- a/albumentations/augmentations/dropout/mask_dropout.py +++ b/albumentations/augmentations/dropout/mask_dropout.py @@ -1,12 +1,11 @@ import random -from typing import Union, Tuple, Any, Dict +from typing import Any, Dict, Tuple, Union import cv2 import numpy as np from skimage.measure import label -from ...core.transforms_interface import DualTransform -from ...core.transforms_interface import to_tuple +from ...core.transforms_interface import DualTransform, to_tuple __all__ = ["MaskDropout"] diff --git a/albumentations/augmentations/eraser/__init__.py b/albumentations/augmentations/eraser/__init__.py new file mode 100644 index 000000000..f704280d7 --- /dev/null +++ b/albumentations/augmentations/eraser/__init__.py @@ -0,0 +1 @@ +from .functional import * diff --git a/albumentations/augmentations/eraser/functional.py b/albumentations/augmentations/eraser/functional.py new file mode 100644 index 000000000..eb67dfd45 --- /dev/null +++ b/albumentations/augmentations/eraser/functional.py @@ -0,0 +1,204 @@ +import glob +import os +import random + +import cv2 +import numpy as np + + +class MetaData: + """Class to extract data from labels of kitti format""" + + def __init__(self, parentDir, imgType): + """Load parent directory and Image type present in the image directory + + Args: + parentDir (string): Path to the directory that contains the Image folder and Label folder + imgType (string): Image type (Ex: JPEG: jpg, PNG: png) + """ + self.labelPath = os.path.join(parentDir, "labels") + self.imgPath = os.path.join(parentDir, "images") + self.imgType = imgType + self.data = {} + self.distribution = {} + self.labelStrengthOrder = [] + + def loadData(self): + """Load data from the txt files and stores it as a dictionary. + Also loads the distribution of classification classes present in the dataset. + """ + for filePath in glob.glob(f"{self.labelPath}/*"): + filename = os.path.basename(filePath).split(".")[0] + if os.path.isfile(os.path.join(self.imgPath, f"{filename}.{self.imgType}")): + self.data[filename] = {} + self.data[filename]["labels"] = {} + self.data[filename]["n_labels"] = {} + with open(filePath) as f: + for line in f: + label = line.split()[0] + if label not in self.data[filename]["labels"].keys(): + self.data[filename]["labels"][label] = {} + self.data[filename]["n_labels"][label] = 1 + else: + self.data[filename]["n_labels"][label] += 1 + + numTag = self.data[filename]["n_labels"][label] + xmin, ymin, xmax, ymax = line.split()[4:8] + length = abs(float(xmin) - float(xmax)) + breadth = abs(float(ymin) - float(ymax)) + area = length * breadth + + truncation = line.split()[1] + occlusion = line.split()[2] + alpha = line.split()[3] + threeDdim = line.split()[8:11] + location = line.split()[11:14] + rotationY = line.split()[14] + + self.data[filename]["labels"][label][f"l{numTag}"] = { + "coord": [(int(float(xmin)), int(float(ymin))), (int(float(xmax)), int(float(ymax)))], + "area": area, + "Truncation": truncation, + "Occlusion": occlusion, + "Alpha": alpha, + "ThreeDdim": threeDdim, + "Location": location, + "RotationY": rotationY, + } + + for label in self.data[filename]["n_labels"]: + if label not in self.distribution.keys(): + self.distribution[label] = self.data[filename]["n_labels"][label] + else: + self.distribution[label] += self.data[filename]["n_labels"][label] + + def identifyMinority(self): + """Sorts the distribution of classification classes to return class with least number of detections and its strength. + + Returns: + list: the first tells us the minority class and the second its number of occurences. + """ + self.labelStrengthOrder = list(dict(sorted(self.distribution.items(), key=lambda item: item[1])).keys()) + minorityLabel = self.labelStrengthOrder[0] + minorityStrength = self.distribution[minorityLabel] + + return [minorityLabel, minorityStrength] + + +def startEraser(parentDir, imgType, imgExpType): + """Start the synthesis process of normalizing the classes and + generates a synthesis image directory and a synthesis label directory. + + Args: + parentDir (string): Path to parent directory that contains image and label directories. + imgType (string): Type of image present in the Image directory + imgExpType (string): Type of synthesised image to be generated + """ + # currentDir = os.getcwd() + # parentDir = os.path.dirname(currentDir) + imgDir = os.path.join(parentDir, "images") + synthImgDir = os.path.join(parentDir, "syntheticImages") + synthLabDir = os.path.join(parentDir, "syntheticLabels") + + try: + os.mkdir(synthImgDir) + os.mkdir(synthLabDir) + except FileExistsError: + print("Synthetic dir already created!") + + obj1 = MetaData(parentDir, imgType) + obj1.loadData() + print(obj1.data) + # print(obj1.distribution) + minorityLabel, minorityStrength = obj1.identifyMinority() + + for filePath in glob.glob(f"{imgDir}/*"): + filename = os.path.basename(filePath).split(".")