38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
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import torch
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import numpy as np
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from typing import List, Callable
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from pytorch_grad_cam.metrics.perturbation_confidence import PerturbationConfidenceMetric
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def multiply_tensor_with_cam(input_tensor: torch.Tensor,
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cam: torch.Tensor):
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""" Multiply an input tensor (after normalization)
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with a pixel attribution map
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"""
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return input_tensor * cam
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class CamMultImageConfidenceChange(PerturbationConfidenceMetric):
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def __init__(self):
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super(CamMultImageConfidenceChange,
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self).__init__(multiply_tensor_with_cam)
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class DropInConfidence(CamMultImageConfidenceChange):
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def __init__(self):
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super(DropInConfidence, self).__init__()
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def __call__(self, *args, **kwargs):
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scores = super(DropInConfidence, self).__call__(*args, **kwargs)
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scores = -scores
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return np.maximum(scores, 0)
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class IncreaseInConfidence(CamMultImageConfidenceChange):
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def __init__(self):
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super(IncreaseInConfidence, self).__init__()
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def __call__(self, *args, **kwargs):
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scores = super(IncreaseInConfidence, self).__call__(*args, **kwargs)
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return np.float32(scores > 0)
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