fix and pin gradio version

README.md

@@ -5,6 +5,7 @@ colorFrom: purple
 colorTo: purple
 sdk: gradio
 app_file: app.py
+sdk_version: 3.17.1
 pinned: false
 ---
 

app.py

@@ -482,8 +482,8 @@ def main(input_path, model_path, output_dir, need_animation=False, resize_h=None
                save_all=True, append_images=all_frames[1:], optimize=False, duration=40, loop=0)
         return os.path.join(frame_dir, "animation.gif"), tensor_to_pil
     
-def gradio_inference(image):
-    return main(input_path=image.name,
+def gradio_inference(image_path):
+    return main(input_path=image_path,
          model_path='model.pth',
          output_dir='output/',
          need_animation=True,  # whether need intermediate results for animation.
@@ -496,14 +496,15 @@ description = "Gradio demo for Paint Transformer: Feed Forward Neural Painting w
 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(
     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")],
+    gr.Image(type="filepath", label="Input"), 
+    [gr.Image(type="filepath", label="Output GIF"),
+    gr.Image(type="pil", label="Output Image")],
     title=title,
     description=description,
     article=article,
+    cache_examples=True,
     examples=[
     ['city.jpg'],
     ['tower.jpg'],
     ]
-    ).launch(enable_queue=True,cache_examples=True)
+    ).launch(enable_queue=True)