Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

Human parsing model for fashion and virtual try-on applications

PyTorch and TensorFlow/Keras image models with automatic weight conversions and equal API/implementations - Vision Transformer (ViT), ResNetV2, EfficientNetV2, NeRF, SegFormer, MixTransformer, (planned...) DeepLabV3+, ConvNeXtV2, YOLO, etc.

This repository demonstrates how to use TensorFlow based SegFormer model in 🤗 transformers package.

This repository provides an overview of Segformer, architecture encoder in particular. Some details of Segformer can be misleaded, thus makes a short description here to help understand the model. Meanwhile, the code (Keras/TensorFlow) is also provided for supporting.

AgriSegment — A multi-modal plant segmentation suite for agricultural research. It offers four FastAPI-powered tools—Hybrid (SegFormer + SAM), Interactive (real-time SAM), Semantic (batch SegFormer), and Panoptic (Mask2Former)—making AI-driven plant segmentation accessible to non-programmers.

This is a warehouse for SegFormer-pytorch-model, can be used to train your image datasets for segmentation tasks.

A Keras 3 Implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"

Repository of the paper: RailSafeNet: Visual Scene Understanding for Tram Safety

Comparing CNN- and Transformer-Based Deep Learning Models for Semantic Segmentation of Remote Sensing Images. Specifically looking at different configurations of U-Net and SegFormer applied to Potsdam, Vaihingen and FloodNet dataset.

Tackling the challenges of off-road environment navigation through Attention Guided Off-Road Semantic Segmentation.

Real time Semantic Segmentation on Cityscapes dataset.

PyTorch Implementation of SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Official implementation of "Automatic Road Extraction from Historical Maps Using Transformer-Based SegFormers".

Clothes semantic segmentation with Transformers

An application for automatic road damage assessment using semantic segmentation on high-resolution images. The project helps municipal authorities and maintenance teams detect and prioritize road repairs, improving safety and reducing costs.

Automatic Damage Segmentation of Sanskrit Palm-leaf Manuscripts

Semantic Segmentation of Drone Images With Hugging Face and MLflow

This repository contains implementations of road segmentation models using deep learning techniques. The primary goal is to accurately identify drivable road areas in images captured from a vehicle's perspective.

Comparative Study of CNN and Vision Transformer architectures for high-resolution semantic segmentation.