Displaying 1 to 7 from 7 results

chainer - A flexible framework of neural networks for deep learning

  •    Python

Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference. For more details of Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter. The stable version of current Chainer is separated in here: v3.

cupy - NumPy-like API accelerated with CUDA

  •    Python

CuPy is an implementation of NumPy-compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it. It supports a subset of numpy.ndarray interface. For detailed instructions on installing CuPy, see the installation guide.

chainercv - ChainerCV: a Library for Deep Learning in Computer Vision

  •    Python

ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. You can find the documentation here.

simple-faster-rcnn-pytorch - A simplified implemention of Faster R-CNN that replicate performance from origin paper

  •    Jupyter

VGG16 train on trainval and test on test split. Note: the training shows great randomness, you may need a bit of luck and more epoches of training to reach the highest mAP. However, it should be easy to surpass the lower bound.

pynvvl - A Python wrapper of NVIDIA Video Loader (NVVL) with CuPy for fast video loading with Python

  •    Python

PyNVVL is a thin wrapper of NVIDIA Video Loader (NVVL). This package enables you to load videos directoly to GPU memory and access them as CuPy ndarrays with zero copy. The pre-built binaries of PyNVVL include NVVL itself, so you do not need to install NVVL. Please choose a right package depending on your CUDA version.

pyinn - CuPy fused PyTorch neural networks ops

  •    Python

CuPy implementations of fused PyTorch ops. The purpose of this package is to contain CUDA ops written in Python with CuPy, which is not a PyTorch dependency.

chainer-pointnet - Chainer implementation of PointNet, PointNet++, KD-Network and 3DContextNework

  •    Python

Various point cloud based deep neural network implementation by Chainer [1]. It includes PointNet, PointNet++, Kd-Network and Kd context net (3DContextNet).