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Eduards Mendez eguar11011
jeremyjordan
/ soft_dice_loss.py
Last active
September 20, 2023 12:50
Generic calculation of the soft Dice loss used as the objective function in image segmentation tasks.
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| def soft_dice_loss(y_true, y_pred, epsilon=1e-6): | |
| ''' | |
| Soft dice loss calculation for arbitrary batch size, number of classes, and number of spatial dimensions. | |
| Assumes the `channels_last` format. | |
| # Arguments | |
| y_true: b x X x Y( x Z...) x c One hot encoding of ground truth | |
| y_pred: b x X x Y( x Z...) x c Network output, must sum to 1 over c channel (such as after softmax) | |
| epsilon: Used for numerical stability to avoid divide by zero errors | |
