{"id":15293027,"url":"https://github.com/nachiket273/vistrans","last_synced_at":"2026-01-05T06:49:16.878Z","repository":{"id":52831329,"uuid":"327103142","full_name":"nachiket273/VisTrans","owner":"nachiket273","description":"Implementations of transformers based models for different vision 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VisTrans\nImplementations of transformers based models for different vision tasks\n\n## Install\n1) Install from \u003ca href=\"https://pypi.org/project/vistrans/\"\u003ePyPI\u003c/a\u003e\n\n```Python\npip install vistrans\n```\n2) Install from \u003ca href=\"https://anaconda.org/nachiket273/vistrans\"\u003eAnaconda\u003c/a\u003e\n\n```Python\nconda install -c nachiket273 vistrans\n```\n\n## Version 0.003 (06/30/2021)\n------------------------------\n[![PyPI version](https://badge.fury.io/py/vistrans.svg)](https://badge.fury.io/py/vistrans)\n\nMinor fixes to fix issues with existing models.\n\n\n## Version 0.002 (04/17/2021)\n------------------------------\n[![PyPI version](https://badge.fury.io/py/vistrans.svg)](https://badge.fury.io/py/vistrans)\n\nPretrained Pytorch \u003ca href=\"https://arxiv.org/pdf/2101.11605v1.pdf\"\u003eBottleneck Transformers for Visual Recognition\u003c/a\u003e including following\n\u003cbr\u003e\n* botnet50\n* botnet101\n* botnet152\n\u003cbr\u003e\nImplementation based off \u003ca href=\"https://gist.github.com/aravindsrinivas/56359b79f0ce4449bcb04ab4b56a57a2\"\u003eOfficial Tensorflow Implementation\u003c/a\u003e\u003cbr\u003e\n\n## Usage\n---------------------\npip install vistrans\n```\n1) List Pretrained Models.\n```Python\nfrom vistrans import BotNet\nBotNet.list_pretrained()\n```\n2) Create Pretrained Models.\n```Python\nfrom vistrans import BotNet\nmodel = BotNet.create_pretrained(name, img_size, in_ch, num_classes,\n                                 n_heads, pos_enc_type)\n```\n3) Create Custom Model\n```Python\nfrom vistrans import BotNet\nmodel = BotNet.create_model(layers, img_size, in_ch, num_classes, groups,\n                            norm_layer, n_heads, pos_enc_type)\n```\n\n## Version 0.001 (03/04/2021)\n-----------------------------\n[![PyPI version](https://badge.fury.io/py/vistrans.svg)](https://badge.fury.io/py/vistrans)\n\nPretrained Pytorch \u003ca href=\"https://arxiv.org/abs/2010.11929\"\u003eVision Transformer\u003c/a\u003e Models including following\n\u003cbr\u003e\n* vit_s16_224\n* vit_b16_224\n* vit_b16_384\n* vit_b32_384\n* vit_l16_224\n* vit_l16_384\n* vit_l32_384\n\u003cbr\u003e\nImplementation based off \u003ca href=https://github.com/google-research/vision_transformer\u003eofficial jax repository\u003c/a\u003e and \u003ca href=\"https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py\"\u003etimm's implementation\u003c/a\u003e\u003cbr\u003e\n\n## Usage\n---------------------\n1) List Pretrained Models.\n```Python\nfrom vistrans import VisionTransformer\nVisionTransformer.list_pretrained()\n```\n2) Create Pretrained Models.\n```Python\nfrom vistrans import VisionTransformer\nmodel = VisionTransformer.create_pretrained(name, img_size, in_ch, num_classes)\n```\n3) Create Custom Model\n```Python\nfrom vistrans import VisionTransformer\nmodel = VisionTransformer.create_model(img_size, patch_size, in_ch, num_classes,\n                                       embed_dim, depth, num_heads, mlp_ratio,\n                                       drop_rate, attention_drop_rate, hybrid,\n                                       norm_layer, bias)\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnachiket273%2Fvistrans","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnachiket273%2Fvistrans","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnachiket273%2Fvistrans/lists"}