Update app.py

app.py

@@ -12,7 +12,6 @@ import torchtext
 from stat import ST_CTIME
 from datetime import datetime, timedelta
 import shutil
-torch.hub.download_url_to_file('https://i.imgur.com/tXrot31.jpg', 'gpu.jpg')
 # Images
 torch.hub.download_url_to_file('https://cdn.pixabay.com/photo/2021/08/04/14/16/tower-6521842_1280.jpg', 'tower.jpg')
 torch.hub.download_url_to_file('https://cdn.pixabay.com/photo/2017/08/31/05/36/buildings-2699520_1280.jpg', 'city.jpg')
@@ -486,25 +485,12 @@ def gradio_inference(image):
          resize_h=400,         # resize original input to this size. None means do not resize.
          resize_w=400,         # resize original input to this size. None means do not resize.
          serial=True)          # if need animation, serial must be True.
-inferences_running = 0
-def throttled_inference(image):
-    global inferences_running
-    current = inferences_running
-    if current >= 5:
-        print(f"Rejected inference when we already had {current} running")
-        return "gpu.jpg",Image.open("gpu.jpg")
-    print(f"Inference starting when we already had {current} running")
-    inferences_running += 1
-    try:
-        return gradio_inference(image)
-    finally:
-        print("Inference finished")
-        inferences_running -= 1
+
 title = "Paint Transformer"
 description = "Gradio demo for Paint Transformer: Feed Forward Neural Painting with Stroke Prediction. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2108.03798'>Paint Transformer: Feed Forward Neural Painting with Stroke Prediction</a> | <a href='https://github.com/Huage001/PaintTransformer'>Github Repo</a></p>"
 gr.Interface(
-    throttled_inference, 
+    gradio_inference, 
     gr.inputs.Image(type="file", label="Input"), 
     [gr.outputs.Image(type="file", label="Output GIF"),
     gr.outputs.Image(type="pil", label="Output Image")],
@@ -514,5 +500,6 @@ gr.Interface(
     examples=[
     ['city.jpg'],
     ['tower.jpg']
-    ]
+    ],
+    enable_queue=True
     ).launch(debug=True)