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awesome-cpp

A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

awesome_deep_learning_interpretability

深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)

car_identify

汽车识别，汽车车型识别，汽车品牌识别，车辆识别，深度学习，神经网络

chineseocr

yolo3+ocr

cvpr2020-code

CVPR 2020 论文开源项目合集

cvprojects

computer vision projects | 计算机视觉等好玩的AI项目

deep-learning

Repo for the Deep Learning Nanodegree Foundations program.

deeplearning

🎈深度学习 CS231n课程学习 花书 吴恩达的深度学习课程 Tensorflow实战 经典论文研读

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

image-matching-and-ranging-based-on-binocular-stereo-vision

双目立体视觉是计算机视觉范畴的核心之一，它利用双目相机来获得目标物体的图像，经过物体图像处理 之后得到目标物体所在场景环境的三维信息，最终实现非接触条件下测距，简单便捷。本次毕业设计主要内容为研究 基于双目立体视觉平台上的图像匹配以及目标物体的距离测量技术，图像特征提取部分研究了 SIFT 算法和 SURF 算 法，特征匹配部分研究了 BF 法和 FLANN 法，距离测量研究主要通过视差深度的计算，结合视觉坐标系的转换实现 三维位置的定位与测量。结合维视双目立体视觉测量平台 MV-VS220，通过 Python+OpenCV 设计实现一个具备图像 采集、图像匹配以及距离测量等功能的原型演示系统。系统可实现对关键环节的过程与结果的演示，以及不同算法的 性能比较。系统测试表明，所开发的原型演示系统从界面、功能与性能方面均达到了设计的要求。

learnggit

rddc2020

road damage detection challenge 2020

tensorflow-from-zero-to-one

记录自己学习TensorFlow的笔记和代码

traffic-survalance-with-computer-vision-and-deep-learning

The system takes video footage of a highway as input and provides statistics like the count of vehicles and an average estimated speed of vehicles on the highway. The statistics provided by the system can have many applications. Like, pricing the billboards on a highway for advertisement, higher the count of vehicles, higher the price. Moreover, the government can use this statistic to know how many vehicles are entering a city each day. The system internally uses YOLO object detection algorithm for vehicle detection, followed by, Centroid Tracking algorithm for tracking the detected vehicles.

vehicle-warning-indicator-system

A deep learning and computer vision based warning indicator system for the vehicle drivers using live dash-cam footage.

yolo_truck

用yolo2来识别车辆 identify vehicles with yolo2

yolov5

YOLOv5 汉化版，保持官方同步更新

yolov5-deepsort