[0] + img = cv2.imread(filePath) + mask = np.full(img.shape[:2], 255, dtype="uint8") + + labelData = obj1.data[filename]["labels"] + labelCount = obj1.data[filename]["n_labels"] + + if minorityLabel not in labelData.keys(): + continue + + for labelname in labelData.keys(): + for tag in labelData[labelname]: + coord = labelData[labelname][tag]["coord"] + cv2.rectangle(mask, coord[0], coord[1], 0, -1) + + # cv.imshow("Mask", mask) + # cv.waitKey(1000) + invMask = 255 - mask + # palette = cv2.bitwise_and(img, img, mask=mask) + # print(palette) + # print(invMask) + # cv.imshow("Inverted Mask", invMask) + # cv.waitKey(1000) + inPaint = cv2.inpaint(img, invMask, 3, cv2.INPAINT_NS) + # cv.imshow("Inpainted Pic", inPaint) + # cv.waitKey(5000) + text = [] + for label in labelData.keys(): + if label != minorityLabel: + tags = list(labelData[label].keys()) + nTags = labelCount[label] + nAdd = labelCount[minorityLabel] + if nTags > nAdd: + tagAdd = random.sample(tags, nAdd) + else: + tagAdd = tags + for tag in tagAdd: + set1 = " ".join( + [ + label, + labelData[label][tag]["Truncation"], + labelData[label][tag]["Occlusion"], + labelData[label][tag]["Alpha"], + ] + ) + set3 = " ".join(labelData[label][tag]["ThreeDdim"]) + set4 = " ".join(labelData[label][tag]["Location"]) + set5 = labelData[label][tag]["RotationY"] + + (xmin, ymin), (xmax, ymax) = labelData[label][tag]["coord"] + set2 = " ".join([str(xmin), str(ymin), str(xmax), str(ymax)]) + inPaint[ymin:ymax, xmin:xmax, :] = img[ymin:ymax, xmin:xmax, :] + + line = " ".join([set1, set2, set3, set4, set5]) + text.append(line) + # cv.imshow("ROI", img[ymin:ymax, xmin:xmax, :]) + # cv.waitKey(5000) + print(f"Adding these tags of {label}:{tagAdd}") + else: + minTags = list(labelData[label].keys()) + for tag in minTags: + set1 = " ".join( + [ + label, + labelData[label][tag]["Truncation"], + labelData[label][tag]["Occlusion"], + labelData[label][tag]["Alpha"], + ] + ) + set3 = " ".join(labelData[label][tag]["ThreeDdim"]) + set4 = " ".join(labelData[label][tag]["Location"]) + set5 = labelData[label][tag]["RotationY"] + (xmin, ymin), (xmax, ymax) = labelData[label][tag]["coord"] + set2 = " ".join([str(xmin), str(ymin), str(xmax), str(ymax)]) + inPaint[ymin:ymax, xmin:xmax, :] = img[ymin:ymax, xmin:xmax, :] + + line = " ".join([set1, set2, set3, set4, set5]) + text.append(line) + # cv.imshow("ROI", img[ymin:ymax, xmin:xmax, :]) + # cv.waitKey(5000) + + # cv.imshow("Synthetic Image", inPaint) + # cv.waitKey(5000) + cv2.imwrite(os.path.join(synthImgDir, f"{filename}.{imgExpType}"), inPaint) + print(f"Synthesised synthetic Image for {filename}.") + fileContents = "\n".join(text) + with open(os.path.join(synthLabDir, f"{filename}.txt"), "w") as f: + f.write(fileContents) + print(f"New label for synthesised {filename} written.") diff --git a/albumentations/augmentations/functional.py b/albumentations/augmentations/functional.py index 879165132..a155c2fe3 100644 --- a/albumentations/augmentations/functional.py +++ b/albumentations/augmentations/functional.py @@ -587,7 +587,7 @@ def move_tone_curve(img, low_y, high_y): # Defines responze of a four-point bezier curve def evaluate_bez(t): - return 3 * (1 - t) ** 2 * t * low_y + 3 * (1 - t) * t ** 2 * high_y + t ** 3 + return 3 * (1 - t) ** 2 * t * low_y + 3 * (1 - t) * t**2 * high_y + t**3 evaluate_bez = np.vectorize(evaluate_bez) remapping = np.rint(evaluate_bez(t) * 255).astype(np.uint8) diff --git a/albumentations/augmentations/transforms.py b/albumentations/augmentations/transforms.py index e5663ecfd..bab1353df 100644 --- a/albumentations/augmentations/transforms.py +++ b/albumentations/augmentations/transforms.py @@ -1822,7 +1822,7 @@ def apply(self, img, gauss=None, **params): def get_params_dependent_on_targets(self, params): image = params["image"] var = random.uniform(self.var_limit[0], self.var_limit[1]) - sigma = var ** 0.5 + sigma = var**0.5 if self.per_channel: gauss = random_utils.normal(self.mean, sigma, image.shape) @@ -2804,7 +2804,7 @@ def get_params(self): / (2 * np.pi * np.sqrt((x - (ksize - 1) / 2) ** 2 + (y - (ksize - 1) / 2) ** 2)), [ksize, ksize], ) - kernel[(ksize - 1) // 2, (ksize - 1) // 2] = cutoff ** 2 / (4 * np.pi) + kernel[(ksize - 1) // 2, (ksize - 1) // 2] = cutoff**2 / (4 * np.pi) # Normalize kernel kernel = kernel.astype(np.float32) / np.sum(kernel) @@ -2982,7 +2982,7 @@ def get_params(self): grid = np.stack(np.meshgrid(ax, ax), axis=-1) # Calculate rotated sigma matrix - d_matrix = np.array([[sigmaX ** 2, 0], [0, sigmaY ** 2]]) + d_matrix = np.array([[sigmaX**2, 0], [0, sigmaY**2]]) u_matrix = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]]) sigma_matrix = np.dot(u_matrix, np.dot(d_matrix, u_matrix.T)) diff --git a/albumentations/random_utils.py b/albumentations/random_utils.py index 11dd2200f..063766999 100644 --- a/albumentations/random_utils.py +++ b/albumentations/random_utils.py @@ -2,7 +2,7 @@ # because numpy can return single number and ndarray import random as py_random -from typing import Optional, Sequence, Union, Type, Any +from typing import Any, Optional, Sequence, Type, Union import numpy as np diff --git a/benchmark/benchmark.py b/benchmark/benchmark.py index e7d243279..64559ed8c 100644 --- a/benchmark/benchmark.py +++ b/benchmark/benchmark.py @@ -1,34 +1,37 @@ from __future__ import division, print_function + import argparse import math import os import sys from abc import ABC -from timeit import Timer from collections import defaultdict -import pkg_resources - -from Augmentor import Operations, Pipeline -from PIL import Image, ImageOps -from pytablewriter import MarkdownTableWriter -from pytablewriter.style import Style +from timeit import Timer import cv2 - -from tqdm import tqdm +import keras_preprocessing.image as keras import numpy as np import pandas as pd -import torchvision.transforms.functional as torchvision -import keras_preprocessing.image as keras -from imgaug import augmenters as iaa -import solt.transforms as slt +import pkg_resources import solt.core as slc +import solt.transforms as slt import solt.utils as slu +import torchvision.transforms.functional as torchvision +from Augmentor import Operations, Pipeline +from imgaug import augmenters as iaa +from PIL import Image, ImageOps +from pytablewriter import MarkdownTableWriter +from pytablewriter.style import Style +from tqdm import tqdm -import albumentations.augmentations.functional as albumentations import albumentations as A -from albumentations.augmentations.geometric.functional