Update app.py

app.py

@@ -4,8 +4,7 @@ import os
 
 os.system("git clone https://github.com/megvii-research/NAFNet")
 os.system("mv NAFNet/* ./")
-os.system("mv NAFNet-REDS-width64.pth experiments/pretrained_models/")
-os.system("mv NAFNet-SIDD-width64.pth experiments/pretrained_models/")
+os.system("mv *.pth experiments/pretrained_models/")
 os.system("python3 setup.py develop --no_cuda_ext --user")
 
 
@@ -20,11 +19,10 @@ def inference(image, task):
     if task == 'Deblurring':
       os.system("python basicsr/demo.py -opt options/test/REDS/NAFNet-width64.yml --input_path ./tmp/image.png --output_path ./tmp/image.png")
   
-    return f'tmp/image.jpg'
-    
-
+    return 'tmp/image.png'
+   
 title = "NAFNet"
-description = "Gradio demo for <b>NAFNet: Nonlinear Activation Free Network for Image Restoration</b>. NAFNet achieves state-of-the-art performance on three tasks: image denoising, image debluring and stereo image super-resolution. See the paper and project page for detailed results below. Here, we provide a demo for image denoise and deblur. To use it, simply upload your image, or click one of the examples to load them."
+description = "Gradio demo for <b>NAFNet: Nonlinear Activation Free Network for Image Restoration</b>. NAFNet achieves state-of-the-art performance on three tasks: image denoising, image debluring and stereo image super-resolution (SR). See the paper and project page for detailed results below. Here, we provide a demo for image denoise and deblur. To use it, simply upload your image, or click one of the examples to load them."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2204.04676' target='_blank'>Simple Baselines for Image Restoration</a> | <a href='https://arxiv.org/abs/2204.08714' target='_blank'>NAFSSR: Stereo Image Super-Resolution Using NAFNet</a>  | <a href='https://github.com/megvii-research/NAFNet' target='_blank'> Github Repo</a></p>"