import glob import shutil import cv2 from zipfile import ZipFile import os import wget import argparse from pathlib import Path main_path = Path("data/") path_to_train_and_valid = main_path / "%s/**/*.*" path_to_test_dataset = main_path / "test" original_dataset_name = "original_dataset" parser = argparse.ArgumentParser() parser.add_argument("--download", action="store_true", help="Download the data") parser.add_argument("--sobel", action="store_true", help="Apply Sobel filter to the dataset") args = parser.parse_args() class DataManager: def download_data(self): if not os.path.isfile("archive.zip"): wget.download("https://storage.googleapis.com/kaggle-data-sets/78313/182633/bundle/archive.zip?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=gcp-kaggle-com%40kaggle-161607.iam.gserviceaccount.com%2F20240502%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20240502T181500Z&X-Goog-Expires=259200&X-Goog-SignedHeaders=host&X-Goog-Signature=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") def unzip_data(self, file_name, path_to_extract): full_path_to_extract = main_path / path_to_extract old_path = "New Plant Diseases Dataset(Augmented)/New Plant Diseases Dataset(Augmented)" if not os.path.exists(main_path): os.makedirs(main_path) ZipFile(file_name).extractall(full_path_to_extract) # shutil.move("data/test/test", # full_path_to_extract, copy_function=shutil.copytree) shutil.move(full_path_to_extract / old_path / "train", full_path_to_extract / "train", copy_function=shutil.copytree) shutil.move(full_path_to_extract / old_path / "valid", full_path_to_extract / "valid", copy_function=shutil.copytree) shutil.rmtree( full_path_to_extract / "New Plant Diseases Dataset(Augmented)" ) shutil.rmtree( full_path_to_extract / "new plant diseases dataset(augmented)" ) def write_image(self, image, path): os.makedirs(path.rsplit('/', 1)[0], exist_ok=True) cv2.imwrite(path, image) def resize_dataset(self, source_dataset_name, width, height): dataset_name = "resized_dataset" if not os.path.exists(main_path / dataset_name): for file in glob.glob(str(path_to_train_and_valid) % source_dataset_name, recursive=True): path_to_file = file.replace("\\", "/") image = cv2.imread(path_to_file) image = cv2.resize(image, (width, height)) new_path = path_to_file.replace( source_dataset_name, dataset_name) self.write_image(image, new_path) def sobelx(self, source_dataset_name): dataset_name = "sobel_dataset" if not os.path.exists(main_path / dataset_name): for file in glob.glob(str(path_to_train_and_valid) % source_dataset_name, recursive=True): path_to_file = file.replace("\\", "/") image = cv2.imread(path_to_file) sobel = cv2.Sobel(image, cv2.CV_64F, 1, 0, ksize=5) new_path = path_to_file.replace( source_dataset_name, dataset_name) self.write_image(sobel, new_path) if __name__ == "__main__": data_manager = DataManager() if args.download: data_manager.download_data() data_manager.unzip_data("archive.zip", original_dataset_name) data_manager.resize_dataset(original_dataset_name, 64, 64) if args.sobel: data_manager.sobelx("resized_dataset")