Instructions to use Gauravgupta8566/horror-object-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Gauravgupta8566/horror-object-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("Gauravgupta8566/horror-object-detector") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Horror Object Detector
Custom YOLO11n object detection model for the AI Horror Game.
Classes
The model detects 8 object classes:
- chair
- bottle
- table
- book
- box
- lamp
- door
- window
Training
This model was fine-tuned from pretrained YOLO11n weights using a custom Open Images based dataset.
Input
An image containing game-environment objects.
Output
The model detects objects and their bounding boxes. The game API converts the detections into object counts.
Example:
{
"objects": {
"chair": 4,
"bottle": 2,
"table": 1,
"book": 0,
"box": 1,
"lamp": 2,
"door": 1,
"window": 3
}
}
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