VisTrans

Implementations of transformers based models for different vision tasks

Install

1. Install from PyPI

pip install vistrans

2. Install from Anaconda

conda install -c nachiket273 vistrans

Version 0.003 (06/30/2021)

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Minor fixes to fix issues with existing models.

Version 0.002 (04/17/2021)

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Pretrained Pytorch Bottleneck Transformers for Visual Recognition including following

• botnet50
• botnet101
• botnet152

Implementation based off Official Tensorflow Implementation

Usage

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pip install vistrans

1) List Pretrained Models.
```Python
from vistrans import BotNet
BotNet.list_pretrained()

2. Create Pretrained Models.

from vistrans import BotNet
model = BotNet.create_pretrained(name, img_size, in_ch, num_classes,
                                 n_heads, pos_enc_type)

3. Create Custom Model

from vistrans import BotNet
model = BotNet.create_model(layers, img_size, in_ch, num_classes, groups,
                            norm_layer, n_heads, pos_enc_type)

Version 0.001 (03/04/2021)

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Pretrained Pytorch Vision Transformer Models including following

• vit_s16_224
• vit_b16_224
• vit_b16_384
• vit_b32_384
• vit_l16_224
• vit_l16_384
• vit_l32_384

Implementation based off official jax repository and timm's implementation

Usage

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1. List Pretrained Models.

from vistrans import VisionTransformer
VisionTransformer.list_pretrained()

2. Create Pretrained Models.

from vistrans import VisionTransformer
model = VisionTransformer.create_pretrained(name, img_size, in_ch, num_classes)

3. Create Custom Model

from vistrans import VisionTransformer
model = VisionTransformer.create_model(img_size, patch_size, in_ch, num_classes,
                                       embed_dim, depth, num_heads, mlp_ratio,
                                       drop_rate, attention_drop_rate, hybrid,
                                       norm_layer, bias)