import rotate, resize, shift_scale_rotate +import albumentations.augmentations.functional as albumentations from albumentations.augmentations.crops.functional import random_crop +from albumentations.augmentations.geometric.functional import ( + resize, + rotate, + shift_scale_rotate, +) cv2.setNumThreads(0) # noqa E402 cv2.ocl.setUseOpenCL(False) # noqa E402 diff --git a/docs/conf.py b/docs/conf.py index 9b2b49bcb..2b7230a3a 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -1,12 +1,11 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- import datetime -from typing import Dict, Any -from unittest.mock import MagicMock - -import re import os +import re import sys +from typing import Any, Dict +from unittest.mock import MagicMock sys.path.insert(0, os.path.abspath("../")) diff --git a/tests/conftest.py b/tests/conftest.py index 319dfe516..7706e8d12 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,11 +1,10 @@ +import multiprocessing import sys import warnings -import multiprocessing import numpy as np import pytest - try: import torch # skipcq: PYL-W0611 import torchvision # skipcq: PYL-W0611 diff --git a/tests/test_bbox.py b/tests/test_bbox.py index 4e4063674..ec79abf4c 100644 --- a/tests/test_bbox.py +++ b/tests/test_bbox.py @@ -1,19 +1,19 @@ import numpy as np import pytest +from albumentations import RandomCrop, RandomResizedCrop, RandomSizedCrop, Rotate from albumentations.augmentations.bbox_utils import ( - normalize_bbox, - denormalize_bbox, - normalize_bboxes, - denormalize_bboxes, calculate_bbox_area, - convert_bbox_to_albumentations, convert_bbox_from_albumentations, + convert_bbox_to_albumentations, convert_bboxes_to_albumentations, + denormalize_bbox, + denormalize_bboxes, + normalize_bbox, + normalize_bboxes, ) -from albumentations.core.composition import Compose, ReplayCompose, BboxParams +from albumentations.core.composition import BboxParams, Compose, ReplayCompose from albumentations.core.transforms_interface import NoOp -from albumentations import RandomSizedCrop, RandomResizedCrop, Rotate, RandomCrop @pytest.mark.parametrize( diff --git a/tests/test_functional.py b/tests/test_functional.py index a9bc4bbd4..2ba2ee354 100644 --- a/tests/test_functional.py +++ b/tests/test_functional.py @@ -773,8 +773,8 @@ def test_solarize(dtype): max_value = F.MAX_VALUES_BY_DTYPE[dtype] if dtype == np.dtype("float32"): - img = np.arange(2 ** 10, dtype=np.float32) / (2 ** 10) - img = img.reshape([2 ** 5, 2 ** 5]) + img = np.arange(2**10, dtype=np.float32) / (2**10) + img = img.reshape([2**5, 2**5]) else: max_count = 1024 count = min(max_value + 1, 1024) diff --git a/tests/test_imgaug.py b/tests/test_imgaug.py index 09b84d21d..88a703a67 100644 --- a/tests/test_imgaug.py +++ b/tests/test_imgaug.py @@ -3,26 +3,25 @@ import numpy as np import pytest +import albumentations as A from albumentations import Compose from albumentations.augmentations.bbox_utils import ( convert_bboxes_from_albumentations, convert_bboxes_to_albumentations, ) -import albumentations as A from albumentations.imgaug.transforms import ( - IAAPiecewiseAffine, - IAAFliplr, - IAAFlipud, - IAASuperpixels, - IAASharpen, IAAAdditiveGaussianNoise, - IAAPerspective, IAAAffine, IAACropAndPad, + IAAFliplr, + IAAFlipud, + IAAPerspective, + IAAPiecewiseAffine, + IAASharpen, + IAASuperpixels, ) from tests.utils import set_seed - TEST_SEEDS = (0, 1, 42, 111, 9999) diff --git a/tests/test_imgaug_imports.py b/tests/test_imgaug_imports.py index bc159f997..15df0d7f5 100644 --- a/tests/test_imgaug_imports.py +++ b/tests/test_imgaug_imports.py @@ -2,7 +2,7 @@ import albumentations as A from albumentations.imgaug.stubs import IAAStub -from tests.conftest import skipif_no_imgaug, skipif_imgaug +from tests.conftest import skipif_imgaug, skipif_no_imgaug @skipif_no_imgaug diff --git a/tests/test_keypoint.py b/tests/test_keypoint.py index d2bb2e7f5..7d380af6d 100644 --- a/tests/test_keypoint.py +++ b/tests/test_keypoint.py @@ -1,17 +1,16 @@ import math -import albumentations as A import numpy as np import pytest +import albumentations as A import albumentations.augmentations.geometric.functional as FGeometric - from albumentations.augmentations.keypoints_utils import ( + angle_to_2pi_range, convert_keypoint_from_albumentations, - convert_keypoints_from_albumentations, convert_keypoint_to_albumentations, + convert_keypoints_from_albumentations, convert_keypoints_to_albumentations, - angle_to_2pi_range, ) diff --git a/tests/test_pytorch.py b/tests/test_pytorch.py index 52b0bf251..702f550ed 100644 --- a/tests/test_pytorch.py +++ b/tests/test_pytorch.py @@ -1,6 +1,5 @@ -import pytest - import numpy as np +import pytest import torch from PIL import Image from torchvision.transforms import ColorJitter diff --git a/tools/make_transforms_docs.py b/tools/make_transforms_docs.py index 828a764b2..a3217d266 100644 --- a/tools/make_transforms_docs.py +++ b/tools/make_transforms_docs.py @@ -1,13 +1,12 @@ +import argparse import inspect import os import sys from enum import Enum -import argparse sys.path.append("..") import albumentations # noqa: E402 - IGNORED_CLASSES = { "BasicTransform", "BasicIAATransform", From 14e578ca86ce2fd20e19899eabacaeaacd3c97b0 Mon Sep 17 00:00:00 2001 From: Lemorra Date: Mon, 11 Apr 2022 03:58:15 +0530 Subject: [PATCH 2/7] Updated README and removed comments from code --- README.md | 5 +++++ .../augmentations/eraser/functional.py | 19 +----------------- .../eraser/sampleImages/000277.jpg | Bin 0 -> 173986 bytes .../eraser/sampleImages/000277.png | Bin 0 -> 792877 bytes .../eraser/sampleImages/oldNewLabels.png | Bin 0 -> 94176 bytes 5 files changed, 6 insertions(+), 18 deletions(-) create mode 