| import numpy as np | |
| from pytorch_grad_cam.base_cam import BaseCAM | |
| from pytorch_grad_cam.utils.svd_on_activations import get_2d_projection | |
| class GradCAMElementWise(BaseCAM): | |
| def __init__(self, model, target_layers, use_cuda=False, | |
| reshape_transform=None): | |
| super( | |
| GradCAMElementWise, | |
| self).__init__( | |
| model, | |
| target_layers, | |
| use_cuda, | |
| reshape_transform) | |
| def get_cam_image(self, | |
| input_tensor, | |
| target_layer, | |
| target_category, | |
| activations, | |
| grads, | |
| eigen_smooth): | |
| elementwise_activations = np.maximum(grads * activations, 0) | |
| if eigen_smooth: | |
| cam = get_2d_projection(elementwise_activations) | |
| else: | |
| cam = elementwise_activations.sum(axis=1) | |
| return cam | |