Update app.py

app.py

@@ -25,11 +25,19 @@ os.makedirs(Ref_path)
 os.makedirs(Ref_path_T)
 os.makedirs('result')
 
-def resize(width,img):
-    basewidth = width
-    wpercent = (basewidth/float(img.size[0]))
-    hsize = int((float(img.size[1])*float(wpercent)))
-    img = img.resize((basewidth,hsize), Image.ANTIALIAS)
+def resize(max_side,img):
+    #basewidth = max_side
+    #wpercent = (basewidth/float(img.size[0]))
+    #hsize = int((float(img.size[1])*float(wpercent)))
+    #img = img.resize((basewidth,hsize), Image.ANTIALIAS)
+    h = img.size[0]
+    w = img.size[1]
+    if max(h, w) > max_side:
+        scale_ratio = max_side / max(h, w)
+        wsize=int(w*scale_ratio)
+        hsize=int(h*scale_ratio)
+    img = img.resize((wsize,hsize), Image.ANTIALIAS)
+
     return img
   
 def inference(LR, Ref):
@@ -58,10 +66,10 @@ title="RefVSR"
 #description="Demo application for Reference-based Video Super-Resolution (RefVSR).\nInstruction: Upload a low-resolution frame and a reference frame to 'LR' and 'Ref' input windows, respectively.\nNote 1: 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. \nNote 2: The model is our small 8K model trained with the proposed two-stage training strategy. \nNote 3: The spatial size of input LR and Ref frames is 1920x1080 (HD), in the PNG format."
 description="Demo application for Reference-based Video Super-Resolution (RefVSR). Upload a low-resolution frame and a reference frame to 'LR' and 'Ref' input windows, respectively."
 
-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>"
+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 will not take advantage of temporal LR and Ref 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 = resize(256, Image.open('LR.png'))
+Ref = resize(256, Image.open('Ref.png'))
 LR.save('LR.png')
 Ref.save('Ref.png')