Image Segmentation
ultralytics
TensorBoard
yolo
yolo26
instance-segmentation
drone
uav
robotics
sae-eletroquad
Eval Results (legacy)
Instructions to use blackbeedrones/sae-2026-hang-all-yolo26n-seg-v2-960 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use blackbeedrones/sae-2026-hang-all-yolo26n-seg-v2-960 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("blackbeedrones/sae-2026-hang-all-yolo26n-seg-v2-960") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 442 Bytes
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{
"class_id": 0,
"class_name": "rose",
"ap50": 0.5668243765830994,
"ap50_95": 0.5668243765830994,
"precision": 0.44575163398692813,
"recall": 0.963276836158192,
"f1_score": 0.6094727435210009
},
{
"class_id": 1,
"class_name": "sphere",
"ap50": 0.9092336297035217,
"ap50_95": 0.9092336297035217,
"precision": 0.630901287553648,
"recall": 1.0,
"f1_score": 0.7736842105263158
}
] |