omoindrot/tensorflow-triplet-loss
Implementation of triplet loss in TensorFlow
Implements online triplet mining with two strategies—"batch all" and "batch hard"—to efficiently select hard and semi-hard triplets during training for metric learning tasks. Includes TensorBoard integration for monitoring triplet quality metrics and demonstrates end-to-end training on MNIST with t-SNE embedding visualization, supporting both CPU and GPU via standard TensorFlow workflows.
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Python
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MIT
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Last pushed
May 09, 2019
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