Add detailed error logging to infer-aw-contour endpoint

backend/app.py

@@ -9,6 +9,7 @@ import os
 from io import BytesIO
 from PIL import Image
 import uvicorn
+import traceback
 from backend.inference import infer_aw_contour, analyze_frame, analyze_video_frame
 
 app = FastAPI(title="Pathora Colposcopy API", version="1.0.0")
@@ -52,11 +53,15 @@ async def infer_aw_contour_endpoint(file: UploadFile = File(...), conf_threshold
     try:
         # Read image file
         image_data = await file.read()
+        print(f"✅ File received, size: {len(image_data)} bytes")
         
         # Try to open image - this will work regardless of content type
         try:
             image = Image.open(BytesIO(image_data))
+            print(f"✅ Image opened, mode: {image.mode}, size: {image.size}")
         except Exception as e:
+            print(f"❌ Image open error: {e}")
+            traceback.print_exc()
             raise HTTPException(status_code=400, detail=f"Invalid image file: {str(e)}")
         
         # Convert to numpy array and BGR format (OpenCV uses BGR)
@@ -69,9 +74,12 @@ async def infer_aw_contour_endpoint(file: UploadFile = File(...), conf_threshold
             image = image.convert('RGB')
         
         frame = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+        print(f"✅ Frame converted, shape: {frame.shape}")
         
         # Run inference - returns dict with 'overlay', 'contours', 'detections', etc.
+        print(f"🔄 Running infer_aw_contour with conf_threshold={conf_threshold}")
         result = infer_aw_contour(frame, conf_threshold=conf_threshold)
+        print(f"✅ Inference complete, detections: {result['detections']}")
         
         # Convert result overlay back to RGB for JSON serialization
         if result["overlay"] is not None:
@@ -84,8 +92,10 @@ async def infer_aw_contour_endpoint(file: UploadFile = File(...), conf_threshold
             buffer.seek(0)
             import base64
             image_base64 = base64.b64encode(buffer.getvalue()).decode()
+            print(f"✅ Image encoded to base64, size: {len(image_base64)} chars")
         else:
             image_base64 = None
+            print("⚠️  No overlay returned from inference")
         
         return JSONResponse({
             "status": "success",
@@ -97,6 +107,8 @@ async def infer_aw_contour_endpoint(file: UploadFile = File(...), conf_threshold
         })
     
     except Exception as e:
+        print(f"❌ EXCEPTION in infer_aw_contour:")
+        traceback.print_exc()
         raise HTTPException(status_code=500, detail=f"Error during inference: {str(e)}")