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Video Transcoding and Streaming

Transcoding is a key task in an adaptive streaming workflow for video. It converts an encoded digital file or set of files into an altered set of digital files that better meet the needs of your hardware or your audience.

Stack (OS & PL & FW)

– Windows/ Linux

– Python/ Javascript/ HTML/ CSS

– FFMPEG

Dataset Not required

Hardware (Resources) (Storage & Compute Power & Time)

– Min i7 Cpu Needed

– 32gb ram needed

Workflow (Processing)

– Fetching video assets

– Encoding videos using FFMPEG

– Packaging and fragmenting videos using FFMPEG

– Sending data on HTTP Web Server

– Output on Client Side web player

End To End (Development & Integration in a System)

– Fetching video assets

– Encoding videos using FFMPEG

– Packaging and fragmenting videos using FFMPEG

– Sending data on HTTP Web Server

– Output on Client Side web player

– Webapp deployment

– System maintenance

Deployment (Server / API)

Web App using Flask/ Django

Applications (General Real World Use)

Transcoding is used heavily in traditional film and video production. Typical needs might be to “down-res” files captured with a camera to lower resolution, lower size “proxy” files which have lossy video quality but can be quickly edited; or to transcode high quality finished video from an editing format like Apple ProRes to a delivery format like H.264. This is usually a process of “local transcoding” relying on video editing and compression software (DaVinci Resolve, Avid Media Composer, Adobe Media Encoder, etc.) which will transcode files on the user’s computer. The main downsides are possible limitations due to hardware, as we mentioned earlier, and the need to manage multiple files yourself.

Use Case (Our Specific)

We used Transcodings to deliver adaptive bitrate streams to clients. We provided following features in the app: – Different resolutions (720,480,144) – Different FPS (30,15) – Adaptive Bitrate – HLS, MP4, and Dash transcoded videos

Task

Artificial Intelligence

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