Delete main.py

main.py

@@ -1,93 +0,0 @@
-from fastapi import FastAPI
-from pydantic import BaseModel
-import cv2
-from deepface import DeepFace
-import tempfile
-import requests
-import shutil
-import logging
-from typing import Optional
-
-# Configure logging
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-app = FastAPI()
-
-# Define the request model
-class FaceVerificationRequest(BaseModel):
-    id_url: str
-    ref_url: str
-
-def download_image(url: str) -> Optional[str]:
-    """Downloads an image from a URL and saves it to a temporary file."""
-    try:
-        response = requests.get(url, stream=True)
-        response.raise_for_status()  
-        temp_path = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg").name
-        with open(temp_path, "wb") as f:
-            shutil.copyfileobj(response.raw, f)
-        logger.info(f"Image downloaded successfully: {url}")
-        return temp_path
-    except requests.exceptions.RequestException as e:
-        logger.error(f"Failed to download image from {url}: {e}")
-        return None
-
-def detect_and_crop_face(image_path, detector_backend="mtcnn") -> Optional[str]:
-    """Detects and crops the face from an image."""
-    try:
-        faces = DeepFace.extract_faces(img_path=image_path, detector_backend=detector_backend, enforce_detection=False)
-        if not faces:
-            logger.warning("No faces detected.")
-            return None
-        
-        face_info = faces[0]
-        facial_area = face_info.get("facial_area", {})
-        if not facial_area:
-            logger.warning("No valid facial area found.")
-            return None
-        
-        x, y, w, h = facial_area["x"], facial_area["y"], facial_area["w"], facial_area["h"]
-        image = cv2.imread(image_path)
-        if image is None or w <= 0 or h <= 0:
-            logger.error("Invalid face cropping dimensions.")
-            return None
-        
-        cropped_face = image[y:y+h, x:x+w]
-        temp_path = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg").name
-        cv2.imwrite(temp_path, cropped_face)
-        logger.info(f"Face successfully cropped and saved at {temp_path}")
-        return temp_path  
-    except Exception as e:
-        logger.error(f"Error during face detection: {e}")
-        return None
-
-@app.post("/verify")
-async def verify_face(request: FaceVerificationRequest):
-    """Verifies whether two faces belong to the same person."""
-    try:
-        id_path = download_image(request.id_url)
-        ref_path = download_image(request.ref_url)
-        
-        if not id_path or not ref_path:
-            return {"error": "Failed to download images."}
-        
-        cropped_face_path = detect_and_crop_face(id_path)
-        if cropped_face_path:
-            result = DeepFace.verify(
-                img1_path=cropped_face_path, 
-                img2_path=ref_path, 
-                model_name="Facenet", 
-                detector_backend="mtcnn"
-            )
-            threshold = 0.6  
-            distance = result.get("distance", 1.0)
-            is_match = distance < threshold
-            
-            logger.info(f"Face verification result: {result}")
-            return {"match": is_match}
-        else:
-            return {"error": "Face detection failed for ID card image."}
-    except Exception as e:
-        logger.error(f"Verification failed: {e}")
-        return {"error": str(e)}