I was looking through the example pipeline for instance segmentation (specifically with yolov5 segmentation) and wondering how I can use the pipeline without GStreamer and instead my own pre processing method. To my understanding it looks like these pipelines are interwoven with pre processing and post processing steps using GStreamer. The end goal is to pre-process a single image without GStreamer and output data from the model (no post processing). How can I reduce the pipeline to still do inference without GStreamer? Thanks!
For alternatives to GStreamer, check out our examples repository:
The repository includes both Python and C++ implementation examples for instance segmentation that should help you get started. Feel free to explore them and let me know if you need any assistance!
Thanks! Was trying to work on this example and it says I need to import the model_zoo. The issue with this is I am attempting to run this off of the pi-5, and the model zoo requires much more powerful hardware when looking at the documentation, as well as on the software downloads page. Is there a way around this, and do I need to download the entire model zoo library to run the instance segmentation example?