How to Use

To use this model in your project, follow the steps below:

1. Installation

Ensure you have the ultralytics library installed, which is used for YOLO models:

pip install ultralytics
# class
Fall-Detected

2. Load the Model

You can load the model and perform detection on an image as follows:

from ultralytics import YOLO

# Load the model
model = YOLO("./falldetect-11x.pt")

# Perform detection on an image
results = model("image.png")

# Display or process the results
results.show()  # This will display the image with detected objects

3. Model Inference

The results object contains bounding boxes, labels (e.g., numbers or operators), and confidence scores for each detected object.

Access them like this:

for result in results:
    print(result.boxes)   # Bounding boxes
    print(result.names)   # Detected classes
    print(result.scores)  # Confidence scores

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Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the HF Inference API does not support ultralytics models with pipeline type object-detection