pytorch-semseg and pytorch-semantic-segmentation
These are competitors—both implement various semantic segmentation architectures (FCN, SegNet, U-Net, etc.) in PyTorch as standalone frameworks, so users would typically choose one based on their preferred architecture implementations and API design rather than using both together.
About pytorch-semseg
meetps/pytorch-semseg
Semantic Segmentation Architectures Implemented in PyTorch
Implements 8+ segmentation architectures (PSPNet, FCN, U-Net, SegNet, LinkNet, ICNet, FRRN) with pretrained weights and integrated support for 7 major datasets (Pascal VOC, Cityscapes, ADE20K, CamVid, NYUDv2, etc.). Provides YAML-based configuration for training with modular components including multiple optimizers, learning rate schedules, data augmentation pipelines, and loss functions. Includes utilities for validation with flip augmentation, inference on custom images with optional DenseCRF post-processing, and real-time FPS measurement.
About pytorch-semantic-segmentation
zijundeng/pytorch-semantic-segmentation
PyTorch for Semantic Segmentation
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