furk4ngg/cv-model-pt_to_hef
1
1
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
FURK4NGG
2025-10-07 13:00:54 +03:00
committed by GitHub
parent 37bf3797f8
commit 19b2c3a2d0
1 changed files with 1 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+1 -1
View File
@@ -22,7 +22,7 @@ sudo systemctl enable docker
Docker Root Dir: /home/$USER/docker_data Docker Root Dir: /home/$USER/docker_data
``` ```
</details> </details>
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. `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]`
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.` 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>