Generating videos focused on a single person from videos that contain multiple people. Check out generated videos on this youtube channel!
Fun fact: this resulted in two offshoot projects: an OpenShot SDK for Go and a HTTP Client Library for Go
Video → Videos following people: uses AWS Rekognition and OpenShot
License: MIT License
Generating videos focused on a single person from videos that contain multiple people. Check out generated videos on this youtube channel!
Fun fact: this resulted in two offshoot projects: an OpenShot SDK for Go and a HTTP Client Library for Go
The current implementation in tracking_converter
copies over the video file from s3 for each new project created (one project / person detected in the video). It would significantly reduce time / storage usage if we only copied over the file once and referenced it from all projects. Check out http://cloud.openshot.org/doc/api_endpoints.html#id21
It's basically a mini openshot go sdk. Might be useful for someone.
Just get tests running on each commit for now
Currently the output video width is always 1/5 the size of the input clip. This isn't ideal since different clips have different zoom levels and the output should reflect that in order to get the closest framing to the dancer possible.
Currently only cropping video's horizontally (keeping vertical height). This isn't ideal since most of the time the dancer only takes in 1/4 to 1/2 of the height of the video.
Evaluate if no state is needed / will soon be needed and if not, remove struct and convert methods to functions.
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