DrSleep/tensorflow-deeplab-resnet

Health v2 · maintenance only

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1258 stars · 424 forks observed · 2026-08-28

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

A TensorFlow re-implementation of the DeepLab-ResNet model for semantic image segmentation, trained and evaluated on the PASCAL VOC dataset. It includes training, multi-scale training, and evaluation scripts with pretrained checkpoints.

Use cases

• semantic segmentation of images with tensorflow
• train deeplab resnet on pascal voc
• segment objects in images using deep learning
• fine-tune deeplab on my own dataset
• evaluate semantic segmentation model mean IoU
• pretrained segmentation model for image labeling

When to choose

• you need a DeepLab-v2 ResNet implementation in TensorFlow for PASCAL VOC-style segmentation
• you want pretrained checkpoints and training scripts to fine-tune on a custom dataset
• you are reproducing classic semantic segmentation research results

When to avoid

• you need modern TensorFlow 2.x or PyTorch - this targets legacy TF 1.x and Python 2.7
• you want actively maintained segmentation tooling with recent updates
• you need real-time or production-grade segmentation pipelines

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision computer-vision deep-learning image-processing python semantic-segmentation tensorflow resnet pascal-voc deeplab linux gpu

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