Update app_v1.py

app_v1.py

@@ -39,9 +39,9 @@ def resize_image_pil(image, new_width, new_height):
 
     return resized
 
-def inference(input_img, is_grad_cam=True, transparency = 0.5, target_layer_number = -1, top_predictions=3):
+def inference(input_img, is_grad_cam=True, transparency = 0.5,layer='layer2', target_layer_number = -1, top_predictions=3):
     input_img = resize_image_pil(input_img, 32, 32)
-    
+
     input_img = np.array(input_img)
     org_img = input_img
     input_img = input_img.reshape((32, 32, 3))
@@ -55,11 +55,33 @@ def inference(input_img, is_grad_cam=True, transparency = 0.5, target_layer_numb
     confidences = {classes[i]: float(o[i]) for i in range(10)}
     _, prediction = torch.max(outputs, 1)
     if is_grad_cam:
-        target_layers = [model.layer2[target_layer_number]]
-        cam = GradCAM(model=model, target_layers=target_layers)
-        grayscale_cam = cam(input_tensor=input_img, targets=None)
-        grayscale_cam = grayscale_cam[0, :]
-        visualization = show_cam_on_image(org_img/255, grayscale_cam, use_rgb=True, image_weight=transparency)
+        if layer == 'layer1':
+          target_layers = [model.layer1[target_layer_number]]
+          cam = GradCAM(model=model, target_layers=target_layers)
+          grayscale_cam = cam(input_tensor=input_img, targets=None)
+          grayscale_cam = grayscale_cam[0, :]
+          visualization = show_cam_on_image(org_img/255, grayscale_cam, use_rgb=True, image_weight=transparency)
+        
+        if layer == 'layer2':
+          target_layers = [model.layer2[target_layer_number]]
+          cam = GradCAM(model=model, target_layers=target_layers)
+          grayscale_cam = cam(input_tensor=input_img, targets=None)
+          grayscale_cam = grayscale_cam[0, :]
+          visualization = show_cam_on_image(org_img/255, grayscale_cam, use_rgb=True, image_weight=transparency)
+
+        if layer == 'layer3':
+          target_layers = [model.layer3[target_layer_number]]
+          cam = GradCAM(model=model, target_layers=target_layers)
+          grayscale_cam = cam(input_tensor=input_img, targets=None)
+          grayscale_cam = grayscale_cam[0, :]
+          visualization = show_cam_on_image(org_img/255, grayscale_cam, use_rgb=True, image_weight=transparency)
+
+        if layer == 'layer4':
+          target_layers = [model.layer4[target_layer_number]]
+          cam = GradCAM(model=model, target_layers=target_layers)
+          grayscale_cam = cam(input_tensor=input_img, targets=None)
+          grayscale_cam = grayscale_cam[0, :]
+          visualization = show_cam_on_image(org_img/255, grayscale_cam, use_rgb=True, image_weight=transparency)
     else:
         visualization = None
 
@@ -91,6 +113,7 @@ demo = gr.Interface(
         gr.Image(width=256, height=256, label="Input Image"),
         gr.Checkbox(label="Show GradCAM"),
         gr.Slider(0, 1, value = 0.5, label="Overall Opacity of Image"), 
+        gr.Dropdown(["layer1", "layer2", "layer3", "layer4"], label="Layer"),
         gr.Slider(-2, -1, value = -2, step=1, label="Which Layer?"),
         gr.Slider(2, 10, value=3, step=1, label="Number of Top Classes")
         ],