Computer Vision models and training
Project description
Quickvision
- Faster Computer Vision.
Install Quickvision
-
Install from PyPi.
-
Current stable
release 0.1
needsPyTorch 1.7
andtorchvision 0.8.1
.pip install quickvision
What is Quickvision?
-
Quickvision makes Computer Vision tasks much faster and easier with PyTorch.
It provides: -
- Easy to use PyTorch native API, for
fit()
,train_step()
,val_step()
of models. - Easily customizable and configurable models with various backbones.
- A complete PyTorch native interface. All models are
nn.Module
, all the training APIs are optional and not binded to models. - A lightning API which helps to accelerate training over multiple GPUs, TPUs.
- A datasets API to convert common data formats very easily and quickly to PyTorch formats.
- A minimal package, with very low dependencies.
- Easy to use PyTorch native API, for
-
Train your models faster. Quickvision has already implemented the long learning in PyTorch.
Quickvision is just PyTorch!!
- Quickvision does not make you learn a new library. If you know PyTorch, you are good to go!!!
- Quickvision does not abstract any code from PyTorch, nor implements any custom classes over it.
- It keeps the data format in
Tensor
so that you don't need to convert it.
Do you want just a model with some backbone configuration?
- Use model made by us. It's just a
nn.Module
which has Tensors only Input and Output format. - Quickvision provides reference scripts too for training it!
Do you want to train your model but not write lengthy loops?
- Just use our training methods such as
fit()
,train_step()
,val_step()
.
Do you want multi GPU training but worried about model configuration?
- Just subclass the PyTorch Lightning model!
- Implement the
train_step()
,val_step()
.
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