Project Title

This project implements different loss functions using PyTorch.

Table of Contents

• Introduction
• Installation
• Usage
• Loss Functions
• Examples
• Contributing
• License

Introduction

Installation

Usage

from losses import CrossEntropyLoss, DiceLoss, DiceCELoss, FocalLoss

# input is logits of (N, *)
# target is (N, C), C is class index
criterion = DiceLoss()
loss = criterion(input, target)

Loss Functions

This project implements the following loss functions:

Loss Name	Status	Link	Task
Cross-entropy loss	✅ passed	cross_entropy_loss.py	Segmentation
Binary cross-entropy loss	Row 2, Column 2	Row 2, Column 3
Mean squared error (MSE) loss	Row 3, Column 2	Row 3, Column 3
Mean absolute error (MAE) loss	Row 4, Column 2	Row 4, Column 3
Dice loss	✅ passed	dice_loss.py	Segmentation
Dice Cross Entropy loss	✅ passed	dice_loss.py	Segmentation
Focal loss	✅ passed	focal_loss.py	Segmentation
Poly Cross Entropy Loss	✅ passed	poly_loss.py	Classification
Smooth Poly Loss	✅ passed	poly_loss.py	Classification

Examples

Contributing

Contributions are welcome! If you have a suggestion for a new loss function or an improvement to an existing one, please open an issue or a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.