bubbliiiing/deeplabv3-plus-pytorch

Health v2 · maintenance only

Adoption not part of the score

1292 stars · 201 forks observed · 2026-08-28

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

A PyTorch implementation of the DeepLabv3+ semantic segmentation model with MobileNetV2 and Xception backbones. It includes scripts for training on custom VOC-format datasets, prediction, and mIoU evaluation, with downloadable pretrained weights.

Use cases

• train a semantic segmentation model on my own dataset
• segment objects in images with deeplabv3+
• evaluate mIoU of a segmentation model on VOC
• run image segmentation with pretrained xception weights
• fine-tune deeplabv3+ with mobilenet backbone
• segment objects in a video

When to choose

• you need a well-documented, easy-to-run DeepLabv3+ implementation in PyTorch
• you want to train semantic segmentation on custom VOC-format labeled data
• you want pretrained weights and simple predict/train scripts for learning or prototyping

When to avoid

• you need a production-grade segmentation pipeline or a maintained library with an API
• you need other segmentation architectures or the latest SOTA models
• you need support for newer PyTorch versions or active development

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision computer-vision image-processing deep-learning machine-learning python semantic-segmentation deeplabv3-plus pytorch model-training pretrained-weights

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