This project utilizes the YOLOv10 model for detecting helmets in images. It's designed to enhance safety measures by identifying whether individuals in a given setting are wearing helmets. The project includes a pre-trained model and a Jupyter Notebook for training the model with custom datasets.
To set up this project, follow these steps:
- Clone the repository to your local machine.
- Ensure you have Python 3.8 or newer installed.
- Run all code section in notebook:
To train the model with your dataset, follow the instructions in yoylov10_train_helmet_detect.ipynb. This notebook guides you through the process of setting up your dataset, initializing the model, and starting the training process.
The pre-trained model yoylov10_helmet_detect_model.pt can be used for inference right away. Refer to the Jupyter Notebook for examples on how to load the model and perform inference on new images.