This repo contains the code for converting an RGB mask into a onehot encoded mask or a single channel grayscale mask, which can be easily used for multiclass segmentation.

This repository contains the code for Multiclass Segmentation on the human faces using Landmark Guided Face Parsing (LaPa) dataset in TensorFlow.

Multiclass Segmentation using UNET on Crowd Instance-level Human Parsing (CHIP) dataset

Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.

Project on multiclass semantic segmentation of medical ultrasound images

Simulation and performance analysis of 3 benchmark models (Standard U-Net, U-Net with Resnet backbone & U-Net with DeepLabV3+ backbone) for Multiclass Semantic Segmentation of Satellite Images.

Multiclass Image Segmentation on Human Face Segmentation in TensorFlow

Liver Tumor Detection using Multiclass Semantic Segmentation with U-Net Model Architecture. CT-Scan images processed with Window Leveling and Window Blending Method, also CT-Scan Mask processed with One Hot Semantic Segmentation (OHESS)

CNN architectures for multiclass semantic segmentation of esophageal diseases

Segmentation of road scenes captured by the front cameras of vehicles (CamVid dataset)

AqUavplant Dataset: An Aquatic Plant Classification and Segmentation High-Resolution Image Dataset using Unmanned Aerial Vehicle RGB Camera. This repository is for custom data loader and benchmarking all the baselines in PyTorch.

This is a repo to organize the tool use for multiclass semantic segmentation. Anyone who wishes to create a semantic segmentation for multiple classes can use this guideline. All the annotated image are saved in grayscale format.