I have some example model that returns rotated bounding boxes in a special way, e.g. in the retinanet-format like [x,y,w,h,theta]. I’d like to integrate that into my existing deepstream pipeline that
- A) decodes a video
- B) inferences on the frame
- C) draws the rotated bbox using opencv or does some other operation on the frame based on the rotated bbox
- D) encodes the frames to a video
- E) saves the video.
According to this forum post: (Rotated Boundingboxes) Infer live video on the jetson Platform with onnx model from the ODTK rotated bounding boxes “are not supported” by deepstream. Does that mean I will reach technical limitations that cannot be overcome? In my mind, I could write a custom plugin that accepts rotated bboxes and draws the box to the frame using opencv, right? Further, if that is not possible: Could I write a custom postprocessing plugin that calculates a minimum unrotated bbox over the rotated bbox and just draw that, so I can continue using my existing model?
Thank you in advance