Quickvision is here !
A simple Computer Vision Library for PyTorch and Lightning !
Brief summary
- Quickvision provides easy training API to Computer Vision Models.
- It is completely based on PyTorch and supports PyTorch Lightning too.
- Quickvision assembles building blocks from torchvision and is highly inspired from torchvison.
- It does not abstract any PyTorch code, the only data format used is `Tensor` and has no custom classes implemented on top.
- Quickvision is a library and not a framework, so it has super low dependencies.
- It also provides a simple PyTorch interface, we tend to avoid writing abstract classes on top of `nn.Module`.
- We keep the library minimal, only to PyTorch, torchvision and optionally PyTorch Lightning.
How does Quickvision help in CV Tasks ?
- The most painful procedure is creating models, supporting different architectures and long training loops.
It takes lot of time to write tested, stable and efficient training pipelines.
- Quickvision has already implemented these for you ! You can simple
1. Create your own model or from Quickvision.
2. Train it using Quickvision engines.
3. Have your trained model back !
We expect our engines to be stable and mature over releases and testing, which would mean you would not have to worry about model creating and loading. We also calculate metrics on fly in PyTorch for models, these are written in PyTorch and do not use any other APIs.
- Quickvision give you full flexibility of PyTorch, you may use customize your training loops combining `train_step` and `val_step` methods of our models. Feel free to experiment and leave the long training loops to us :smiley: