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)

Minor fixes to fix issues with existing models.

## Version 0.002 (04/17/2021)

Pretrained Pytorch Bottleneck Transformers for Visual Recognition including following
* botnet50 * botnet101 * botnet152
Implementation based off Official Tensorflow Implementation

## Usage

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)

Pretrained Pytorch Vision Transformer Models including following
* vits16224 * vitb16224 * vitb16384 * vitb32384 * vitl16224 * vitl16384 * vitl32384
Implementation based off official jax repository and timm's implementation

## Usage

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)