add video support to segment-anything-2 pipeline

[eliteprox]

This change updates the request field image to media_file and loads the appropriate segment-anything-2 inference model based on the content type of the file. It uses ffmpeg to process the video to image frames and loads them in with inference values from the request.

Some adjustments still need to be made to the request/response parameters. I think "frame index" and "object id' may be two request parameters to add to this pipeline for the video requests, I've hard coded some values for now.

[pschroedl]

I have a feeling we should return the full triple instead of creating a video segment, leaving post-processing to the consumer of the API ( though I recognize this is good quick way to validate the sanity of the mask outputs )

[eliteprox]

Thanks for the guidance on this, I see how we can just return the results of self.tm_vid.propagate_in_video(inference_state):

[eliteprox]

I have a feeling we should return the full triple instead of creating a video segment, leaving post-processing to the consumer of the API ( though I recognize this is good quick way to validate the sanity of the mask outputs )

I had some issues trying to return the correct values. I added frame index as an input parameter, normally propagate_in_video will loop returning results for each frame starting at the frame index until the end of the video, now it should only return a single frame. But the data doesn't look correct, can you take a look? @pschroedl