Update modules

app.py

@@ -285,22 +285,22 @@ def test(img_lq, model, args, window_size):
 if __name__ == '__main__':
     
     parser = argparse.ArgumentParser()
-    parser.add_argument('--task', type=str, default='real_sr', help='classical_sr, lightweight_sr, real_sr, '
+    parser.add_argument('--task', type=str, default='compressed_sr', help='classical_sr, lightweight_sr, real_sr, '
                                                                      'gray_dn, color_dn, jpeg_car, color_jpeg_car')
     parser.add_argument('--scale', type=int, default=4, help='scale factor: 1, 2, 3, 4, 8') # 1 for dn and jpeg car
     parser.add_argument('--noise', type=int, default=15, help='noise level: 15, 25, 50')
-    parser.add_argument('--jpeg', type=int, default=40, help='scale factor: 10, 20, 30, 40')
-    parser.add_argument('--training_patch_size', type=int, default=128, help='patch size used in training Swin2SR. '
+    parser.add_argument('--jpeg', type=int, default=10, help='scale factor: 10, 20, 30, 40')
+    parser.add_argument('--training_patch_size', type=int, default=48, help='patch size used in training Swin2SR. '
                                        'Just used to differentiate two different settings in Table 2 of the paper. '
                                        'Images are NOT tested patch by patch.')
     parser.add_argument('--large_model', action='store_true', help='use large model, only provided for real image sr')
     parser.add_argument('--model_path', type=str,
-                        default='experiments/pretrained_models/Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR.pth')
+                        default='experiments/pretrained_models/Swin2SR_CompressedSR_X4_48.pth')
     parser.add_argument('--folder_lq', type=str, default="test", help='input low-quality test image folder')
     parser.add_argument('--folder_gt', type=str, default=None, help='input ground-truth test image folder')
     parser.add_argument('--tile', type=int, default=None, help='Tile size, None for no tile during testing (testing as a whole)')
     parser.add_argument('--tile_overlap', type=int, default=32, help='Overlapping of different tiles')
-    parser.add_argument('--save_img_only', default=False, action='store_true', help='save image and do not evaluate')
+    parser.add_argument('--save_img_only', default=True, action='store_true', help='save image and do not evaluate')
     args = parser.parse_args()
 
     device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
@@ -320,15 +320,24 @@ if __name__ == '__main__':
     
     #main(img)
     
-    title = "Swin2SR"
-    description = "Gradio demo for Swin2SR."
+    title = "Super-Resolution Demo Swin2SR Official 🚀🚀🔥"
+    description = ''' 
+<br>
+
+**This Demo expects low-quality and low-resolution JPEG compressed images**
+
+**We are looking for collaborators! Collaborator를 찾고 있습니다!** 🇬🇧 🇪🇸 🇰🇷 🇫🇷 🇷🇴 🇩🇪 🇨🇳
+
+**Please check our github project: https://github.com/mv-lab/swin2sr**
+</br>
+'''
     article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2209.11345' target='_blank'>Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration</a> | <a href='https://github.com/mv-lab/swin2sr' target='_blank'>Github Repo</a></p>"
 
-    examples=[['butterflyx4.png']]
+    examples= glob.glob("samples/*.jpg")
     gr.Interface(
         main, 
         gr.inputs.Image(type="pil", label="Input"),
-        "image",
+        gr.inputs.Image(type="pil", label="Ouput"),
         title=title,
         description=description,
         article=article,