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
| map50,map50_95,mar_100,mar_10,mar_1,precision,recall,f1_score,metric_target,box_map50,box_map50_95,mean_iou,inference_time_per_image,total_detections | |
| 0.9729880690574646,0.7380290031433105,0.4360054191167993,0.045313040470425454,0.0046725469848956525,0.5000769814406364,0.9740518962075848,0.6576545512051951,masks,0.9970287680625916,0.9571905732154846,0.6846777219484743,0.07740570140790336,1030 | |