/datumaro-gui

Simplify the process of managing datasets in computer vision tasks using Datumaro, by offering a GUI. Split, Merge, Filter Dataset (i.e. coco).

Primary LanguagePythonMIT LicenseMIT

Datumaro-GUI

Datumaro-GUI is a graphical user interface (GUI) built with Streamlit to make working with computer vision datasets using Datumaro easier and more intuitive. This project aims to provide an easy-to-use interface for registering, merging, and filtering annotations.

Features

  • Register new datasets: Upload and process images and annotations to create new datasets.
  • Merge datasets: Combine existing datasets with new data and split them into training and validation sets.
  • Filter annotations: Apply custom filters to datasets to extract specific data based on conditions.
  • AWS S3 Integration: Load existing datasets from S3 and upload the processed datasets back to S3.

Project Structure

datumaro-gui/
├── app.py
├── utils.py
├── pages/
│   ├── merge.py
│   ├── new.py
│   ├── filter.py
├── requirements.txt
├── README.md
└── credentials/
    └── aws.yaml
  • app.py: The main entry point for the Streamlit application.
  • utils.py: Utility functions for handling file uploads, AWS S3 interactions, and other helper functions.
  • pages/: Contains the different pages for the Streamlit app.
    • merge.py: Page for merging datasets.
    • new.py: Page for registering new annotations.
    • filter.py: Page for applying filters to datasets.
  • credentials/aws.yaml: Stores the AWS credentials for interacting with S3.

Installation

  1. Clone the repository:

    git clone https://github.com/ccomkhj/datumaro-gui.git
cd datumaro-gui/

  2. Create a virtual environment and activate it:

    conda create -n datumaro-gui python=3.11 -y
conda activate datumaro-gui

    [Note] tested with python =< 3.11 OR

    python3 -m venv env
source env/bin/activate  # On Windows, use `env\Scripts\activate`

  3. Install the dependencies:

    pip install -r requirements.txt

  4. (if you want to use S3) Set up AWS credentials in credentials/aws.yaml:

    aws_access_key_id: <YOUR_AWS_ACCESS_KEY_ID>
aws_secret_access_key: <YOUR_AWS_SECRET_ACCESS_KEY>

Usage

  1. Run the Streamlit application:

    streamlit run app.py

  2. Open your browser and go to http://localhost:8501 to interact with the Datumaro-GUI.

Contributing

Contributions are welcome! Feel free to submit a pull request or open an issue.

License

This project is licensed under the MIT License. See the LICENSE file for details.