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Update app.py
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app.py
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from concurrent.futures import ThreadPoolExecutor
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from deepface import DeepFace # Advanced face recognition for better accuracy
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# Load Google Drive API credentials
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SCOPES = ['https://www.googleapis.com/auth/drive']
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SERVICE_ACCOUNT_FILE = './salesforce-api-439514-d6b432a2e20e.json' # Assuming file in current directory
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credentials = service_account.Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes=SCOPES)
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drive_service = build('drive', 'v3', credentials=credentials)
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# Folder IDs
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aadhar_folder_id = '1Qtb5DYzSFE67Mbb5ZgDIqWUtdJaDD2F4'
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cphotos_folder_id = '1DGeRqRbCPcfLDdEgP0h5fyX-MF8EQ8AH'
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suspects_folder_id = '1N3RMhVD0OygeufLPYod6IYLtqzvlm3Jv'
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def list_files_in_folder(folder_id):
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print(f"Listing files in folder ID: {folder_id}")
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query = f"'{folder_id}' in parents and trashed=false"
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try:
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results = drive_service.files().list(q=query, pageSize=1000, fields="files(id, name, mimeType, owners, parents)").execute()
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files = results.get('files', [])
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if not files:
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print(f"No files found in folder ID: {folder_id}. Ensure that the folder has files and the service account has access.")
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else:
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print(f"Found {len(files)} files in folder ID: {folder_id}.")
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return files
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except Exception as e:
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print(f"Error listing files in folder ID: {folder_id} - {e}")
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return []
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def download_file(file_id, file_name):
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print(f"Attempting to download file: {file_name} (ID: {file_id})")
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if not file_name.lower().endswith(('.jpg', '.jpeg', '.png')):
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file_name += ".jpg"
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try:
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request = drive_service.files().get_media(fileId=file_id)
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file_io = io.BytesIO()
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downloader = MediaIoBaseDownload(file_io, request)
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done = False
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while not done:
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_, done = downloader.next_chunk()
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file_io.seek(0)
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with open(file_name, 'wb') as f:
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f.write(file_io.read())
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print(f"Successfully downloaded file: {file_name}")
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return file_name
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except Exception as e:
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print(f"Error downloading file ID: {file_id} - {e}")
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return None
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def verify_and_fix_image(image_path):
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try:
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with Image.open(image_path) as img:
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img.verify()
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with Image.open(image_path) as img:
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img.save(image_path)
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print(f"Image verified and cleaned: {image_path}")
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return True
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except Exception as e:
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print(f"Image verification failed for {image_path}. Error: {e}")
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return False
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def upload_file(file_path, folder_id):
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print(f"Uploading file: {file_path} to folder ID: {folder_id}")
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file_metadata = {'name': os.path.basename(file_path), 'parents': [folder_id]}
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media = MediaFileUpload(file_path, resumable=True)
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try:
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file = drive_service.files().create(body=file_metadata, media_body=media, fields='id').execute()
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print(f"Uploaded file ID: {file.get('id')}")
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return file.get('id')
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except Exception as e:
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print(f"Error uploading file {file_path} to folder ID: {folder_id} - {e}")
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return None
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def process_images(aadhar_folder_id, cphotos_folder_id, suspects_folder_id):
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print("Starting processing of images...")
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aadhar_files = list_files_in_folder(aadhar_folder_id)
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cphotos_files = list_files_in_folder(cphotos_folder_id)
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aadhar_embeddings = []
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with ThreadPoolExecutor() as executor:
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future_to_aadhar = {executor.submit(download_file, file['id'], file['name']): file['name'] for file in aadhar_files}
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for future in future_to_aadhar:
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file_name = future_to_aadhar[future]
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try:
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file_path = future.result()
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if file_path:
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embedding = DeepFace.represent(img_path=file_path, model_name='VGG-Face')
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if embedding:
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aadhar_embeddings.append((file_name, embedding))
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except Exception as e:
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print(f"Error processing Aadhar file {file_name}: {e}")
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if not aadhar_embeddings:
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print("No valid Aadhar face embeddings found. Exiting.")
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return
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unmatched_files = []
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with ThreadPoolExecutor() as executor:
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future_to_cphoto = {executor.submit(download_file, file['id'], file['name']): file for file in cphotos_files}
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for future in future_to_cphoto:
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file = future_to_cphoto[future]
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try:
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file_path = future.result()
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if not file_path:
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continue
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embedding_cctv = DeepFace.represent(img_path=file_path, model_name='VGG-Face')
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if not embedding_cctv:
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continue
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matched = False
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for aadhar_name, aadhar_embedding in aadhar_embeddings:
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result = DeepFace.verify(embedding_cctv, aadhar_embedding, model_name='VGG-Face')
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if result['verified']:
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matched = True
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print(f"Match found for CCTV file: {file['name']} with Aadhar file: {aadhar_name}")
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break
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if not matched:
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unmatched_files.append(file_path)
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print(f"Unmatched image queued for upload: {file['name']}")
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except Exception as e:
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print(f"Error processing CCTV file {file['name']}: {e}")
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with ThreadPoolExecutor() as executor:
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for file_path in unmatched_files:
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executor.submit(upload_file, file_path, suspects_folder_id)
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def main():
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start_time = time.time()
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print("Script started...")
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process_images(aadhar_folder_id, cphotos_folder_id, suspects_folder_id)
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end_time = time.time()
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print(f"Script completed in {end_time - start_time:.2f} seconds.")
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if __name__ == "__main__":
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main()
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google-api-python-client==2.52.0
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google-auth==2.12.0
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google-auth-oauthlib==0.5.3
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oauth2client==4.1.3
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opencv-python==4.5.5.64
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numpy==1.21.4
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Pillow==9.2.0
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deepface==0.0.75
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