Getting started

About Aloception

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Aloception is a set of packages for computer vision built on top of popular deep learning libraries: pytorch and pytorch lightning .

Aloscene extends the use of tensors with Augmented Tensors and Spatial Augmented Tensors. The latter are designed to facilitate the use of computer vision data (such as frames, 2d boxes, 3d boxes, optical flow, disparity, camera parameters…).
Alodataset implements ready-to-use datasets for computer vision with the help of aloscene and augmented tensors to make it easier to transform and display your vision data.
Alonet integrates several promising computer vision architectures. You can use it for research purposes or to quickly finetune or deploy your model using TensorRT. Alonet is mainly built on top of pytorch lightning with the help of aloscene and alodataset.

Note

One can use aloscene independently than the two other packages to handle computer vision data, or to improve its training pipelines with augmented tensors.

Install

Aloception’s packages are built on top of multiple libraries. Most of them are listed in the requirements.txt file:

pip install -r requirements.txt

Once the other packages are installed, you still need to install pytorch based on your hardware and environment configuration. Please, ref to the pytorch website for this install.

Other optional installation

Deformable DETR: build Multi-scale Deformable Attention ops:

cd alonet/deformable_detr/ops
./make.sh
python test.py # should yield True

Please check gcc compatibility with your CUDA Toolkit Version. For example: CUDA Toolkit 11.4.0 Or other versions of CUDA Toolkit.

Exporting to tensorRT: TensorRT toolkit need to be installed on your system. Once done, the following pip packages are required:

pip instal onnx
pip install onnx_graphsurgeon --index-url https://pypi.ngc.nvidia.com
pip install tensorrt