#Ffmpeg h264 input hls output software
#Ffmpeg h264 input hls output code
#Ffmpeg h264 input hls output mac

Object tracking TheresholdĪn example of a playing card by reduction to the maximum contrast.

#Ffmpeg h264 input hls output code

Let's take a look at simple code to detect the card in the frame. What can we analyze? - Well, basically in general anything that can be 2d matrix. OpenCV is a main tool in Artificial intelligence when we are talking about media content. Definitely is a tool kit with lot of algorithms. Using multi core process and low level optimization gives way to a super fast library analysis. You must be thinking to yourself “That’s a high load, isn't” ? It means that the analysis should be very fast to keep your CPU running. Over 30 frames per second with top quality makes around 30 millions pixel per second. The main thing to note about OpenCV is the high performance analysis using 2d pixel matrix. OpenCV - Originally developed by Intel 's research center, as for me, it is the greatest leap within computer vision and media data analysis. See how Lemberg might help you leverage data science at your project. Rows and column represent pixel matrix which are an intermediate format in the streaming process. cv::Mat object - represents 2D pixel matrix with HSV or BGR pixel format. AVFoundation screen device ffmpeg -f avfoundation -i '1' -pix_fmt yuv420p -r 25 -t 5 /Users/UserName/Downloads/out.movīased on ffmpeg, openCV lib uses the same principles to handle the stream source: const std::string url = “ playlist.m3u8' Ĭv::namedWindow('Stream', CV_WINDOW_AUTOSIZE) Īs a result we see a window with current stream capture.Ĭv::Mat frame - current frame object. AVFoundation media device list ffmpeg -f avfoundation -list_devices true -i ''

#Ffmpeg h264 input hls output mac

No matter what source you are going to utilize with FFmpeg (screen, camera, file) - you can even set it up with a command line: Mac OS.

#Ffmpeg h264 input hls output software

FFmpeg is a free software project that produces libraries and programs for handling multimedia data. So what's cooking? How do you create a successful point and handle the first stream frame? The main tool for that is FFmpeg lib. Data Collection for Machine Learning Algorithm' and ' Motion Gesture Detection Using Tensorflow on Android'. Go Live - create shared stream endpoint with multi-connection support.Ĭheck also our other articles about machine learning ' Getting Started with Activity Tracking App.Compress output via codec to improve productivity and decrease latency. Encode to RBG/HSV pixel format to be able to analyze and edit each frame. Encode - preparing and formatting the input stream.It could be a file or another stream used as a source. Capture - on this stage we capture input stream as a raw data.There are the 3 stages that build up the Stream: Capture, Encode and Go Live. Live Stream (Broadcast) is not peer-to-peer data flow model. If your product isn't Live, add it in Todo list! Such as Youtube, Facebook, Snapchat, Instagram. LIVE mode is a common thing nowadays. Most of the social media supports live streaming. Magic should appear smooth and natural! Today we'll take a look behind the scenes. When you are performing a good 'card trick' all the details and complexity should be invisible to the observer.