Source code for catalyst.dl.utils.criterion.iou

import torch

from catalyst.utils import get_activation_fn

[docs]def iou( outputs: torch.Tensor, targets: torch.Tensor, eps: float = 1e-7, threshold: float = None, activation: str = "Sigmoid" ): """ Args: outputs (torch.Tensor): A list of predicted elements targets (torch.Tensor): A list of elements that are to be predicted eps (float): epsilon to avoid zero division threshold (float): threshold for outputs binarization activation (str): An torch.nn activation applied to the outputs. Must be one of ["none", "Sigmoid", "Softmax2d"] Returns: float: IoU (Jaccard) score """ activation_fn = get_activation_fn(activation) outputs = activation_fn(outputs) if threshold is not None: outputs = (outputs > threshold).float() intersection = torch.sum(targets * outputs) union = torch.sum(targets) + torch.sum(outputs) iou = intersection / (union - intersection + eps) return iou
jaccard = iou __all__ = ["iou", "jaccard"]