Image Segmentation
ultralytics
TensorBoard
PyTorch
v8
ultralyticsplus
yolov8
yolo
vision
awesome-yolov8-models
Eval Results (legacy)
Instructions to use keremberke/yolov8n-pcb-defect-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use keremberke/yolov8n-pcb-defect-segmentation with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("keremberke/yolov8n-pcb-defect-segmentation", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Commit ·
c185d15
1
Parent(s): 721056a
add ultralyticsplus config
Browse files- config.json +1 -0
config.json
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{"input_size": 640, "task": "instance-segmentation", "ultralyticsplus_version": "0.0.23", "ultralytics_version": "8.0.21", "model_type": "v8", "score_map50": 0.51186, "score_map50_mask": 0.51667}
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