FURK4NGG
31 lines
1.2 KiB
Markdown
31 lines
1.2 KiB
Markdown
## 👀 cv-model-pt_to_hef Overview
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<h1 align="center">Convert Computer Vision model .pt to .hef for Rasberry Pi 5 Hailo AI HAT</h1>
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## 🔎 Preparation
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1. `Go to the`[`HAILO AI DEVELOPER ZONE`](https://hailo.ai/developer-zone/software-downloads/)`adress and download .zip file with this configration: Software Package[AI Software Suite], Software Sub-Package[AI Software Suite], Architecture[x86], OS[Linux], Python Version[3.8]`
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2. `In model training, place 60%–80% of the photos you use into the train/images folder. The photos should be raw, unlabelled images — there should be no labeling process applied to them. You don’t need labels or a classes.txt file; only the images folder is required.`
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<details>
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<summary>3. Get your .pt model and convert it to .onnx</summary>
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1. Run this .py code at the same directory with your .pt model:
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```bash
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!pip install ultralytics
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from ultralytics import YOLO
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model = YOLO("model.pt")
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model.export(format="onnx")
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```
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</details>
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/home/$USER/docker_hailo/hailo8_ai_sw_suite_2025-10_docker.zip
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/home/$USER/docker_hailo/train/images/(60%–80% of your photos)
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/home/$USER/docker_hailo/shared_with_docker/models/model.onnx
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/home/bob/Docker_hailo/shared_with_docker/doc/
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## 📦 Setup
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1. ``
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## 🎉 Run
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``
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