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android_learning

android_mobilenetv2-yolov3-nano-ncnn

MobileNetV2-YOLOV3-Nano NCNN sample

atmosphericcorrection

6s模型大气校正python版本，支持GF1、2,Landsat-8,Sentinel-2等影像

chatgpt

🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

corrnet

Continuous Sign Language Recognition with Correlation Network (CVPR 2023)

depth-anything

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

drowsiness_detection

A simple Drowsiness Detection module for humans. 😴 🚫 🚗

imgaug

Image augmentation for machine learning experiments.

javacpp

The missing bridge between Java and native C++

libtorch-yolov3

A Libtorch implementation of the YOLO v3 object detection algorithm

mobilenet-yolo

MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:

my_github

nanodet

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

ncnn-android-nanodet

openvino_2022.1.0.643_to_yolov5v6.1

openvino_2022.1.0.643_to_yolov5v6.1

paddleclas

A treasure chest for visual recognition powered by PaddlePaddle

prometheus

Open source software for autonomous drones.

pytorch-opcounter

Count the MACs / FLOPs of your PyTorch model.

rgbd-slam-tutor2

The second version of RGBD SLAM tutorial. We will discuss more about pnp, tracking, multi-thread and loop closure methods. Please refer to my blog for details: www.cnblogs.com/gaoxiang12 .

surface-defect-detection

缺陷检测文献记录

tensorrt-utils

⚡ Useful scripts when using TensorRT

tensorrt-yolov4

tensorrt5, yolov4, yolov3,yolov3-tniy,yolov3-tniy-prn

tensorrt_demos

TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet

tensorrtx

Implementation of popular deep learning networks with TensorRT network definition API

tutorials

教程

yolo-fastestv2

:zap: Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

yolo-fastestv2-opencv

使用OpenCV部署Yolo-FastestV2，包含C++和Python两种版本的程序

yolov2_xilinx_fpga

A demo for accelerating YOLOv2 in xilinx's fpga pynq/zedboard

yolov34-cpp-opencv-dnn

基于opencv的4种YOLO目标检测，C++和Python两个版本的实现，仅仅只依赖opencv库就可以运行

yolov5-6.1-opencv-c-

适配于当前2022-6-20 YoloV5最新版本Release6.1的OpenVINO加速的C++代码。