sithu31296/semantic-segmentation
SOTA Semantic Segmentation Models in PyTorch
This project helps experts in computer vision automatically identify and delineate specific objects or regions within images. You input an image, and it outputs a segmented image where different objects (like people, faces, or elements in a scene) are highlighted or outlined. It's designed for researchers and practitioners who need precise pixel-level classification in fields like scene understanding or medical imaging.
939 stars. No commits in the last 6 months.
Use this if you need to precisely segment objects or regions within images for tasks like scene parsing, human parsing, face parsing, or medical image analysis, and you require state-of-the-art models.
Not ideal if you need a simpler, off-the-shelf solution for general object detection or instance segmentation, or if you prefer frameworks other than PyTorch.
Stars
939
Forks
163
Language
Python
License
MIT
Category
Last pushed
Mar 20, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sithu31296/semantic-segmentation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
MLSTRUCT/MLStructFP
Multi-unit floor plan dataset for architectural analysis and recognition
DrSleep/light-weight-refinenet
Light-Weight RefineNet for Real-Time Semantic Segmentation
wkentaro/pytorch-fcn
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original...
luyanger1799/Amazing-Semantic-Segmentation
Amazing Semantic Segmentation on Tensorflow && Keras (include FCN, UNet, SegNet, PSPNet, PAN,...
meetps/pytorch-semseg
Semantic Segmentation Architectures Implemented in PyTorch