test

app.py

@@ -26,6 +26,10 @@ def image_mod(image, noise_level, denoiser):
         denoiser = dinv.models.DnCNN()
     elif denoiser == 'MedianFilter':
         denoiser = dinv.models.MedianFilter()
+    elif denoiser == 'BM3D':
+        denoiser = dinv.models.BM3D()
+    elif denoiser == 'DRUNet':
+        denoiser = dinv.models.DRUNet()
     else:
         raise ValueError("Invalid denoiser")
     noisy = image + torch.randn_like(image) * noise_level
@@ -40,7 +44,7 @@ input_image_output = gr.Image(label='Input Image')
 
 noise_levels = gr.Dropdown(choices=[0.1, 0.2, 0.3, 0.4, 0.5], value=0.1, label='Noise Level')
 
-denoiser = gr.Dropdown(choices=['DnCNN', 'MedianFilter'], value=0.1, label='DnCNN')
+denoiser = gr.Dropdown(choices=['DnCNN', 'DRUNet', 'BM3D', 'MedianFilter'], value=0.1, label='DRUNet')
 
 demo = gr.Interface(
     image_mod,

requirements.txt

@@ -1 +1,2 @@
-deepinv
+deepinv
+bm3d