Annotate-Lab is an open-source application designed for image annotation, comprising two main components: the client and the server. The client, a React application, is responsible for the user interface where users perform annotations. On the other hand, the server, a Flask application, manages persisting the annotated changes and generating masked and annotated images, along with configuration settings. More information can be found in our documentation.
- Project Structure
- Dependencies
- Setup and Installation
- Running the Application
- Usage
- Outputs
- Troubleshooting
- Contributing
- License
annotation-lab/
├── client/
│ ├── public/
│ ├── src/
│ ├── package.json
│ ├── package-lock.json
│ └── ... (other React app files)
├── server/
│ ├── db/
│ ├── tests/
│ ├── venv/
│ ├── app.py
│ ├── requirements.txt
│ └── ... (other Flask app files)
├── README.md- public/: Static files and the root HTML file.
- src/: React components and other frontend code.
- package.json: Contains client dependencies and scripts.
- db/: Database-related files and handlers.
- venv/: Python virtual environment (not included in version control).
- tests/: Contains test files.
- app.py: Main Flask application file.
- requirements.txt: Contains server dependencies.
One can configure the tools, tags, upload images and do many more from the settings.
- React
- Axios
- Other dependencies as listed in
package.json
- Flask
- Flask-CORS
- pandas
- Other dependencies as listed in
requirements.txt
- Navigate to the
clientdirectory:cd client - Install the dependencies:
npm install
- Navigate to the
serverdirectory:cd server - Create and activate a virtual environment:
python3 -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`
- Install the dependencies:
pip install -r requirements.txt- Navigate to the
clientdirectory:cd client - Install the dependencies:
npm start
The application should now be running on http://localhost:5173.
- Navigate to the
serverdirectory:cd server - Activate the virtual environment:
source venv/bin/activate # On Windows use `venv\Scripts\activate`
- Start the Flask application:
flask run
The server should now be running on http://localhost:5000.
First, change the VITE_SERVER_URL to http://127.0.0.1:8080.
Then, navigate to the root directory and run the following command to start the application:
docker-compose build
docker-compose up -d #running in detached mode
- Open your web browser and navigate to http://localhost:5173.
- Use the user interface to upload and annotate images.
- The annotations and other interactions will be handled by the Flask server running at http://localhost:5000.
Sample of annotated image along with its mask and settings is show below.
{
"configuration":[
{
"image-name":"orange.png",
"regions":[
{
"region-id":"47643630436867834",
"image-src":"http://127.0.0.1:5000/uploads/orange.png",
"class":"Orange",
"comment":"",
"tags":"",
"points":[
[
0.4685613390092879,
0.7693498452012384
],
[
0.6781491873065015,
0.6640866873065016
],
[
0.723921246130031,
0.5092879256965944
],
[
0.7480118034055728,
0.34055727554179566
],
[
0.5841960139318886,
0.14705882352941177
],
[
0.41917569659442727,
0.13312693498452013
],
[
0.30113196594427244,
0.22755417956656346
],
[
0.21079237616099072,
0.4411764705882353
],
[
0.26620065789473685,
0.6764705882352942
],
[
0.4011077786377709,
0.7879256965944272
]
]
},
{
"region-id":"5981359766055432",
"image-src":"http://127.0.0.1:5000/uploads/orange.png",
"class":"Apple",
"comment":"",
"tags":"",
"x":[
0.1770655959752322
],
"y":[
0.11764705882352941
],
"w":[
0.5854005417956657
],
"h":[
0.6981424148606811
]
}
]
}
]
}
- Ensure that both the client and server are running.
- Check the browser console and terminal for any errors and troubleshoot accordingly.
- Verify that dependencies are correctly installed.
If you would like to contribute to this project, please fork the repository and submit a pull request. For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License.
This project uses some part of work from idapgroup react-image-annotate and image_annotator.