Convert Yolo Pytorch model to HEF for Raspberry Pi 5 with Hailo8L

General
,
5

Well, I managed to convert my model using this command

hailomz compile --ckpt guinea-pig-chons-v12.onnx --hw-arch hailo8l --calib-path data --yaml hef_config.yaml --classes 4 --performance

this file hef_config.yaml

- base/yolov8.yaml
postprocessing:
  device_pre_post_layers:
    nms: true
  hpp: true
network:
  network_name: yolov8n
paths:
  network_path:
  - models_files/ObjectDetection/Detection-COCO/yolo/yolov8n/2023-01-30/yolov8n.onnx
  alls_script: yolov8n.alls
  url: https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ObjectDetection/Detection-COCO/yolo/yolov8n/2023-01-30/yolov8n.zip
parser:
  nodes:
  - null
  - - /model.22/cv2.0/cv2.0.2/Conv
    - /model.22/cv3.0/cv3.0.2/Conv
    - /model.22/cv2.1/cv2.1.2/Conv
    - /model.22/cv3.1/cv3.1.2/Conv
    - /model.22/cv2.2/cv2.2.2/Conv
    - /model.22/cv3.2/cv3.2.2/Conv
info:
  task: object detection
  input_shape: 640x640x3
  output_shape: 80x5x100
  operations: 8.74G
  parameters: 3.2M
  framework: pytorch
  training_data: coco train2017
  validation_data: coco val2017
  eval_metric: mAP
  full_precision_result: 37.23
  source: https://github.com/ultralytics/ultralytics
  license_url: https://github.com/ultralytics/ultralytics/blob/main/LICENSE
  license_name: GPL-3.0

Deduced from this other topic

Well, now I have other worries about using this model, but that’s another topic.