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.gitignore
vendored
54
.gitignore
vendored
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data
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data/
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archive.zip
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# https://github.com/microsoft/vscode-python/blob/main/.gitignore
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.DS_Store
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.huskyrc.json
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out
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log.log
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**/node_modules
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*.pyc
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*.vsix
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envVars.txt
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**/.vscode/.ropeproject/**
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**/testFiles/**/.cache/**
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*.noseids
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.nyc_output
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.vscode-test
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__pycache__
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npm-debug.log
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**/.mypy_cache/**
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!yarn.lock
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coverage/
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cucumber-report.json
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**/.vscode-test/**
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**/.vscode test/**
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**/.vscode-smoke/**
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**/.venv*/
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port.txt
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precommit.hook
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python_files/lib/**
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python_files/get-pip.py
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debug_coverage*/**
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languageServer/**
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languageServer.*/**
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bin/**
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obj/**
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.pytest_cache
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tmp/**
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.python-version
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.vs/
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test-results*.xml
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xunit-test-results.xml
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build/ci/performance/performance-results.json
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!build/
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debug*.log
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debugpy*.log
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pydevd*.log
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nodeLanguageServer/**
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nodeLanguageServer.*/**
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dist/**
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# translation files
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*.xlf
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package.nls.*.json
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l10n/
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@ -1,55 +0,0 @@
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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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mainPath="data/"
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pathToTrainAndValidDate = mainPath + "%s/**/*.*"
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pathToTestDataset = mainPath + "/test"
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originalDatasetName = "original dataset"
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class DataManager:
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def downloadData(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 unzipData(self, fileName, pathToExtract):
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if not os.path.exists(mainPath):
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os.makedirs("data")
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ZipFile(fileName).extractall(mainPath + pathToExtract)
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shutil.move("data/original dataset/test/test", "data", copy_function = shutil.copytree)
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shutil.move("data/original dataset/New Plant Diseases Dataset(Augmented)/New Plant Diseases Dataset(Augmented)/train", "data/original dataset/train", copy_function = shutil.copytree)
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shutil.move("data/original dataset/New Plant Diseases Dataset(Augmented)/New Plant Diseases Dataset(Augmented)/valid", "data/original dataset/valid", copy_function = shutil.copytree)
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shutil.rmtree("data/original dataset/New Plant Diseases Dataset(Augmented)")
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shutil.rmtree("data/Detection-of-plant-diseases/data/original dataset/test")
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def writeImageToGivenPath(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 resizeDataset(self, soruceDatasetName, width, height):
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if not os.path.exists(mainPath + "resized dataset"):
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for file in glob.glob(pathToTrainAndValidDate % soruceDatasetName, recursive=True):
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pathToFile = file.replace("\\","/")
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image = cv2.imread(pathToFile)
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image = cv2.resize(image, (width, height))
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newPath = pathToFile.replace(soruceDatasetName,"resized dataset")
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self.writeImageToGivenPath(image,newPath)
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def sobelx(self, soruceDatasetName):
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if not os.path.exists(mainPath + "sobel dataset"):
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for file in glob.glob(pathToTrainAndValidDate % soruceDatasetName, recursive=True):
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pathToFile = file.replace("\\","/")
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image = cv2.imread(pathToFile)
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sobel = cv2.Sobel(image,cv2.CV_64F,1,0,ksize=5)
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newPath = pathToFile.replace(soruceDatasetName,"sobel dataset")
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self.writeImageToGivenPath(sobel,newPath)
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dataManager = DataManager()
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dataManager.downloadData()
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dataManager.unzipData("archive.zip","original dataset")
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dataManager.resizeDataset("original dataset", 64, 64)
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dataManager.sobelx("resized dataset")
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8
Makefile
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8
Makefile
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.PHONY: download-dataset sobel-dataset
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download-dataset:
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python3 ./file_manager/data_manager.py --download
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sobel-dataset:
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python3 ./file_manager/data_manager.py --sobel
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0
file_manager/__init__.py
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0
file_manager/__init__.py
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81
file_manager/data_manager.py
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81
file_manager/data_manager.py
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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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shutil.rmtree(
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"data/Detection-of-plant-diseases/data/original dataset/test")
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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(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(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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5
requirements.txt
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5
requirements.txt
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tensorflow==2.16.1
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tensorflow-io==0.37.0
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numpy==1.26.4
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opencv-python==4.9.0.80
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wget==3.2
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