divamgupta/image-segmentation-keras

Health v2 · maintenance only

Adoption not part of the score

3003 stars · 1149 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Keras library implementing popular deep learning semantic image segmentation models including SegNet, FCN, U-Net, and PSPNet. It provides both Python and CLI interfaces for training and inference, with a PyPI package (keras-segmentation).

Use cases

• train a semantic segmentation model in keras
• segment images pixel-wise with unet
• implement FCN or PSPNet without writing from scratch
• fine-tune a pretrained segmentation model on my own dataset
• run image segmentation from the command line
• classify every pixel of an image into classes

When to choose

• you want ready-made implementations of classic segmentation architectures in Keras
• you need a simple Python API or CLI to train and predict segmentation masks
• you want to fine-tune models like VGG-U-Net or ResNet-PSPNet on custom data

When to avoid

• you need PyTorch or TensorFlow 2-native modern segmentation toolkits
• you need instance segmentation or object detection rather than semantic segmentation
• you need actively developed state-of-the-art architectures like transformers-based segmentation

Facets

library · maturity maintenance

machine-learning image-processing computer-vision cli computer-vision image-processing deep-learning machine-learning python cross-platform semantic-segmentation keras unet fcn pspnet segnet deep-learning

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