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apollo

An open autonomous driving platform

bevdepth

Official code for BEVDepth.

bevdet

Official code base of the BEVDet series .

chatgpt_academic

科研工作专用ChatGPT/GLM拓展，特别优化学术Paper润色体验，模块化设计支持自定义快捷按钮&函数插件，支持代码块表格显示，Tex公式双显示，新增Python和C++项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持gpt-3.5/gpt-4/chatglm，兼容newbing

cpp_primer_practice

搞定C++:punch:。C++ Primer 中文版第5版学习仓库，包括笔记和课后练习答案。

cv-papers

计算机视觉相关论文整理、记录、分享; 包括图像分类、目标检测、视觉跟踪/目标跟踪、人脸识别/人脸验证、OCR/场景文本检测及识别等领域。欢迎加星,欢迎指正错误,同时也期待能够共同参与！！! 持续更新中... ...

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

daily-paper-computer-vision

记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文

deep-learning-interview-book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

deeplearningexamples

Deep Learning Examples

dlcv_for_beginners

《深度学习与计算机视觉》配套代码

labelcloud

A lightweight tool for labeling 3D bounding boxes in point clouds.

lift-splat-shoot

Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D (ECCV 2020)

numpy-100

100 numpy exercises (with solutions)

occupancym3d

opencv-python-tutorial

OpenCV问答群不再维护。有问题，自己去搜索。Google能找到大部分答案。

paddle3d

A 3D computer vision development toolkit based on PaddlePaddle. It supports point-cloud object detection, segmentation, and monocular 3D object detection models.

point_labeler

My awesome point cloud labeling tool

pointnet_pointnet2_pytorch

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

pytorch-hub

Submission to https://pytorch.org/hub/

tj4dradset

TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving

view-of-delft-dataset

This repository shares the documentation and development kit of the View of Delft automotive dataset.

votenet

Deep Hough Voting for 3D Object Detection in Point Clouds

yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

yolov5-pytorch

这是一个YoloV5-pytorch的源码，可以用于训练自己的模型。

yolov7-pytorch

这是一个yolov7的库，可以用于训练自己的数据集。