metadata
language:
- en
library_name: ultralytics
pipeline_tag: object-detection
tags:
- yolo
- object-detect
- yolo11
- yolov11
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
