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import requests
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import csv
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import mimetypes
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from io import BytesIO
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from PIL import Image
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from surya.ocr import run_ocr
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from surya.model.detection.model import load_model as load_det_model, load_processor as load_det_processor
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from surya.model.recognition.model import load_model as load_rec_model
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from surya.model.recognition.processor import load_processor as load_rec_processor
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def get_github_contents(repo_url):
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parts = repo_url.rstrip('/').split('/')
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user = parts[-2]
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repo = parts[-1]
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api_url = f"https://api.github.com/repos/{user}/{repo}/contents/"
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response = requests.get(api_url)
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response.raise_for_status()
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return response.json()
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def process_contents(contents, paths=[], parent_path=""):
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langs = ["en"]
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det_processor, det_model = load_det_processor(), load_det_model()
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rec_model, rec_processor = load_rec_model(), load_rec_processor()
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for item in contents:
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path = parent_path + item['name']
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if item['type'] == 'dir':
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dir_contents = requests.get(item['url']).json()
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process_contents(dir_contents, paths, path + "/")
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else:
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mime_type, _ = mimetypes.guess_type(item['name'])
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if mime_type and mime_type.split('/')[0] == 'image':
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image_content = requests.get(item['download_url']).content
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image = Image.open(BytesIO(image_content))
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predictions = run_ocr([image], [langs], det_model, det_processor, rec_model, rec_processor)
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paths.append({"path": path, "content": ""})
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return paths
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def write_to_csv(data, output_file):
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if data:
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with open(output_file, 'w', newline='', encoding='utf-8') as csvfile:
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fieldnames = ['path', 'content']
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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writer.writeheader()
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for row in data:
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writer.writerow(row)
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else:
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print("No data to write to CSV.")
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if __name__ == "__main__":
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repo_url = input("Enter GitHub repository URL: ")
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contents = get_github_contents(repo_url)
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paths = process_contents(contents)
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write_to_csv(paths, "repo_ocr.csv")
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print(f"CSV file 'repo_ocr.csv' generated successfully with {len(paths)} entries.")
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