Image Classification
Transformers
PyTorch
English
drowsiness_detector
computer-vision
drowsiness-detection
driver-safety
cnn
tensorflow
Instructions to use ckcl/driver-drowsiness-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckcl/driver-drowsiness-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ckcl/driver-drowsiness-detector") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ckcl/driver-drowsiness-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tensorflow==2.15.0 | |
| opencv-python==4.8.1.78 | |
| numpy==1.24.3 | |
| scikit-learn==1.3.2 | |
| gradio==4.14.0 | |
| Pillow==10.0.0 | |
| ffmpeg-python==0.2.0 | |
| huggingface-hub>=0.21.0 | |
| transformers==4.35.2 | |
| torch>=2.0.0 | |
| torchvision>=0.15.0 | |
| tqdm==4.66.1 | |
| scipy>=1.10.0 | |
| mediapipe==0.10.9 | |
| safetensors>=0.4.0 |