100644 albumentations/augmentations/eraser/sampleImages/000277.jpg create mode 100755 albumentations/augmentations/eraser/sampleImages/000277.png create mode 100644 albumentations/augmentations/eraser/sampleImages/oldNewLabels.png diff --git a/README.md b/README.md index 9e816cdf2..621d45a49 100644 --- a/README.md +++ b/README.md @@ -225,6 +225,11 @@ Spatial-level transforms will simultaneously change both an input image as well ### Keypoints augmentation +### Object Removal augmentation +Using `startEraser(parentDir, imgType, imgExpType)` one can easily equalise strength of different classes of a dataset. The dataset must contain two folders, 'images' folder and 'labels' folder. Using the 'labels' folder, `startEraser()` finds the minority class and then avoids images that doesn't contain the minority classes for synthesis. Later on the rest of images that has the minority class, `startEraser()` blurs out instances of classes that are in excess from the images. It also returns proper labels of the synthesised images. +![object blurring 1](/albumentations/augmentations/eraser/sampleImages/000277.png) +![object blurring 1](/albumentations/augmentations/eraser/sampleImages/000277.png) +![old new lable](/albumentations/augmentations/eraser/sampleImages/oldNewLabels.png) ## Benchmarking results To run the benchmark yourself, follow the instructions in [benchmark/README.md](https://github.com/albumentations-team/albumentations/blob/master/benchmark/README.md) diff --git a/albumentations/augmentations/eraser/functional.py b/albumentations/augmentations/eraser/functional.py index eb67dfd45..34d7ba5e1 100644 --- a/albumentations/augmentations/eraser/functional.py +++ b/albumentations/augmentations/eraser/functional.py @@ -94,8 +94,6 @@ def startEraser(parentDir, imgType, imgExpType): imgType (string): Type of image present in the Image directory imgExpType (string): Type of synthesised image to be generated """ - # currentDir = os.getcwd() - # parentDir = os.path.dirname(currentDir) imgDir = os.path.join(parentDir, "images") synthImgDir = os.path.join(parentDir, "syntheticImages") synthLabDir = os.path.join(parentDir, "syntheticLabels") @@ -109,7 +107,7 @@ def startEraser(parentDir, imgType, imgExpType): obj1 = MetaData(parentDir, imgType) obj1.loadData() print(obj1.data) - # print(obj1.distribution) + print(obj1.distribution) minorityLabel, minorityStrength = obj1.identifyMinority() for filePath in glob.glob(f"{imgDir}/*"): @@ -128,17 +126,8 @@ def startEraser(parentDir, imgType, imgExpType): coord = labelData[labelname][tag]["coord"] cv2.rectangle(mask, coord[0], coord[1], 0, -1) - # cv.imshow("Mask", mask) - # cv.waitKey(1000) invMask = 255 - mask - # palette = cv2.bitwise_and(img, img, mask=mask) - # print(palette) - # print(invMask) - # cv.imshow("Inverted Mask", invMask) - # cv.waitKey(1000) inPaint = cv2.inpaint(img, invMask, 3, cv2.INPAINT_NS) - # cv.imshow("Inpainted Pic", inPaint) - # cv.waitKey(5000) text = [] for label in labelData.keys(): if label != minorityLabel: @@ -168,8 +157,6 @@ def startEraser(parentDir, imgType, imgExpType): line = " ".join([set1, set2, set3, set4, set5]) text.append(line) - # cv.imshow("ROI", img[ymin:ymax, xmin:xmax, :]) - # cv.waitKey(5000) print(f"Adding these tags of {label}:{tagAdd}") else: minTags = list(labelData[label].keys()) @@ -191,11 +178,7 @@ def startEraser(parentDir, imgType, imgExpType): line = " ".join([set1, set2, set3, set4, set5]) text.append(line) - # cv.imshow("ROI", img[ymin:ymax, xmin:xmax, :]) - # cv.waitKey(5000) - # cv.imshow("Synthetic Image", inPaint) - # cv.waitKey(5000) cv2.imwrite(os.path.join(synthImgDir, f"{filename}.{imgExpType}"), inPaint) print(f"Synthesised synthetic Image for {filename}.") fileContents = "\n".join(text) diff --git a/albumentations/augmentations/eraser/sampleImages/000277.jpg b/albumentations/augmentations/eraser/sampleImages/000277.jpg new file mode 100644 index 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Mon, 11 Apr 2022 04:06:04 +0530 Subject: [PATCH 3/7] Updated README (Image Correction) --- README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 621d45a49..edbf09921 100644 --- a/README.md +++ b/README.md @@ -227,8 +227,11 @@ Spatial-level transforms will simultaneously change both an input image as well ### Object Removal augmentation Using `startEraser(parentDir, imgType, imgExpType)` one can easily equalise strength of different classes of a dataset. The dataset must contain two folders, 'images' folder and 'labels' folder. Using the 'labels' folder, `startEraser()` finds the minority class and then avoids images that doesn't contain the minority classes for synthesis. Later on the rest of images that has the minority class, `startEraser()` blurs out instances of classes that are in excess from the images. It also returns proper labels of the synthesised images. +#### Original Image ![object blurring 1](/albumentations/augmentations/eraser/sampleImages/000277.png) -![object blurring 1](/albumentations/augmentations/eraser/sampleImages/000277.png) +#### Sythesised Image +![object blurring 1](/albumentations/augmentations/eraser/sampleImages/000277.jpg) +#### Newly Generated Label Comparison ![old new lable](/albumentations/augmentations/eraser/sampleImages/oldNewLabels.png) ## Benchmarking results From f0d4353822bd9bb1840d6ff68fe9b415072fc10a Mon Sep 17 00:00:00 2001 From: Lemorra Date: Sun, 29 May 2022 16:05:44 +0530 Subject: [PATCH 4/7] Removed changes made to pre-commit --- albumentations/augmentations/__init__.py | 14 ++++---- .../augmentations/dropout/channel_dropout.py | 7 ++-- .../augmentations/dropout/coarse_dropout.py | 3 +- .../augmentations/dropout/cutout.py | 7 ++-- .../augmentations/dropout/functional.py | 3 +- .../augmentations/dropout/grid_dropout.py | 4 +-- .../augmentations/dropout/mask_dropout.py | 5 +-- albumentations/augmentations/functional.py | 2 +- albumentations/augmentations/transforms.py | 6 ++-- albumentations/random_utils.py | 2 +- benchmark/benchmark.py | 33 +++++++++---------- docs/conf.py | 7 ++-- tests/conftest.py | 3 +- tests/test_bbox.py | 14 ++++---- tests/test_functional.py | 4 +-- tests/test_imgaug.py | 15 +++++---- tests/test_imgaug_imports.py | 2 +- tests/test_keypoint.py | 7 ++-- tests/test_pytorch.py | 3 +- tools/make_transforms_docs.py | 3 +- 20 files changed, 76 insertions(+), 68 deletions(-) diff --git a/albumentations/augmentations/__init__.py b/albumentations/augmentations/__init__.py index 2a22822f3..72b482f1b 100644 --- a/albumentations/augmentations/__init__.py +++ b/albumentations/augmentations/__init__.py @@ -5,18 +5,20 @@ # New transformations goes to individual files listed below from .domain_adaptation import * +from .functional import * + +from .geometric.functional import * +from .geometric.resize import * +from .geometric.rotate import * +from .geometric.transforms import * + from .dropout.channel_dropout import * from .dropout.coarse_dropout import * from .dropout.cutout import * from .dropout.functional import * from .dropout.grid_dropout import * from .dropout.mask_dropout import * -from .eraser.functional import * -from .functional import * -from .geometric.functional import * -from .geometric.resize import * -from .geometric.rotate import * -from .geometric.transforms import * + from .keypoints_utils import * from .transforms import * from .utils import * diff --git a/albumentations/augmentations/dropout/channel_dropout.py b/albumentations/augmentations/dropout/channel_dropout.py index 48b4707ce..45d42c76d 100644 --- a/albumentations/augmentations/dropout/channel_dropout.py +++ b/albumentations/augmentations/dropout/channel_dropout.py @@ -1,10 +1,11 @@ import random -from typing import Any, Mapping, Tuple, Union +from typing import Union, Tuple, Any, Mapping import numpy as np -from albumentations.core.transforms_interface import ImageOnlyTransform - +from albumentations.core.transforms_interface import ( + ImageOnlyTransform, +) from .functional import channel_dropout __all__ = ["ChannelDropout"] diff --git a/albumentations/augmentations/dropout/coarse_dropout.py b/albumentations/augmentations/dropout/coarse_dropout.py index c6b1d5cbc..a82d05e48 100644 --- a/albumentations/augmentations/dropout/coarse_dropout.py +++ b/albumentations/augmentations/dropout/coarse_dropout.py @@ -1,12 +1,13 @@ import random import typing -from typing import Iterable, List, Optional, Tuple, Union +from typing import Optional, List, Tuple, Iterable, Union import numpy as np from ...core.transforms_interface import DualTransform from .functional import cutout + __all__ = ["CoarseDropout"] diff --git a/albumentations/augmentations/dropout/cutout.py b/albumentations/augmentations/dropout/cutout.py index c781c97bb..206f171e3 100644 --- a/albumentations/augmentations/dropout/cutout.py +++ b/albumentations/augmentations/dropout/cutout.py @@ -1,11 +1,12 @@ import random import warnings -from typing import Any, Dict, Tuple, Union +from typing import Union, Any, Dict, Tuple import numpy as np -from albumentations.core.transforms_interface import ImageOnlyTransform - +from albumentations.core.transforms_interface import ( + ImageOnlyTransform, +) from .functional import cutout __all__ = ["Cutout"] diff --git a/albumentations/augmentations/dropout/functional.py b/albumentations/augmentations/dropout/functional.py index d40b51665..759bc4d0c 100644 --- a/albumentations/augmentations/dropout/functional.py +++ b/albumentations/augmentations/dropout/functional.py @@ -1,7 +1,6 @@ -from typing import Iterable, List, Tuple, Union +from typing import List, Tuple, Union, Iterable import numpy as np - from ..functional import preserve_shape __all__ = ["cutout", "channel_dropout"] diff --git a/albumentations/augmentations/dropout/grid_dropout.py b/albumentations/augmentations/dropout/grid_dropout.py index eeeeafdad..de7321a74 100644 --- a/albumentations/augmentations/dropout/grid_dropout.py +++ b/albumentations/augmentations/dropout/grid_dropout.py @@ -1,10 +1,10 @@ import random -from typing import Iterable, Tuple +from typing import Tuple, Iterable import numpy as np -from ...core.transforms_interface import DualTransform from . import functional as F +from ...core.transforms_interface import DualTransform __all__ = ["GridDropout"] diff --git a/albumentations/augmentations/dropout/mask_dropout.py b/albumentations/augmentations/dropout/mask_dropout.py index 25cfd17a2..af69ad181 100644 --- a/albumentations/augmentations/dropout/mask_dropout.py +++ b/albumentations/augmentations/dropout/mask_dropout.py @@ -1,11 +1,12 @@ import random -from typing import Any, Dict, Tuple, Union +from typing import Union, Tuple, Any, Dict import cv2 import numpy as np from skimage.measure import label -from ...core.transforms_interface import DualTransform, to_tuple +from ...core.transforms_interface import DualTransform +from ...core.transforms_interface import to_tuple __all__ = ["MaskDropout"] diff --git a/albumentations/augmentations/functional.py b/albumentations/augmentations/functional.py index a155c2fe3..879165132 100644 --- a/albumentations/augmentations/functional.py +++ b/albumentations/augmentations/functional.py @@ -587,7 +587,7 @@ def move_tone_curve(img, low_y, high_y): # Defines responze of a four-point bezier curve def evaluate_bez(t): - return 3 * (1 - t) ** 2 * t * low_y + 3 * (1 - t) * t**2 * high_y + t**3 + return 3 * (1 - t) ** 2 * t * low_y + 3 * (1 - t) * t ** 2 * high_y + t ** 3 evaluate_bez = np.vectorize(evaluate_bez) remapping = np.rint(evaluate_bez(t) * 255).astype(np.uint8) diff --git a/albumentations/augmentations/transforms.py b/albumentations/augmentations/transforms.py index bab1353df..e5663ecfd 100644 --- a/albumentations/augmentations/transforms.py +++ b/albumentations/augmentations/transforms.py @@ -1822,7 +1822,7 @@ def apply(self, img, gauss=None, **params): def get_params_dependent_on_targets(self, params): image = params["image"] var = random.uniform(self.var_limit[0], self.var_limit[1]) - sigma = var**0.5 + sigma = var ** 0.5 if self.per_channel: gauss = random_utils.normal(self.mean, sigma, image.shape) @@ -2804,7 +2804,7 @@ def get_params(self): / (2 * np.pi * np.sqrt((x - (ksize - 1) / 2) ** 2 + (y - (ksize - 1) / 2) ** 2)), [ksize, ksize], ) - kernel[(ksize - 1) // 2, (ksize - 1) // 2] = cutoff**2 / (4 * np.pi) + kernel[(ksize - 1) // 2, (ksize - 1) // 2] = cutoff ** 2 / (4 * np.pi) # Normalize kernel kernel = kernel.astype(np.float32) / np.sum(kernel) @@ -2982,7 +2982,7 @@ def get_params(self): grid = np.stack(np.meshgrid(ax, ax), axis=-1) # Calculate rotated sigma matrix - d_matrix = np.array([[sigmaX**2, 0], [0, sigmaY**2]]) + d_matrix = np.array([[sigmaX ** 2, 0], [0, sigmaY ** 2]]) u_matrix = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]]) sigma_matrix = np.dot(u_matrix, np.dot(d_matrix, u_matrix.T)) diff --git a/albumentations/random_utils.py b/albumentations/random_utils.py index 063766999..11dd2200f 100644 --- a/albumentations/random_utils.py +++ b/albumentations/random_utils.py @@ -2,7 +2,7 @@ # because numpy can return single number and ndarray import random as py_random -from typing import Any, Optional, Sequence, Type, Union +from typing import Optional, Sequence, Union, Type, Any import numpy as np diff --git a/benchmark/benchmark.py b/benchmark/benchmark.py index 64559ed8c..e7d243279 100644 --- a/benchmark/benchmark.py +++ b/benchmark/benchmark.py @@ -1,37 +1,34 @@ from __future__ import division, print_function - import argparse import math import os import sys from abc import ABC -from collections import defaultdict from timeit import Timer - -import cv2 -import keras_preprocessing.image as keras -import numpy as np -import pandas as pd +from collections import defaultdict import pkg_resources -import solt.core as slc -import solt.transforms as slt -import solt.utils as slu -import torchvision.transforms.functional as torchvision + from Augmentor import Operations, Pipeline -from imgaug import augmenters as iaa from PIL import Image, ImageOps from pytablewriter import MarkdownTableWriter from pytablewriter.style import Style + +import cv2 + from tqdm import tqdm +import numpy as np +import pandas as pd +import torchvision.transforms.functional as torchvision +import keras_preprocessing.image as keras +from imgaug import augmenters as iaa +import solt.transforms as slt +import solt.core as slc +import solt.utils as slu -import albumentations as A import albumentations.augmentations.functional as albumentations +import albumentations as A +from albumentations.augmentations.geometric.functional import rotate, resize, shift_scale_rotate from albumentations.augmentations.crops.functional import random_crop -from albumentations.augmentations.geometric.functional import ( - resize, - rotate, - shift_scale_rotate, -) cv2.setNumThreads(0) # noqa E402 cv2.ocl.setUseOpenCL(False) # noqa E402 diff --git a/docs/conf.py b/docs/conf.py index 2b7230a3a..9b2b49bcb 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -1,11 +1,12 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- import datetime -import os +from typing import Dict, Any +from unittest.mock import MagicMock + import re +import os import sys -from typing import Any, Dict -from unittest.mock import MagicMock sys.path.insert(0, os.path.abspath("../")) diff --git a/tests/conftest.py b/tests/conftest.py index 7706e8d12..319dfe516 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,10 +1,11 @@ -import multiprocessing import sys import warnings +import multiprocessing import numpy as np import pytest + try: import torch # skipcq: PYL-W0611 import torchvision # skipcq: PYL-W0611 diff --git a/tests/test_bbox.py b/tests/test_bbox.py index ec79abf4c..4e4063674 100644 --- a/tests/test_bbox.py +++ b/tests/test_bbox.py @@ -1,19 +1,19 @@ import numpy as np import pytest -from albumentations import RandomCrop, RandomResizedCrop, RandomSizedCrop, Rotate from albumentations.augmentations.bbox_utils import ( + normalize_bbox, + denormalize_bbox, + normalize_bboxes, + denormalize_bboxes, calculate_bbox_area, - convert_bbox_from_albumentations, convert_bbox_to_albumentations, + convert_bbox_from_albumentations, convert_bboxes_to_albumentations, - denormalize_bbox, - denormalize_bboxes, - normalize_bbox, - normalize_bboxes, ) -from albumentations.core.composition import BboxParams, Compose, ReplayCompose +from albumentations.core.composition import Compose, ReplayCompose, BboxParams from albumentations.core.transforms_interface import NoOp +from albumentations import RandomSizedCrop, RandomResizedCrop, Rotate, RandomCrop @pytest.mark.parametrize( diff --git a/tests/test_functional.py b/tests/test_functional.py index 2ba2ee354..a9bc4bbd4 100644 --- a/tests/test_functional.py +++ b/tests/test_functional.py @@ -773,8 +773,8 @@ def test_solarize(dtype): max_value = F.MAX_VALUES_BY_DTYPE[dtype] if dtype == np.dtype("float32"): - img = np.arange(2**10, dtype=np.float32) / (2**10) - img = img.reshape([2**5, 2**5]) + img = np.arange(2 ** 10, dtype=np.float32) / (2 ** 10) + img = img.reshape([2 ** 5, 2 ** 5]) else: max_count = 1024 count = min(max_value + 1, 1024) diff --git a/tests/test_imgaug.py b/tests/test_imgaug.py index 88a703a67..09b84d21d 100644 --- a/tests/test_imgaug.py +++ b/tests/test_imgaug.py @@ -3,25 +3,26 @@ import numpy as np import pytest -import albumentations as A from albumentations import Compose from albumentations.augmentations.bbox_utils import ( convert_bboxes_from_albumentations, convert_bboxes_to_albumentations, ) +import albumentations as A from albumentations.imgaug.transforms import ( - IAAAdditiveGaussianNoise, - IAAAffine, - IAACropAndPad, + IAAPiecewiseAffine, IAAFliplr, IAAFlipud, - IAAPerspective, - IAAPiecewiseAffine, - IAASharpen, IAASuperpixels, + IAASharpen, + IAAAdditiveGaussianNoise, + IAAPerspective, + IAAAffine, + IAACropAndPad, ) from tests.utils import set_seed + TEST_SEEDS = (0, 1, 42, 111, 9999) diff --git a/tests/test_imgaug_imports.py b/tests/test_imgaug_imports.py index 15df0d7f5..bc159f997 100644 --- a/tests/test_imgaug_imports.py +++ b/tests/test_imgaug_imports.py @@ -2,7 +2,7 @@ import albumentations as A from albumentations.imgaug.stubs import IAAStub -from tests.conftest import skipif_imgaug, skipif_no_imgaug +from tests.conftest import skipif_no_imgaug, skipif_imgaug @skipif_no_imgaug diff --git a/tests/test_keypoint.py b/tests/test_keypoint.py index 7d380af6d..d2bb2e7f5 100644 --- a/tests/test_keypoint.py +++ b/tests/test_keypoint.py @@ -1,16 +1,17 @@ import math +import albumentations as A import numpy as np import pytest -import albumentations as A import albumentations.augmentations.geometric.functional as FGeometric + from albumentations.augmentations.keypoints_utils import ( - angle_to_2pi_range, convert_keypoint_from_albumentations, - convert_keypoint_to_albumentations, convert_keypoints_from_albumentations, + convert_keypoint_to_albumentations, convert_keypoints_to_albumentations, + angle_to_2pi_range, ) diff --git a/tests/test_pytorch.py b/tests/test_pytorch.py index 702f550ed..52b0bf251 100644 --- a/tests/test_pytorch.py +++ b/tests/test_pytorch.py @@ -1,5 +1,6 @@ -import numpy as np import pytest + +import numpy as np import torch from PIL import Image from torchvision.transforms import ColorJitter diff --git a/tools/make_transforms_docs.py b/tools/make_transforms_docs.py index a3217d266..828a764b2 100644 --- a/tools/make_transforms_docs.py +++ b/tools/make_transforms_docs.py @@ -1,12 +1,13 @@ -import argparse import inspect import os import sys from enum import Enum +import argparse sys.path.append("..") import albumentations # noqa: E402 + IGNORED_CLASSES = { "BasicTransform", "BasicIAATransform", From 51fff67b8ec8dd72a03e5f939e7c834999b4f2f6 Mon Sep 17 00:00:00 2001 From: Lemorra Date: Mon, 11 Jul 2022 18:25:14 +0530 Subject: [PATCH 5/7] precommit file and import changes --- .pre-commit-config.yaml | 6 +++--- albumentations/augmentations/__init__.py | 1 + 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index cb3a5231f..72f35c27d 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,6 +1,6 @@ repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.1.0 + rev: v3.4.0 hooks: - id: trailing-whitespace - id: end-of-file-fixer @@ -8,7 +8,7 @@ repos: - id: check-json - id: check-yaml - repo: https://github.com/pre-commit/mirrors-isort - rev: v5.10.1 # Use the revision sha / tag you want to point at + rev: 1ba6bfc # Use the revision sha / tag you want to point at hooks: - id: isort args: [ "--profile", "black" ] @@ -18,7 +18,7 @@ repos: - id: black args: [ --config=black.toml ] - repo: https://github.com/pre-commit/mirrors-mypy - rev: v0.942 + rev: v0.910 hooks: - id: mypy additional_dependencies: [ types-PyYAML ] diff --git a/albumentations/augmentations/__init__.py b/albumentations/augmentations/__init__.py index 5f80648d6..29434c624 100644 --- a/albumentations/augmentations/__init__.py +++ b/albumentations/augmentations/__init__.py @@ -10,6 +10,7 @@ from .dropout.functional import * from .dropout.grid_dropout import * from .dropout.mask_dropout import * +from .eraser.functional import * from .functional import * from .geometric.functional import * from .geometric.resize import * From 774a95edb054692b7c502009602ef5c5df923def Mon Sep 17 00:00:00 2001 From: Lemorra Date: Sat, 3 Sep 2022 11:18:41 +0530 Subject: [PATCH 6/7] Removed print statements --- albumentations/augmentations/eraser/functional.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/albumentations/augmentations/eraser/functional.py b/albumentations/augmentations/eraser/functional.py index 34d7ba5e1..10b0c47a7 100644 --- a/albumentations/augmentations/eraser/functional.py +++ b/albumentations/augmentations/eraser/functional.py @@ -106,8 +106,8 @@ def startEraser(parentDir, imgType, imgExpType): obj1 = MetaData(parentDir, imgType) obj1.loadData() - print(obj1.data) - print(obj1.distribution) + # print(obj1.data) + print(f"Identified:{obj1.distribution}") minorityLabel, minorityStrength = obj1.identifyMinority() for filePath in glob.glob(f"{imgDir}/*"): From 382cffb8ad2fc4d8d62aef3aba0ef949bab67ea1 Mon Sep 17 00:00:00 2001 From: Lemorra Date: Thu, 13 Oct 2022 12:11:01 +0530 Subject: [PATCH 7/7] Compose interation possible --- albumentations/augmentations/__init__.py | 2 +- .../augmentations/eraser/__init__.py | 2 +- .../augmentations/eraser/metadata.py | 167 ++++++++++++++++++ 3 files changed, 169 insertions(+), 2 deletions(-) create mode 100644 albumentations/augmentations/eraser/metadata.py diff --git a/albumentations/augmentations/__init__.py b/albumentations/augmentations/__init__.py index 29434c624..86cf248a5 100644 --- a/albumentations/augmentations/__init__.py +++ b/albumentations/augmentations/__init__.py @@ -10,7 +10,7 @@ from .dropout.functional import * from .dropout.grid_dropout