from . import base from . import functional as F from ..base.modules import Activation class IoU(base.Metric): __name__ = 'iou_score' def __init__(self, eps=1e-7, threshold=0.5, activation=None, ignore_channels=None, **kwargs): super().__init__(**kwargs) self.eps = eps self.threshold = threshold self.activation = Activation(activation) self.ignore_channels = ignore_channels def forward(self, y_pr, y_gt): y_pr = self.activation(y_pr) return F.iou( y_pr, y_gt, eps=self.eps, threshold=self.threshold, ignore_channels=self.ignore_channels, ) class Fscore(base.Metric): def __init__(self, beta=1, eps=1e-7, threshold=0.5, activation=None, ignore_channels=None, **kwargs): super().__init__(**kwargs) self.eps = eps self.beta = beta self.threshold = threshold self.activation = Activation(activation) self.ignore_channels = ignore_channels def forward(self, y_pr, y_gt): y_pr = self.activation(y_pr) return F.f_score( y_pr, y_gt, eps=self.eps, beta=self.beta, threshold=self.threshold, ignore_channels=self.ignore_channels, ) class Accuracy(base.Metric): def __init__(self, threshold=0.5, activation=None, ignore_channels=None, **kwargs): super().__init__(**kwargs) self.threshold = threshold self.activation = Activation(activation) self.ignore_channels = ignore_channels def forward(self, y_pr, y_gt): y_pr = self.activation(y_pr) return F.accuracy( y_pr, y_gt, threshold=self.threshold, ignore_channels=self.ignore_channels, ) class Recall(base.Metric): def __init__(self, eps=1e-7, threshold=0.5, activation=None, ignore_channels=None, **kwargs): super().__init__(**kwargs) self.eps = eps self.threshold = threshold self.activation = Activation(activation) self.ignore_channels = ignore_channels def forward(self, y_pr, y_gt): y_pr = self.activation(y_pr) return F.recall( y_pr, y_gt, eps=self.eps, threshold=self.threshold, ignore_channels=self.ignore_channels, ) class Precision(base.Metric): def __init__(self, eps=1e-7, threshold=0.5, activation=None, ignore_channels=None, **kwargs): super().__init__(**kwargs) self.eps = eps self.threshold = threshold self.activation = Activation(activation) self.ignore_channels = ignore_channels def forward(self, y_pr, y_gt): y_pr = self.activation(y_pr) return F.precision( y_pr, y_gt, eps=self.eps, threshold=self.threshold, ignore_channels=self.ignore_channels, )