Update app.py

app.py

@@ -33,8 +33,8 @@ def resize(width,img):
     return img
   
 def inference(LR, Ref):
-    LR = resize(256, LR)
-    Ref = resize(256, Ref)
+    LR = resize(256, 'LR.png')
+    Ref = resize(256, 'Ref.png')
 
     LR.save(os.path.join(LR_path, '0000.png'))
     Ref.save(os.path.join(Ref_path, '0000.png'))
@@ -60,6 +60,11 @@ description="Demo application for Reference-based Video Super-Resolution (RefVSR
 
 article = "<p style='text-align: center'>This demo only supports RefVSR for a single LR and Ref frame due to computational complexity. Hence, the model might not take advantage of temporal frames.</p><p style='text-align: center'>The model is our small 8K model trained with the proposed two-stage training strategy.</p><p style='text-align: center'>The spatial size of input LR and Ref frames is 1920x1080 (HD), in the PNG format.</p><p style='text-align: center'><a href='https://junyonglee.me/projects/RefVSR' target='_blank'>Project</a> | <a href='https://arxiv.org/abs/2203.14537' target='_blank'>arXiv</a> | <a href='https://github.com/codeslake/RefVSR' target='_blank'>Github</a></p>"
 
+LR = resize(256, 'LR.png')
+Ref = resize(256, 'Ref.png')
+LR.save('LR.png')
+Ref.save('Ref.png')
+
 examples=[[['LR.png'], ['Ref.png']]]
 
 gr.Interface(inference,[gr.inputs.Image(type="pil"), gr.inputs.Image(type="pil")],gr.outputs.Image(type="file"),title=title,description=description,article=article,theme ="peach",examples=examples).launch(enable_queue=True)