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Update app.py
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import os
import cv2
from google.oauth2 import service_account
from googleapiclient.discovery import build
from googleapiclient.http import MediaIoBaseDownload, MediaFileUpload
import io
import time
from PIL import Image
from concurrent.futures import ThreadPoolExecutor
from deepface import DeepFace # Advanced face recognition for better accuracy
# Load Google Drive API credentials
SCOPES = ['https://www.googleapis.com/auth/drive']
SERVICE_ACCOUNT_FILE = './salesforce-api-439514-d6b432a2e20e.json' # Assuming file in current directory
credentials = service_account.Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes=SCOPES)
drive_service = build('drive', 'v3', credentials=credentials)
# Folder IDs
aadhar_folder_id = '1Qtb5DYzSFE67Mbb5ZgDIqWUtdJaDD2F4'
cphotos_folder_id = '1DGeRqRbCPcfLDdEgP0h5fyX-MF8EQ8AH'
suspects_folder_id = '1N3RMhVD0OygeufLPYod6IYLtqzvlm3Jv'
def list_files_in_folder(folder_id):
print(f"Listing files in folder ID: {folder_id}")
query = f"'{folder_id}' in parents and trashed=false"
try:
results = drive_service.files().list(q=query, pageSize=1000, fields="files(id, name, mimeType, owners, parents)").execute()
files = results.get('files', [])
if not files:
print(f"No files found in folder ID: {folder_id}. Ensure that the folder has files and the service account has access.")
else:
print(f"Found {len(files)} files in folder ID: {folder_id}.")
return files
except Exception as e:
print(f"Error listing files in folder ID: {folder_id} - {e}")
return []
def download_file(file_id, file_name):
print(f"Attempting to download file: {file_name} (ID: {file_id})")
if not file_name.lower().endswith(('.jpg', '.jpeg', '.png')):
file_name += ".jpg"
try:
request = drive_service.files().get_media(fileId=file_id)
file_io = io.BytesIO()
downloader = MediaIoBaseDownload(file_io, request)
done = False
while not done:
_, done = downloader.next_chunk()
file_io.seek(0)
with open(file_name, 'wb') as f:
f.write(file_io.read())
print(f"Successfully downloaded file: {file_name}")
return file_name
except Exception as e:
print(f"Error downloading file ID: {file_id} - {e}")
return None
def verify_and_fix_image(image_path):
try:
with Image.open(image_path) as img:
img.verify()
with Image.open(image_path) as img:
img.save(image_path)
print(f"Image verified and cleaned: {image_path}")
return True
except Exception as e:
print(f"Image verification failed for {image_path}. Error: {e}")
return False
def upload_file(file_path, folder_id):
print(f"Uploading file: {file_path} to folder ID: {folder_id}")
file_metadata = {'name': os.path.basename(file_path), 'parents': [folder_id]}
media = MediaFileUpload(file_path, resumable=True)
try:
file = drive_service.files().create(body=file_metadata, media_body=media, fields='id').execute()
print(f"Uploaded file ID: {file.get('id')}")
return file.get('id')
except Exception as e:
print(f"Error uploading file {file_path} to folder ID: {folder_id} - {e}")
return None
def process_images(aadhar_folder_id, cphotos_folder_id, suspects_folder_id):
print("Starting processing of images...")
aadhar_files = list_files_in_folder(aadhar_folder_id)
cphotos_files = list_files_in_folder(cphotos_folder_id)
aadhar_embeddings = []
with ThreadPoolExecutor() as executor:
future_to_aadhar = {executor.submit(download_file, file['id'], file['name']): file['name'] for file in aadhar_files}
for future in future_to_aadhar:
file_name = future_to_aadhar[future]
try:
file_path = future.result()
if file_path:
embedding = DeepFace.represent(img_path=file_path, model_name='VGG-Face')
if embedding:
aadhar_embeddings.append((file_name, embedding))
except Exception as e:
print(f"Error processing Aadhar file {file_name}: {e}")
if not aadhar_embeddings:
print("No valid Aadhar face embeddings found. Exiting.")
return
unmatched_files = []
with ThreadPoolExecutor() as executor:
future_to_cphoto = {executor.submit(download_file, file['id'], file['name']): file for file in cphotos_files}
for future in future_to_cphoto:
file = future_to_cphoto[future]
try:
file_path = future.result()
if not file_path:
continue
embedding_cctv = DeepFace.represent(img_path=file_path, model_name='VGG-Face')
if not embedding_cctv:
continue
matched = False
for aadhar_name, aadhar_embedding in aadhar_embeddings:
result = DeepFace.verify(embedding_cctv, aadhar_embedding, model_name='VGG-Face')
if result['verified']:
matched = True
print(f"Match found for CCTV file: {file['name']} with Aadhar file: {aadhar_name}")
break
if not matched:
unmatched_files.append(file_path)
print(f"Unmatched image queued for upload: {file['name']}")
except Exception as e:
print(f"Error processing CCTV file {file['name']}: {e}")
with ThreadPoolExecutor() as executor:
for file_path in unmatched_files:
executor.submit(upload_file, file_path, suspects_folder_id)
def main():
start_time = time.time()
print("Script started...")
process_images(aadhar_folder_id, cphotos_folder_id, suspects_folder_id)
end_time = time.time()
print(f"Script completed in {end_time - start_time:.2f} seconds.")
if __name__ == "__main__":
main()