GeorgeSeif/Semantic-Segmentation-Suite
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
ArchivedProvides modular implementations of 15+ semantic segmentation architectures (SegNet, U-Net, DeepLabV3+, PSPNet, RefineNet, etc.) with pluggable feature extractors (ResNet, MobileNetV2, InceptionV4) built on TensorFlow's Keras API. Includes comprehensive evaluation metrics (IoU, F1, per-class accuracy), data augmentation, and dataset-agnostic training/testing pipelines for rapid experimentation across custom or standard benchmarks like CamVid.
2,526 stars. No commits in the last 6 months.
Stars
2,526
Forks
872
Language
Python
License
—
Category
Last pushed
Apr 22, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/GeorgeSeif/Semantic-Segmentation-Suite"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MLSTRUCT/MLStructFP
Multi-unit floor plan dataset for architectural analysis and recognition
yassouali/pytorch-segmentation
:art: Semantic segmentation models, datasets and losses implemented in PyTorch.
wkentaro/pytorch-fcn
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original...
meetps/pytorch-semseg
Semantic Segmentation Architectures Implemented in PyTorch
fregu856/deeplabv3
PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.