Update app.py

app.py

@@ -263,16 +263,23 @@ def predict(image):
     if len(input_shape) == 4 and input_shape[0] == 1:
         image = np.expand_dims(image, axis=0)
     image = image.astype(np.float32)
+
+    print("Input image shape:", image.shape)
     
     # Make prediction
     output = model.run(None, {input_name: image})
+
+    print("Output shape:", output.shape)
     
-    print("type output:", type(output))
-    print(output)
+    # print("type output:", type(output))
+    # print(output)
 
     # Postprocess output image
     
     annotated_img = output[0]
+
+    print("Output[0] image shape:", annotated_img.shape)
+    
     # annotated_img = (output[0] / 255.0 - mean)/std
     # annotated_img = classes[output[0][0].argmax(0)]
     print("Annotated image type:", type(annotated_img))
@@ -301,8 +308,8 @@ def predict(image):
 demo = gr.Interface(
     fn=predict,
     inputs=gr.Image(sources=["webcam"], type="numpy"),  # Accepts image input
-    # outputs="image"  # Customize based on your output format
-    outputs=gr.Image(type="numpy"),  # Accepts image input
+    outputs="image"  # Customize based on your output format
+    # outputs=gr.Image(type="numpy"),  # Accepts image input
 )
 
 if __name__ == "__main__":