Update main.py

main.py

@@ -23,17 +23,17 @@ async def root():
 async def predict(request: ImageRequest):
     # Check if the image string is empty
     if not request.image:
-        return {"error": "Empty image string"}
+        return {"error": "Invalid Image"}
     
     try:
         # Attempt to decode Base64 string to bytes
         image_bytes = base64.b64decode(request.image, validate=True)
     except Exception as e:
-        return {"error": "Invalid Base64 string", "details": str(e)}
+        return {"error": "Invalid Image"}
     
     # Ensure the decoded bytes are not empty
     if not image_bytes:
-        return {"error": "Decoded data is empty"}
+        return {"error": "Invalid Image"}
     
     np_arr = np.frombuffer(image_bytes, np.uint8)
     image = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
@@ -62,7 +62,6 @@ async def predict(request: ImageRequest):
         key = f"{class_name}{class_counters[class_name]}" if class_counters[class_name] > 1 else class_name
         json_result[key] = [x1, y1, x2, y2]
     
-    # Using model's summary output if available
     if hasattr(result, "summary") and isinstance(result.summary, dict):
         statistics_summary = result.summary
     else: