from pytorch_grad_cam.base_cam import BaseCAM | |
from pytorch_grad_cam.utils.svd_on_activations import get_2d_projection | |
# Like Eigen CAM: https://arxiv.org/abs/2008.00299 | |
# But multiply the activations x gradients | |
class EigenGradCAM(BaseCAM): | |
def __init__(self, model, target_layers, use_cuda=False, | |
reshape_transform=None): | |
super(EigenGradCAM, self).__init__(model, target_layers, use_cuda, | |
reshape_transform) | |
def get_cam_image(self, | |
input_tensor, | |
target_layer, | |
target_category, | |
activations, | |
grads, | |
eigen_smooth): | |
return get_2d_projection(grads * activations) | |