import * from .dropout.mask_dropout import * -from .eraser.functional import * +from .eraser.metadata import * from .functional import * from .geometric.functional import * from .geometric.resize import * diff --git a/albumentations/augmentations/eraser/__init__.py b/albumentations/augmentations/eraser/__init__.py index f704280d7..3833b7982 100644 --- a/albumentations/augmentations/eraser/__init__.py +++ b/albumentations/augmentations/eraser/__init__.py @@ -1 +1 @@ -from .functional import * +from .metadata import * diff --git a/albumentations/augmentations/eraser/metadata.py b/albumentations/augmentations/eraser/metadata.py new file mode 100644 index 000000000..377bd301d --- /dev/null +++ b/albumentations/augmentations/eraser/metadata.py @@ -0,0 +1,167 @@ +import glob +import os +import random + +import cv2 +import numpy as np + +from ...core.transforms_interface import ImageOnlyTransform +from . import functional as F + + +def load_label_data(label_file): + label_data = {} + label_data["labels"] = {} + label_data["n_labels"] = {} + with open(label_file) as f: + for line in f: + label = line.split()[0] + if label not in label_data["labels"]: + label_data["labels"][label] = {} + label_data["n_labels"][label] = 1 + else: + label_data["n_labels"][label] += 1 + + numTag = label_data["n_labels"][label] + xmin, ymin, xmax, ymax = line.split()[4:8] + length = abs(float(xmin) - float(xmax)) + breadth = abs(float(ymin) - float(ymax)) + area = length * breadth + + truncation = line.split()[1] + occlusion = line.split()[2] + alpha = line.split()[3] + threeDdim = line.split()[8:11] + location = line.split()[11:14] + rotationY = line.split()[14] + + label_data["labels"][label][f"l{numTag}"] = { + "coord": [(int(float(xmin)), int(float(ymin))), (int(float(xmax)), int(float(ymax)))], + "area": area, + "Truncation": truncation, + "Occlusion": occlusion, + "Alpha": alpha, + "ThreeDdim": threeDdim, + "Location": location, + "RotationY": rotationY, + } + + return label_data + + +def generate_img(img, label_names, label_count, minority_label, new_label_file_name, parent_dir): + mask = np.full(img.shape[:2], 255, dtype="uint8") + for label_name in label_names: + for tag in label_names[label_name]: + coord = label_names[label_name][tag]["coord"] + cv2.rectangle(mask, coord[0], coord[1], 0, -1) + + inv_mask = 255 - mask + inPaint = cv2.inpaint(img, inv_mask, 3, cv2.INPAINT_NS) + + text = [] + + for label in label_names: + if label != minority_label: + tags = list(label_names[label].keys()) + n_tags = label_count[label] + n_add = label_count[minority_label] + + if n_tags > n_add: + tag_add = random.sample(tags, n_add) + else: + tag_add = tags + + for tag in tag_add: + set1 = " ".join( + [ + label, + label_names[label][tag]["Truncation"], + label_names[label][tag]["Occlusion"], + label_names[label][tag]["Alpha"], + ] + ) + set3 = " ".join(label_names[label][tag]["ThreeDdim"]) + set4 = " ".join(label_names[label][tag]["Location"]) + set5 = label_names[label][tag]["RotationY"] + + (xmin, ymin), (xmax, ymax) = label_names[label][tag]["coord"] + set2 = " ".join([str(xmin), str(ymin), str(xmax), str(ymax)]) + inPaint[ymin:ymax, xmin:xmax, :] = img[ymin:ymax, xmin:xmax, :] + + line = " ".join([set1, set2, set3, set4, set5]) + text.append(line) + print(f"Adding these tags of {label}:{tag_add}") + else: + minTags = list(label_names[label].keys()) + for tag in minTags: + set1 = " ".join( + [ + label, + label_names[label][tag]["Truncation"], + label_names[label][tag]["Occlusion"], + label_names[label][tag]["Alpha"], + ] + ) + set3 = " ".join(label_names[label][tag]["ThreeDdim"]) + set4 = " ".join(label_names[label][tag]["Location"]) + set5 = label_names[label][tag]["RotationY"] + (xmin, ymin), (xmax, ymax) = label_names[label][tag]["coord"] + set2 = " ".join([str(xmin), str(ymin), str(xmax), str(ymax)]) + inPaint[ymin:ymax, xmin:xmax, :] = img[ymin:ymax, xmin:xmax, :] + + line = " ".join([set1, set2, set3, set4, set5]) + text.append(line) + file_contents = "\n".join(text) + with open(os.path.join(parent_dir, f"{new_label_file_name}.txt"), "w") as f: + f.write(file_contents) + + return inPaint + + +def apply_earser(img, label_file, minority_label, new_label_file_name): + try: + if os.path.getsize(label_file) > 0: + label_data = load_label_data(label_file) + label_names = label_data["labels"] + if minority_label not in label_names: + raise RuntimeWarning(f"Given label file doesn't have {minority_label} label!") + else: + label_count = label_data["n_labels"] + parent_dir = os.path.dirname(label_file) + img = generate_img(img, label_names, label_count, minority_label, new_label_file_name, parent_dir) + else: + raise RuntimeError(f"{label_file} is empty!") + except OSError as e: + print(f"Error reading label file: {e}") + + return img + + +class MetaData(ImageOnlyTransform): + """Class to extract data from labels of kitti format""" + + def __init__(self, always_apply=False, p=0.5): + """ + Erase instances of labels in image. + + Args: + label_file (_type_): _description_ + minority_label (_type_): _description_ + new_label_file_name (_type_): _description_ + always_apply (bool, optional): _description_. Defaults to False. + p (float, optional): _description_. Defaults to 0.5. + """ + super().__init__(always_apply=always_apply, p=p) + + def __call__(self, **data): + self.label_file = data["label_file"] + self.minority_label = data["minority_label"] + self.new_label_file_name = data["new_label_file_name"] + + data["image"] = self.apply(**data) + + return data + + def apply(self, image, label_file, minority_label, new_label_file_name, **params): + return apply_earser(image, label_file, minority_label, new_label_file_name)