semantic-segmentation
Examine state-of-the-art semantic segmentation models equipped with versatile datasets in PyTorch. The project provides practical tools, seamless integration with leading backbone architectures, and accommodates various parsing tasks such as scene, human, and medical image segmentation. Future updates aim to revamp the training pipeline, deliver baseline pre-trained models, implement distributed training, and offer tutorials for custom datasets. Compatibility with ONNX and TFLite ensures widespread adaptability, serving developers who demand precision and flexibility in segmentation applications. Anticipate significant enhancements in the scheduled May 2024 release.