Update app.py

app.py

@@ -16,10 +16,19 @@ def callback(image_slice: np.ndarray) -> sv.Detections:
     # Run inference on the image slice
     results = model.infer(image_slice)
     
-    # Check if results is a tuple, and if so, access the first element (the detections)
+    # Check if results are in the expected format and handle accordingly
     if isinstance(results, tuple):
-        results = results[0]  # Extract the detections from the tuple
+        results = results[0]  # Extract the detections from the tuple if necessary
     
+    # If the results are a list (likely from Roboflow), access them correctly
+    if isinstance(results, list):
+        # If results are a list of predictions, we need to handle each one
+        detections = []
+        for result in results:
+            detections.extend(sv.Detections.from_inference(result))
+        return detections
+
+    # If results are a single dictionary, process them directly
     return sv.Detections.from_inference(results)
 
 # Initialize the SAHI Inference Slicer