anyboxes 0.1.1

Lightweight package for managing bounding boxes that works seamlessly with most computing frameworks.

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This package provides a simple API for managing bounding boxes. It allows you to perform transformation to your Numpy's ndarray, JAX's Array, PyTorch Tensor or Tensorflow Tensor from one orientation to another.

️️⚙️ Installation

Install the package from the PyPI registry. You may need to specify the framework that you want to managed. Numpy is enabled by default.

pip install anyboxes
# or
pip install "anyboxes[torch]" # or jax, tensorflow

Install the package from the latest commit of the repository.

pip install git+https://github.com/VDuchauffour/anyboxes

⚡ Usage

Example

from anyboxes import TorchBoxes
import torch

detections = torch.randint(0, 1000, (10, 4))

boxes = TorchBoxes.from_bottom_left_corner(detections)
boxes = boxes.to_center()
boxes.as_tensor

In a nutshell, using a Boxes involve 3 stages:

To be more specific, when a Boxes is instantiated, the following attribute are created:

⛏️ Development

Clone the project

git clone https://github.com/VDuchauffour/anyboxes

In order to install all development dependencies, run the following command:

pip install -e ".[all,dev]"

To ensure that you follow the development workflow, please setup the pre-commit hooks:

pre-commit install

🧭 Roadmap

• Implementations
  • PyTorch
  • Numpy
  • JAX
  • Tensorflow
• Dispatch implementation using a metaclass