Instructions to use melihuzunoglu/human-fall-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use melihuzunoglu/human-fall-detection with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("melihuzunoglu/human-fall-detection") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -40,7 +40,7 @@ results = model.predict(source="image1.jpg", conf=0.25, save=True)
|
|
| 40 |
|
| 41 |
The model can detect and distinguish between the following three states:
|
| 42 |
```python
|
| 43 |
-
|
| 44 |
|
| 45 |
Sitting: People sitting on chairs, benches, or floor.
|
| 46 |
|
|
|
|
| 40 |
|
| 41 |
The model can detect and distinguish between the following three states:
|
| 42 |
```python
|
| 43 |
+
Fallen: Active falling motion or a person on the ground after a fall.
|
| 44 |
|
| 45 |
Sitting: People sitting on chairs, benches, or floor.
|
| 46 |
|