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README.md

@@ -124,26 +124,21 @@ target_layers = [model.layer4[-1]]
 input_tensor = # Create an input tensor image for your model..
 # Note: input_tensor can be a batch tensor with several images!
 
-
-# We have to specify the target we want to generate
-# the Class Activation Maps for.
+# We have to specify the target we want to generate the CAM for.
 targets = [ClassifierOutputTarget(281)]
 
 # Construct the CAM object once, and then re-use it on many images.
 with GradCAM(model=model, target_layers=target_layers) as cam:
-
   # You can also pass aug_smooth=True and eigen_smooth=True, to apply smoothing.
   grayscale_cam = cam(input_tensor=input_tensor, targets=targets)
-
   # In this example grayscale_cam has only one image in the batch:
   grayscale_cam = grayscale_cam[0, :]
   visualization = show_cam_on_image(rgb_img, grayscale_cam, use_rgb=True)
-
   # You can also get the model outputs without having to redo inference
   model_outputs = cam.outputs
 ```
 
-cam.py has a more detailed usage example.
+[cam.py](https://github.com/jacobgil/pytorch-grad-cam/blob/master/cam.py) has a more detailed usage example.
 
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