/cv_models

Implement common deep networks for computer vision with pytorch from scratch.

Primary LanguagePythonMIT LicenseMIT

cv_models

Implement common deep networks for computer vision with pytorch from scratch.

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Dependencies

Packages

  • Pytorch 1.12.0

Environment

  • Python 3.10

Backbones

Common Backbones

Model Status Paper
ConvNext A ConvNet for the 2020s
MLP-Mixer MLP-Mixer: An all-MLP Architecture for Vision
ResNet
ResNeXt
BoTNet Bottleneck Transformers for Visual Recognition
Swin Transformer 🔄️
Vision Transformer An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Xception Xception: Deep Learning with Depthwise Separable Convolutions

Lightweight/Mobile Backbones

Model Status Paper
MobileNet
MobileViT 🔄️
ShuffleNet

Segmentation

Model Status Paper
UNet 🔄️
DeepLab V3+ 🔄️

Detection

No detailed plan yet.

3D

No detailed plan yet.

Plugin-in Modules

No detailed plan yet.

License

Copyright (c) 2022 SmartPolarBear

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.