37 lines
1022 B
Python
37 lines
1022 B
Python
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import numpy as np
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from pytorch_grad_cam.base_cam import BaseCAM
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from pytorch_grad_cam.utils.svd_on_activations import get_2d_projection
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# https://ieeexplore.ieee.org/document/9462463
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class LayerCAM(BaseCAM):
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def __init__(
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self,
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model,
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target_layers,
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use_cuda=False,
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reshape_transform=None):
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super(
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LayerCAM,
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self).__init__(
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model,
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target_layers,
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use_cuda,
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reshape_transform)
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def get_cam_image(self,
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input_tensor,
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target_layer,
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target_category,
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activations,
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grads,
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eigen_smooth):
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spatial_weighted_activations = np.maximum(grads, 0) * activations
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if eigen_smooth:
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cam = get_2d_projection(spatial_weighted_activations)
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else:
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cam = spatial_weighted_activations.sum(axis=1)
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return cam
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