omoindrot/tensorflow-triplet-loss

Health v2 · maintenance only

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1126 stars · 280 forks observed · 2026-08-28

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

A TensorFlow implementation of triplet loss with online triplet mining strategies (batch all and batch hard), for training embedding models like those used in face recognition. It includes MNIST training experiments, embedding visualization, and tests.

Use cases

• train embeddings with triplet loss in tensorflow
• implement online triplet mining
• learn metric learning with batch hard triplet loss
• visualize mnist embeddings with tsne
• reproduce facenet-style embedding training

When to choose

• you need a reference implementation of triplet loss with online mining in TensorFlow 1.x
• you are learning how batch all and batch hard triplet mining work
• you want a well-explained, tested metric learning example

When to avoid

• you use TensorFlow 2.x or PyTorch, since this targets old TensorFlow 1.x and is unmaintained
• you need production-ready, actively maintained metric learning libraries
• you need offline triplet mining or other loss functions

Facets

library · maturity abandoned

machine-learning deep-learning machine-learning deep-learning python triplet-loss tensorflow online-triplet-mining embeddings metric-learning face-recognition

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