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Segments invasive acacia stands in top-down satellite imagery of Portugal. 🥇 1st place overall, JunctionX Lisbon 2025.
▶ Try it in your browser · Code · Dataset
| Architecture | YOLOv8n-seg (3.4M params) |
| Training | Fine-tuned 15 epochs at 640 px |
| Formats | PyTorch .pt; ONNX export (13 MB) used in the browser demo |
| Metric | Value |
|---|---|
| Box mAP@50 | 0.56 |
| Mask mAP@50 | 0.24 |
| Acacia tiles flagged | 22 / 32 |
| Negative tiles flagged | 0 / 16 |
Satellite tiles (Esri World Imagery) cut around acacia stands mapped in Portugal's COS2018 land-use map (class 5.1.1.6), plus tiles of other land as negatives. Masks are COS2018 polygons rasterised to 640×640. See the dataset card.
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
weights = hf_hub_download("duartepcruz/forest-guardian-yolov8-seg", "best.pt")
model = YOLO(weights)
results = model.predict("tile.jpg", imgsz=640, conf=0.25)
results[0].show()
This is a first pass that points foresters at places worth checking. It is tuned to stay quiet when unsure, so an empty result means "nothing obvious", not "no acacia".
conf to about 0.15 helps.Ultralytics/YOLOv8