yolo11x-cls-mask / README.md
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metadata
language:
  - en
library_name: ultralytics
pipeline_tag: image-classification
tags:
  - mask

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
with_mask
without_mask

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("./mask-11x-224.pt")

# Perform detection on an image
results = model("image.png", imgsz=224)

# 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:

# View results
for r in results:
    print(r.probs)  # print the Probs object containing the detected class probabilities