NanoDet on RKNN2

Python Version

• Based on rknn-toolkit2 and rknn-toolkit-lite2
• use OpenCV for image capture & process
  • Capture image // TODO: Set attributes of capture stream
  • Resize it to (320, 320) and convert to RGB
  • Feed converted image to RKNN, get result of inference
  • Parse result, draw box as overlay of origin image // TODO
  • Async / Multithread support maybe? //TODO

CPP Version // TODO

• Based on rknn-rt2
• Use V4L2 / GStreamer / librga / mpp...?
  • Maybe capture YUYV, then convert YUYV to NV12?
• Other, TBD...