Metrics
Classification & Segmentation
Accuracy
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common.utils.metric.
accuracy
(output, target, topk=(1, ))[source] Computes the accuracy over the k top predictions for the specified values of k
- Parameters
output (tensor) – Classification outputs, (N,C) where C = number of classes
target (tensor) – (N) where each value is 0≤targets[i]≤C−1
topk (sequence[int]) – A list of top-N number.
- Returns
Top-N accuracies (N ∈ topK).
ConfusionMatrix
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class
common.utils.metric.
ConfusionMatrix
(num_classes)[source] -
compute
()[source] compute global accuracy, per-class accuracy and per-class IoU
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format
(classes)[source] Get the accuracy and IoU for each class in the table format
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update
(target, output)[source] Update confusion matrix.
- Parameters
target – ground truth
output – predictions of models
- Shape:
target: (minibatch,C) where C means the number of classes.
output: (minibatch,C) where C means the number of classes.
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