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<details> <details>
<summary>1. Prepare docker enviroment </summary> <summary>1. Prepare docker enviroment </summary>
1. Follow these steps: Follow these steps:
```bash ```bash
sudo systemctl stop docker.socket sudo systemctl stop docker.socket
sudo systemctl stop docker.service sudo systemctl stop docker.service
@@ -22,8 +22,8 @@ sudo systemctl enable docker
Docker Root Dir: /home/$USER/docker_data Docker Root Dir: /home/$USER/docker_data
``` ```
</details> </details>
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]` 2. `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]`
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.` 3. `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.`
<details> <details>
<summary>3. Get your .pt model and convert it to .onnx</summary> <summary>3. Get your .pt model and convert it to .onnx</summary>