84 lines
4.0 KiB
Python
84 lines
4.0 KiB
Python
import glob
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import shutil
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import cv2
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from zipfile import ZipFile
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import os
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import wget
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import argparse
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from pathlib import Path
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main_path = Path("data/")
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path_to_train_and_valid = main_path / "%s/**/*.*"
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path_to_test_dataset = main_path / "test"
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original_dataset_name = "original_dataset"
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parser = argparse.ArgumentParser()
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parser.add_argument("--download", action="store_true",
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help="Download the data")
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parser.add_argument("--sobel", action="store_true",
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help="Apply Sobel filter to the dataset")
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args = parser.parse_args()
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class DataManager:
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def download_data(self):
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if not os.path.isfile("archive.zip"):
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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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")
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def unzip_data(self, file_name, path_to_extract):
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full_path_to_extract = main_path / path_to_extract
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old_path = "New Plant Diseases Dataset(Augmented)/New Plant Diseases Dataset(Augmented)"
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if not os.path.exists(main_path):
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os.makedirs(main_path)
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ZipFile(file_name).extractall(full_path_to_extract)
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# shutil.move("data/test/test",
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# full_path_to_extract, copy_function=shutil.copytree)
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shutil.move(full_path_to_extract / old_path / "train",
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full_path_to_extract / "train", copy_function=shutil.copytree)
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shutil.move(full_path_to_extract / old_path / "valid",
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full_path_to_extract / "valid", copy_function=shutil.copytree)
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shutil.rmtree(
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full_path_to_extract / "New Plant Diseases Dataset(Augmented)"
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)
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shutil.rmtree(
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full_path_to_extract / "new plant diseases dataset(augmented)"
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)
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def write_image(self, image, path):
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os.makedirs(path.rsplit('/', 1)[0], exist_ok=True)
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cv2.imwrite(path, image)
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def resize_dataset(self, source_dataset_name, width, height):
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dataset_name = "resized_dataset"
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if not os.path.exists(main_path / dataset_name):
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for file in glob.glob(str(path_to_train_and_valid) % source_dataset_name, recursive=True):
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path_to_file = file.replace("\\", "/")
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image = cv2.imread(path_to_file)
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image = cv2.resize(image, (width, height))
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new_path = path_to_file.replace(
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source_dataset_name, dataset_name)
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self.write_image(image, new_path)
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def sobelx(self, source_dataset_name):
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dataset_name = "sobel_dataset"
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if not os.path.exists(main_path / dataset_name):
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for file in glob.glob(str(path_to_train_and_valid) % source_dataset_name, recursive=True):
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path_to_file = file.replace("\\", "/")
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image = cv2.imread(path_to_file)
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sobel = cv2.Sobel(image, cv2.CV_64F, 1, 0, ksize=5)
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new_path = path_to_file.replace(
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source_dataset_name, dataset_name)
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self.write_image(sobel, new_path)
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if __name__ == "__main__":
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data_manager = DataManager()
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if args.download:
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data_manager.download_data()
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data_manager.unzip_data("archive.zip", original_dataset_name)
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data_manager.resize_dataset(original_dataset_name, 64, 64)
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if args.sobel:
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data_manager.sobelx("resized_dataset")
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