Self-Critical.Pytorch
Visit Toolself-critical.pytorch is an open-source PyTorch implementation for image captioning research. It supports self-critical sequence training, bottom-up feature extraction, and multi-GPU training.
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self-critical.pytorch is an open-source PyTorch implementation for image captioning research. It supports self-critical sequence training, bottom-up feature extraction, and multi-GPU training.
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About
self-critical.pytorch provides a comprehensive codebase for image captioning research, offering an unofficial PyTorch implementation for Self-critical Sequence Training. Key features include support for bottom-up features, test-time ensemble, and multi-GPU training, with DistributedDataParallel now supported via pytorch-lightning. The codebase also integrates Transformer captioning models and offers a simple demo via a Colab notebook. Researchers can train networks on datasets like COCO and Flickr30k, with options for scheduled sampling and evaluation using metrics like BLEU, METEOR, and CIDEr. Pretrained models are available, and the tool facilitates generating image captions and evaluating them on various splits.
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Free
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