Update app.py

app.py

@@ -1,20 +1,32 @@
 import gradio as gr
 import os
 
-def image_mod(image):
-    return image.rotate(45)
 
 os.system("git clone https://github.com/megvii-research/NAFNet")
 os.system("mv NAFNet/* ./")
-print(os.listdir('.'))
-#os.system("pip install -r requirements.txt")
+os.system("mv NAFNet-REDS-width64.pth experiments/pretrained_models/")
+os.system("mv NAFNet-SIDD-width64.pth experiments/pretrained_models/")
 os.system("python3 setup.py develop --no_cuda_ext")
 
+
+def inference(image, task):
+    if not os.path.exists('temp'):
+      os.system('mkdir temp')
+    img.save("temp/image.png", "PNG")
+    
+    if task == 'Denoising':
+      os.system("python basicsr/demo.py -opt options/test/SIDD/NAFNet-width64.yml --input_path ./temp/image.png --output_path ./temp/image.png")
+  
+    if task == 'Deblurring':
+      os.system("python basicsr/demo.py -opt options/test/REDS/NAFNet-width64.yml --input_path ./temp/image.png --output_path ./temp/image.png")
+  
+    return f'temp/{task}/image.jpg'
+    
+
 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."
-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>"
+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>"
 
-inference = image_mod
 
 examples = [['demo/noisy.png', 'Denoising'],
             ['demo/blurry.jpg', 'Deblurring']]