All Projects → CMICAI → Dink

CMICAI / Dink

Licence: bsd-3-clause
点云深度学习框架 | Point cloud Deep learning Framework

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Dink

Smallpt Parallel Bvh Gpu
A GPU implementation of smallpt (http://www.kevinbeason.com/smallpt/) with Bounding Volume Hierarchy (BVH) tree.
Stars: ✭ 36 (-35.71%)
Mutual labels:  cuda
Docs Pytorch
Deep Object Co-Segmentation
Stars: ✭ 43 (-23.21%)
Mutual labels:  cuda
Hungariangpu
An GPU/CUDA implementation of the Hungarian algorithm
Stars: ✭ 51 (-8.93%)
Mutual labels:  cuda
Style Feature Reshuffle
caffe implementation of "Arbitrary Style Transfer with Deep Feature Reshuffle"
Stars: ✭ 38 (-32.14%)
Mutual labels:  cuda
Qualia2.0
Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.
Stars: ✭ 41 (-26.79%)
Mutual labels:  cuda
Slic cuda
Superpixel SLIC for GPU (CUDA)
Stars: ✭ 45 (-19.64%)
Mutual labels:  cuda
Cure
Stars: ✭ 36 (-35.71%)
Mutual labels:  cuda
Deformable conv2d pytorch
deformable_conv2d layer implemented in pytorch
Stars: ✭ 53 (-5.36%)
Mutual labels:  cuda
Cuda Convnet2.torch
Torch7 bindings for cuda-convnet2 kernels!
Stars: ✭ 42 (-25%)
Mutual labels:  cuda
Cs344
Introduction to Parallel Programming class code
Stars: ✭ 1,051 (+1776.79%)
Mutual labels:  cuda
Nbody
N body gravity attraction problem solver
Stars: ✭ 40 (-28.57%)
Mutual labels:  cuda
Sixtyfour
How fast can we brute force a 64-bit comparison?
Stars: ✭ 41 (-26.79%)
Mutual labels:  cuda
Singularity Tutorial
Tutorial for using Singularity containers
Stars: ✭ 46 (-17.86%)
Mutual labels:  cuda
Soul Engine
Physically based renderer and simulation engine for real-time applications.
Stars: ✭ 37 (-33.93%)
Mutual labels:  cuda
Carlsim3
CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.
Stars: ✭ 52 (-7.14%)
Mutual labels:  cuda
Nvidia libs test
Tests and benchmarks for cudnn (and in the future, other nvidia libraries)
Stars: ✭ 36 (-35.71%)
Mutual labels:  cuda
Lyra
Stars: ✭ 43 (-23.21%)
Mutual labels:  cuda
3d Ken Burns
an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
Stars: ✭ 1,073 (+1816.07%)
Mutual labels:  cuda
Pamtri
PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification (ICCV 2019) - Official PyTorch Implementation
Stars: ✭ 53 (-5.36%)
Mutual labels:  cuda
Hornet
Hornet data structure for sparse dynamic graphs and matrices
Stars: ✭ 49 (-12.5%)
Mutual labels:  cuda

DINK V0.2

点云深度学习框架|Point Cloud Deep learning Framework

DINK是一个点云深度学习框架,兼并SOTA深度学习算法与传统算法,一键运行并模拟,一键训练评估深度学习模型。

DINK下载安装|DINK INSTALL

DINK三大特点:

1.兼并SOTA深度学习算法与传统算法,一键运行模拟。

2.DINK中人工智能纯Tensorflow实现。

3.全流程模块协同,CUDA加速。

DINK两步安装:

1.安装Nvidia Docker。

2.下载运行DINK镜像。


DINK is a deep learning point cloud framework. It combines SOTA in-depth learning algorithm with traditional algorithm and runs simulation with one key.

DINK 3 main features:

1.Integrating SOTA deep learning algorithm and traditional algorithm, one-click operation simulation.

2.In DINK, artificial intelligence is made of pure Tensorflow.

3.Full process module collaboration, CUDA acceleration

DINK two-step installation:

1.Install Nvidia Docker.

2.Download and run DINK mirror.


中集飞瞳|CMICAI 集装箱箱况智能管家|Container condition housekeeper

官网|Official website: http://cimcai.com/

商务邮箱|Business email: [email protected]

联系电话|phone: 400-880-5717

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].