Unofficial implementations of transfomers models for vision.
Project description
VisTrans
Implementations of transformers based models for different vision tasks
Install
- Install from PyPI
pip install vistrans
- 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()
- Create Pretrained Models.
from vistrans import BotNet
model = BotNet.create_pretrained(name, img_size, in_ch, num_classes,
n_heads, pos_enc_type)
- 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
- 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
- List Pretrained Models.
from vistrans import VisionTransformer
VisionTransformer.list_pretrained()
- Create Pretrained Models.
from vistrans import VisionTransformer
model = VisionTransformer.create_pretrained(name, img_size, in_ch, num_classes)
- 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)
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