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Computer Vision models and training

Project description

Quickvision

  • Faster Computer Vision.

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Install Quickvision

  • Install from PyPi.

  • Current stable release 0.1.1 needs PyTorch 1.7.1 and torchvision 0.8.2.

    pip install quickvision
    

What is Quickvision?

  • Quickvision makes Computer Vision tasks much faster and easier with PyTorch.

    It provides: -

    1. Easy to use PyTorch native API, for fit(), train_step(), val_step() of models.
    2. Easily customizable and configurable models with various backbones.
    3. A complete PyTorch native interface. All models are nn.Module, all the training APIs are optional and not binded to models.
    4. A lightning API which helps to accelerate training over multiple GPUs, TPUs.
    5. A datasets API to convert common data formats very easily and quickly to PyTorch formats.
    6. A minimal package, with very low dependencies.
  • 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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