Update app.py

app.py

@@ -7,18 +7,18 @@ from PIL import Image
 os.system("git clone https://github.com/codeslake/RefVSR.git")
 os.chdir("RefVSR")
 os.system("./install/install_cudnn113.sh")
-
-
 os.mkdir("ckpt")
-os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_small_MFID_8K.pytorch -O ckpt/RefVSR_small_MFID_8K.pytorch")
+os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/SPyNet.pytorch -O ckpt/SPyNet.pytorch")
+
 os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_MFID_8K.pytorch -O ckpt/RefVSR_MFID_8K.pytorch")
-os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_MFID.pytorch -O ckpt/RefVSR_MFID.pytorch")
+os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_small_MFID_8K.pytorch -O ckpt/RefVSR_small_MFID_8K.pytorch")
 
-os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/SPyNet.pytorch -O ckpt/SPyNet.pytorch")
+os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_MFID.pytorch -O ckpt/RefVSR_MFID.pytorch")
+os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_small_MFID_8K.pytorch -O ckpt/RefVSR_small_MFID.pytorch")
 
 sys.path.append("RefVSR")
 
-## RefVSR
+## Input setup (creates folders and places inputs corresponding to the original RefVSR code)
 HR_LR_path = "test/RealMCVSR/test/HR/UW/0000"
 HR_Ref_path = "test/RealMCVSR/test/HR/W/0000"
 HR_Ref_path_T = "test/RealMCVSR/test/HR/T/0000"
@@ -32,13 +32,10 @@ os.makedirs(HR_LR_path)
 os.makedirs(HR_Ref_path)
 os.makedirs(HR_Ref_path_T)
 os.makedirs('result')
-
-#os.system("wget https://www.dropbox.com/s/xv6inxwy0so4ni0/LR.png -O LR.png")
-#os.system("wget https://www.dropbox.com/s/abydd1oczs1163l/Ref.png -O Ref.png")
 os.system("wget https://www.dropbox.com/s/vqekqdz80d85gi4/UW.png -O LR.png")
 os.system("wget https://www.dropbox.com/s/lsopmquhpm87v83/W.png -O Ref.png")
 
-
+## resize if necessary (not used)
 def resize(img):
     max_side = 512
     w = img.size[0]
@@ -49,40 +46,45 @@ def resize(img):
         hsize=int(h*scale_ratio)
         img = img.resize((wsize,hsize), Image.ANTIALIAS)
     return img
-  
+
+## inference  
 def inference(LR, Ref):
+    ## resize for user selected input (not used)
     #LR = resize(LR)
     #Ref = resize(Ref)
-
+    
+    ## Input setup (creates folders and places inputs corresponding to the original RefVSR code)
     LR.save(os.path.join(LR_path, '0000.png'))
     Ref.save(os.path.join(Ref_path, '0000.png'))
     Ref.save(os.path.join(Ref_path_T, '0000.png'))
     LR.save(os.path.join(HR_LR_path, '0000.png'))
     Ref.save(os.path.join(HR_Ref_path, '0000.png'))
     Ref.save(os.path.join(HR_Ref_path_T, '0000.png'))
-        
-
+    
+    ## Run RefVSR model
     os.system("python -B run.py \
-                --mode RefVSR_MFID_8K \
-                --config config_RefVSR_MFID \
+                --mode amp_RefVSR_small_MFID_8K \
+                --config config_RefVSR_small_MFID \
                 --data RealMCVSR \
-                --ckpt_abs_name ckpt/RefVSR_MFID_8K.pytorch \
+                --ckpt_abs_name ckpt/RefVSR_small_MFID_8K.pytorch \
                 --data_offset ./test \
                 --output_offset ./result \
                 --qualitative_only \
                 --cpu \
-                --is_gradio")
-                
+                --is_gradio")               
     return "result/0000.png"
 
 title="RefVSR (under construction)"
-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."
+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. The demo runs on CPUs and takes about 150s"
 
 article = "<p style='text-align: center'><b>To check the full capability of the module, we recommend to clone Github repository and run RefVSR models on videos using GPUs.</b></p><p style='text-align: center'>This demo runs on CPUs and 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 trained proposed two-stage training strategy, and the sample frames are in 430x270 resolution and saved 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>"
 
+## resize for sample (not used)
 #LR = resize(Image.open('LR.png')).save('LR.png')
 #Ref = resize(Image.open('Ref.png')).save('Ref.png')
 
+## input
 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)
+## interface
+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)