@ByiProX thanks for the PR!

The intended use-case for LoadStreams() is to connect to multiple cameras for batched inference, i.e. you have 8 RTSP cameras, you pass their addresses in a streams.txt file (one per line), and then detect.py will load them all asynchronously and run batched inference on them:

python detect.py --source streams.txt

This results in an incredibly fast multi-camera inference system, but a few issues are:

• Some cameras may suffer connectivity issues, so one image in the batch will be static, or fail to load, while the other cameras operate correctly.
• Queue buildup if the system is not realtime capable. The cv2 loader will load the previous frame of the RTSP stream, not the current frame. So for example if your connection is slow and you can only download 1 image per second, the inference stream will never be realtime, it will always be running inference on past frames.

Ideally we'd want a streamloader that checks for and pulls the current frame at a proposed framerate, does not build up a queue, and skips inference if the entire batch is identical as you propose here.

@ByiProX see also #2222 for a recent PR to patch a frame loss bug on multi-RTSP streaming.

/rebase

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