Update server.py

server.py

@@ -32,20 +32,23 @@ async def run_inference(images: list[UploadFile] = File(...)):
     img_paths = []
     for upload in images:
         data = await upload.read()
-
-        # Decode bytes → BGR image, dropping any alpha channel
-        bgr = mmcv.imfrombytes(data, flag="color")  
-
-        # Overwrite to disk as a 3-channel PNG (or JPEG)
+        # force 3-channel BGR
+        bgr = mmcv.imfrombytes(data, flag="color")
         tmp = f"/tmp/{upload.filename}"
         mmcv.imwrite(bgr, tmp)
-
         img_paths.append(tmp)
 
-    # Now all inputs are (3, H, W)—your model won’t hit that dim==4 assertion
-    bev_paths = infer_images(img_paths)
+    # wrap the inference in try/except
+    try:
+        bev_paths = infer_images(img_paths)
+    except Exception as e:
+        logging.exception("❌ inference failed")
+        # return the error message to the client for debugging
+        return JSONResponse(
+            status_code=500,
+            content={"error": str(e)}
+        )
 
-    # Base64-encode outputs
     output = []
     for p in bev_paths:
         with open(p, "rb") as f: