Update main.py

main.py

@@ -19,6 +19,11 @@ def load_model():
     model = Model(device='cuda' if torch.cuda.is_available() else 'cpu')
     model.load_model('cartoon4')
 
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+
 @app.post("/upload/")
 async def process_image(file: UploadFile = File(...), top: int = Form(...), bottom: int = Form(...), left: int = Form(...), right: int = Form(...)):
     global model
@@ -31,10 +36,18 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
     # Convert the uploaded image to numpy array
     nparr = np.frombuffer(contents, np.uint8)
     frame_rgb = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    logging.info(f"Uploaded image shape: {frame_rgb.shape}")
 
     # Process the uploaded image
     aligned_face, instyle, message = model.detect_and_align_image(frame_rgb, top, bottom, left, right)
+    if aligned_face is None or instyle is None:
+        logging.error("Failed to process the image: No face detected or alignment failed.")
+        return {"error": message}
+
     processed_image, message = model.image_toonify(aligned_face, instyle, model.exstyle, style_degree=0.5, style_type='cartoon4')
+    if processed_image is None:
+        logging.error("Failed to toonify the image.")
+        return {"error": message}
 
     # Convert BGR to RGB
     processed_image_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
@@ -44,8 +57,6 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
 
     # Return the processed image as a streaming response
     return StreamingResponse(BytesIO(encoded_image.tobytes()), media_type="image/jpeg")
-
-
 # Mount static files directory
 app.mount("/", StaticFiles(directory="AB", html=True), name="static")