Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
Real time Semantic Segmentation on Cityscapes dataset.
Implementation of various Semantic segmentation architectures
DeepReveal is a deep learning-based image forensics system that performs pixel-level detection of AI-generated or manipulated image regions using U-Net segmentation, PyTorch, OpenCV, and Flask.
A PyTorch-based deep learning pipeline for semantic segmentation of satellite and aerial imagery. Supports 9 architectures, 40+ encoders, multi-class classification, and large image processing.
Add a description, image, and links to the semantic-segmentation-models topic page so that developers can more easily learn about it.
To associate your repository with the semantic-segmentation-models topic, visit your repo's landing page and select "manage topics."