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YOLOv8 INT8 TFLite webcam inference for i.MX8MP (NPU / CPU)

Project description

yolov8-tflite-imx

YOLOv8 INT8 TFLite webcam inference for i.MX8MP (phyBOARD-Pollux).
Supports CPU and NPU acceleration via the VeriSilicon VX delegate.


Included models

Command Model task Default model path
detect Object detection (COCO) yolov8n_object_detection_full_integer_quant.tflite
pose Pose estimation yolov8n-pose_full_integer_quant.tflite
obb Oriented bounding box yolov8n-obb_full_integer_quant.tflite
segment Instance segmentation yolov8n-seg_full_integer_quant.tflite

Pose estimation

pose --cam 0                          # CPU
pose --cam 0 --npu                    # NPU

Oriented bounding box (OBB)

obb --cam 0                           # CPU
obb --cam 0 --npu                     # NPU

Instance segmentation

segment --cam 0                       # CPU
segment --cam 0 --npu                 # NPU

All flags (same for every command)

Flag Default Description
--model PATH see table above Path to .tflite model
--cam INT 0 Camera device ID
--conf FLOAT 0.25 Confidence threshold
--iou FLOAT 0.45 NMS IoU threshold
--npu off Enable NPU via /usr/lib/libvx_delegate.so
--delegate PATH None Custom delegate .so (overrides --npu)
--no-gst off Disable GStreamer, use V4L2 directly

Keys while running

Key Action
q or ESC Quit
s Save current frame as capture_<task>.jpg

Requirements

  • Python ≥ 3.8
  • tflite_runtime (installed separately for your board/arch)
  • opencv-python ≥ 4.5
  • numpy ≥ 1.21
  • NPU: /usr/lib/libvx_delegate.so present on the board

License

MIT

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