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mmedit.evaluation.metrics.matting_mse

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MattingMSE

Mean Squared Error metric for image matting.

class mmedit.evaluation.metrics.matting_mse.MattingMSE(norm_const=1000, **kwargs)[源代码]

Bases: mmengine.evaluator.BaseMetric

Mean Squared Error metric for image matting.

This metric compute per-pixel squared error average across all pixels. i.e. mean((a-b)^2) / norm_const

备注

Current implementation assume image / alpha / trimap array in numpy format and with pixel value ranging from 0 to 255.

备注

pred_alpha should be masked by trimap before passing into this metric

Default prefix: ‘’

参数

norm_const (int) – Divide the result to reduce its magnitude. Default to 1000.

Metrics:
  • MattingMSE (float): Mean of Squared Error

default_prefix = ''[源代码]
process(data_batch: Sequence[dict], data_samples: Sequence[dict]) None[源代码]

Process one batch of data and predictions.

参数
  • data_batch (Sequence[dict]) – A batch of data from the dataloader.

  • data_samples (Sequence[dict]) – A batch of outputs from the model.

compute_metrics(results: List)[源代码]

Compute the metrics from processed results.

参数

results (dict) – The processed results of each batch.

返回

The computed metrics. The keys are the names of the metrics, and the values are corresponding results.

返回类型

Dict

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