Implementations of transformers based models for different vision tasks
Implementations of transformers based models for different vision tasks
1) Install from PyPI
pip install vistrans
2) Install from Anaconda
conda install -c nachiket273 vistrans
Minor fixes to fix issues with existing models.
Pretrained Pytorch Bottleneck Transformers for Visual Recognition including following
* botnet50
* botnet101
* botnet152
Implementation based off Official Tensorflow Implementation
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)
Pretrained Pytorch Vision Transformer Models including following
* vits16224
* vitb16224
* vitb16384
* vitb32384
* vitl16224
* vitl16384
* vitl32384
Implementation based off official jax repository and timm's implementation
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)