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title: Vessel Detection
sdk: gradio
app_file: app.py
python_version: 3.11
pinned: false
license: mit
---
# Vessel Detection
Gradio Space for detecting vessels in satellite imagery with a fine-tuned YOLOv8 model.
The main demo example is a multi-vessel satellite patch with 14 detections at the default confidence threshold.
## Links
- Live Space: https://huggingface.co/spaces/DefendIntelligence/vessel-detection
- Model repository: https://huggingface.co/DefendIntelligence/vessel-detection
- Direct model download: https://huggingface.co/DefendIntelligence/vessel-detection/resolve/main/models/best.pt
## Model
- Local file expected by the app: `models/best.pt`
- Checkpoint source: `train-20260417T124314Z-fad9d3ed_best.pt`
- Run source: `infer-b88a2887`
- Training name: `super-visible-y8s-newlabels-focuslite-e45`
- Family: YOLOv8s
- Main dataset: `sentinel-2-rgb`
- Local index mAP50: `0.7912`
The GitHub repository does not store `best.pt`. Use the bootstrap command below and it will download the model from Hugging Face.
## Run Locally
```bash
git clone https://github.com/anisayari/vessel-detection.git
cd vessel-detection
python run_local.py
```
Windows shortcut:
```powershell
.\start.ps1
```
macOS/Linux shortcut:
```bash
bash start.sh
```
The script creates a local `.venv`, installs `requirements.txt`, downloads `models/best.pt` from Hugging Face, then starts Gradio at `http://127.0.0.1:7860`.
Useful options:
```bash
python run_local.py --download-only
python run_local.py --skip-install
python run_local.py --host 0.0.0.0 --port 7860
```
## Use The App
1. Upload an RGB satellite image or select an example.
2. Adjust the confidence threshold if needed.
3. Click `Detect vessels`.
The app tiles large images before inference so small vessels remain visible to the model.
## Hugging Face Deployment
```bash
git init
git lfs install
git remote add origin https://huggingface.co/spaces/DefendIntelligence/vessel-detection
git add .
git commit -m "Add YOLOv8 satellite boat detector Space"
git push -u origin main
```
If the Space already exists, clone it and copy this folder's contents to the Space repository root.
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