Instructions to use illimax/jolgsm-distraction-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use illimax/jolgsm-distraction-detector with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("illimax/jolgsm-distraction-detector") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
JolGSM Distraction Detector (RT-DETR-L)
μ΄μ μ λΆμ£Όμ/μ‘Έμ κ°μ§λ₯Ό μν RT-DETR-L νμΈνλ λͺ¨λΈμ λλ€.
ν΄λμ€
| ID | ν΄λμ€ | μ€λͺ |
|---|---|---|
| 0 | face_normal |
μ μ μ£Όμ μΌκ΅΄ |
| 1 | face_distracted |
λΆμ£Όμ μν μΌκ΅΄ (ν΅ν μ¬ν) |
| 2 | phone |
ν΄λν° |
νμ΅ μ 보
- λ² μ΄μ€ λͺ¨λΈ: RT-DETR-L (
rtdetr-l.pt) - λ°μ΄ν°μ : AI-Hub μ‘Έμμ΄μ μλ°©μ μν μ΄μ μ μν μ 보 μμ (ν΅μ νκ²½ bbox)
- νμ΅ μ΄λ―Έμ§: 33,519μ₯ (train) / 4,335μ₯ (val)
- μ λ ₯ ν΄μλ: 640Γ640
- νμ΅ epochs: 20
μ¬μ©λ²
from ultralytics import RTDETR
model = RTDETR("jolgsm-distraction-detector.pt")
results = model.predict("image.jpg", conf=0.65)
results[0].show()
νλ‘μ νΈ
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