ioekg's starred repositories
trackerslist
Updated list of public BitTorrent trackers
conv_arithmetic
A technical report on convolution arithmetic in the context of deep learning
ZLMediaKit
WebRTC/RTSP/RTMP/HTTP/HLS/HTTP-FLV/WebSocket-FLV/HTTP-TS/HTTP-fMP4/WebSocket-TS/WebSocket-fMP4/GB28181/SRT server and client framework based on C++11
Ultra-Light-Fast-Generic-Face-Detector-1MB
💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
onnx-simplifier
Simplify your onnx model
deep-learning-model-convertor
The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
Towards-Realtime-MOT
Joint Detection and Embedding for fast multi-object tracking
OpenCV-MinGW-Build
👀 MinGW 32bit and 64bit version of OpenCV compiled on Windows. Including OpenCV 3.3.1, 3.4.1, 3.4.1-x64, 3.4.5, 3.4.6, 3.4.7, 3.4.8-x64, 3.4.9, 4.0.0-alpha-x64, 4.0.0-rc-x64, 4.0.1-x64, 4.1.0, 4.1.0-x64, 4.1.1-x64, 4.5.0-with-contrib, 4.5.2-x64
dma_ip_drivers
Xilinx QDMA IP Drivers
Onekey_Caddy_PHP7_Sqlite3
小内存 VPS 一键搭建 Caddy+PHP7+Sqlite3 环境 （支持VPS最小内存64M），一键翻墙 caddy+web(php+sqlite3)+v2ray+bbr。
nano_build_opencv
Build OpenCV on Nvidia Jetson Nano
caffe-yolov3
A real-time object detection framework of Yolov3/v4 based on caffe
LFD-A-Light-and-Fast-Detector
LFD is a big update upon LFFD. Generally, LFD is a multi-class object detector characterized by lightweight, low inference latency and superior precision. It is for real-world appilcations.
onnx2caffe
pytorch to caffe by onnx
lenet5_hls
FPGA Accelerator for CNN using Vivado HLS
pytorch-aarch64
PyTorch wheels (whl) & conda for aarch64 / ARMv8 / ARM64
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
acuity-models
Acuity Model Zoo
webcam_yolov3_jetson_tx_hikvision
多个网络摄像头进行拉流以及对象检测。平台使用Jetson TX2 (ARM architecture)，海康摄像头，对象检测采用YOLO v3模型。
RtspMonitor
IP Camera RTSP stream Monitor
YOLOv3-tiny-custom-object-detection
As I continued exploring YOLO object detection, I found that for starters to train their own custom object detection project, it is ideal to use a YOLOv3-tiny architecture since the network is relative slow and suitable for small/middle size datasets
Uart_Transfer_BIN_to_exFlash
STM32串口烧录BIN文件、字库文件【QT上位机】
Tiny-ImageNet-to-TFRecords
Implementation to convert Tiny ImageNet dataset to TFRecords
STM32F4xx_USART_Example
STM32F4 的 USART 驱动