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ffmpeg-cuda

ffmpeg-examples

Some examples base on ffmpeg apis

ffmpeg-go-server

A web server for ffmepg codeing with golang

ffmpeg-tutorial

A set of tutorials that demonstrates how to write a video player based on FFmpeg

ffmpeg4android

A FFmpeg library version 2.4 for Android API level 12, Refered to MX player open source.

ffmpeg_camera_streamer

This program can read from PC camera and stream it to live streaming server, you can also add different video filters to the live stream.本程序实现了读取PC端摄像头并进行直播的功能,同时支持添加不同的视频滤镜

ffmpeg_video_combine

本程序实现了对多路视频进行合并实现分屏效果,并且可以添加不同的视频滤镜。This program can combine multiple input videos and output one video which implementing a mutli-screen display, you can also add different filters for each input.

flv.js

HTML5 FLV Player

ftp

FTP client package for Go

gccxml

goagent

https://code.google.com/p/goagent/issues/list

gotao

iOS app to read and play the game of Go, also known as Weiqi in Chinese.

gotty

Share your terminal as a web application

gstwebrtc-demos

Demo apps for using gstreamer's webrtc implementation

h264

H.264/AVC Parser

hellogopher

Hellogopher: "just clone and make" your conventional Go project

horovod

Distributed training framework for TensorFlow.

html5-rtsp

HTML5 播放 RTSP 示例仓库

htty

Share your terminal as a web application (simple for yudai/gotty and thx :)

iboot

iBoot from iOS9

ijkplayer

Android/iOS video player based on FFmpeg n3.3, with MediaCodec, VideoToolbox support.

indexablelistview

iPhone like fast scroll ListView on Android

iris_detector

Real-time iris detector. Only need 8ms on Intel i5 CPU!

jetson-inference

Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

jetsontx1_decode

using gstreamer decode multi rtsp at nvidia_tx1

joy4

Golang audio/video library and streaming server

jrtplib

RTP Library

jspaint

🎨 Classic MS Paint, ＲＥＶＩＶＥＤ + ✨Extras

kubeadm-ha

Boot a ha kubernetes 1.11.0/1.12.1/1.13.0/1.14.0 cluster with kubeadm.

kubernetes-gpu-guide

This guide should help fellow researchers and hobbyists to easily automate and accelerate there deep leaning training with their own Kubernetes GPU cluster.