Update app.py

app.py

@@ -70,25 +70,25 @@ def classify_image(inp):
 
     prediction = model(img_t.unsqueeze(0)).softmax(-1).flatten()
 
-    modulator = model.layers[0].blocks[2].modulation.modulator.norm(2, 1, keepdim=True)
+    modulator = model.layers[0].blocks[11].modulation.modulator.norm(2, 1, keepdim=True)
     modulator = nn.Upsample(size=img_t.shape[1:], mode='bilinear')(modulator)
     modulator = modulator.squeeze(1).detach().permute(1, 2, 0).numpy()
     modulator = (modulator - modulator.min()) / (modulator.max() - modulator.min())
     cam0 = show_cam_on_image(img_d, modulator, use_rgb=True)
 
-    modulator = model.layers[0].blocks[5].modulation.modulator.norm(2, 1, keepdim=True)
+    modulator = model.layers[0].blocks[8].modulation.modulator.norm(2, 1, keepdim=True)
     modulator = nn.Upsample(size=img_t.shape[1:], mode='bilinear')(modulator)
     modulator = modulator.squeeze(1).detach().permute(1, 2, 0).numpy()
     modulator = (modulator - modulator.min()) / (modulator.max() - modulator.min())
     cam1 = show_cam_on_image(img_d, modulator, use_rgb=True)
 
-    modulator = model.layers[0].blocks[8].modulation.modulator.norm(2, 1, keepdim=True)
+    modulator = model.layers[0].blocks[5].modulation.modulator.norm(2, 1, keepdim=True)
     modulator = nn.Upsample(size=img_t.shape[1:], mode='bilinear')(modulator)
     modulator = modulator.squeeze(1).detach().permute(1, 2, 0).numpy()
     modulator = (modulator - modulator.min()) / (modulator.max() - modulator.min())
     cam2 = show_cam_on_image(img_d, modulator, use_rgb=True)
 
-    modulator = model.layers[0].blocks[11].modulation.modulator.norm(2, 1, keepdim=True)
+    modulator = model.layers[0].blocks[2].modulation.modulator.norm(2, 1, keepdim=True)
     modulator = nn.Upsample(size=img_t.shape[1:], mode='bilinear')(modulator)
     modulator = modulator.squeeze(1).detach().permute(1, 2, 0).numpy()
     modulator = (modulator - modulator.min()) / (modulator.max() - modulator.min())
@@ -107,16 +107,16 @@ gr.Interface(
     outputs=[
         gr.outputs.Image(
         type="pil",
-        label="Modulator at layer 3"),     
+        label="Modulator at layer 12"),     
         gr.outputs.Image(
         type="pil",
-        label="Modulator at layer 6"),     
+        label="Modulator at layer 9"),     
         gr.outputs.Image(
         type="pil",
-        label="Modulator at layer 9"),     
+        label="Modulator at layer 6"),     
         gr.outputs.Image(
         type="pil",
-        label="Modulator at layer 12"),                        
+        label="Modulator at layer 3"),                        
         label,
     ],
     examples=[["./donut.png"], ["./horses.png"], ["./pencil.png"]],