debug

app.py

@@ -29,12 +29,14 @@ imagenet_classes = load_text_lines(IMAGENET_CLASSES_FILE)
 
 
 def classify_image(input_image) -> str:
+    print(type(input_image))
     inputs = processor(
         text=imagenet_classes,
         images=input_image,
         return_tensors="pt",
         padding=True)
     outputs = model(**inputs)
+    print(outputs)
     probs = outputs.logits_per_image.softmax(dim=1)
     class_index = np.argmax(probs.detach().numpy())
     return imagenet_classes[class_index]
@@ -58,4 +60,4 @@ with gr.Blocks() as demo:
         run_on_click=True
     )
 
-demo.queue(max_size=64).launch(debug=False)
+demo.launch(debug=False)