MarvinTeichmann/tensorflow-fcn

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1094 stars · 421 forks observed · 2026-08-28

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

A single-file TensorFlow implementation of Fully Convolutional Networks (FCN) for semantic segmentation, using VGG16 weights loaded from a .npy file. It is designed to be integrated into custom segmentation pipelines and finetuned on user data.

Use cases

• implement fully convolutional networks in tensorflow
• semantic segmentation of images
• finetune vgg16 for pixel-wise classification
• convert vgg classification weights into an fcn
• build a segmentation pipeline for datasets like kitti or pascal voc

When to choose

• you are maintaining legacy TensorFlow 1.x code that needs an FCN
• you want a minimal, single-file FCN implementation to study or modify
• you need VGG16-based segmentation without a Caffe dependency

When to avoid

• you are starting a new project - use TensorFlow 2.x, PyTorch, or modern segmentation libraries
• you need pretrained Pascal VOC segmentation weights out of the box
• you require active maintenance, GPU modern features, or recent TensorFlow versions

Facets

library · maturity abandoned

machine-learning deep-learning image-processing computer-vision machine-learning deep-learning python tensorflow fcn semantic-segmentation vgg16 computer-vision deprecated linux gpu

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