This project, named Label-Studio-Yolo-Backend, is an open-source project aimed at providing an assisted labeling backend for Label Studio using label-studio-ml. The project consists of a single Python file and leverages the YOLOv5 model, which has been trained using Ultralytics YOLOv5. For more information on how to set up and integrate a machine learning backend with Label Studio, please refer to the Label Studio ML Backend repository.
This project was developed with the assistance of the GPT-4 language model, which also helped in the creation of this README file.
Label-Studio-Yolo-Backend is a project that provides an efficient way to integrate a YOLOv5 object detection model with Label Studio. This enables users to take advantage of the pre-trained YOLOv5 model to improve their annotation workflow and reduce the time required for manual annotation.
- Easy integration with Label Studio
- Leverages the powerful YOLOv5 object detection model
- Assisted annotation to speed up the labeling process
- Single Python file for easy setup and deployment
- Set up and install Label Studio following the instructions in their documentation.
- Install the Label Studio ML Backend by following the steps in their repository.
- Clone the Ultralytics YOLOv5 repository and follow the instructions to set it up.
- Clone this repository and copy the Python file to the appropriate directory in your Label Studio ML Backend setup.
- Configure your Label Studio project to use the Label-Studio-Yolo-Backend.
- Important Note: In some cases, you might need to modify the
get_local_pathfunction in themodel.pyfile of thelabel-studio-mllibrary. Please refer to this issue comment for more details and a potential solution.
This project was developed with the help of the GPT-4 language model, which also assisted in the creation of this README file.
Label-Studio-Yolo-Backend is released under the MIT License.