/AI-Image-Annotation

An intuitive Python tool for annotating images with bounding boxes. Easily assign custom classes to objects and save annotations. Includes AI model integration for automated annotation. Perfect for streamlining computer vision projects. classes to these objects, and save annotations.

Primary LanguageJupyter NotebookMIT LicenseMIT

AI Image Annotator 🖼️

The AI Image Annotator is a Python application built with tkinter for annotating images with bounding boxes representing objects detected in the images. It also provides functionality to annotate images using an AI model for object detection.

Features ✨

  • Load and display images for annotation.
  • Draw bounding boxes around objects in images.
  • Annotate images with custom classes and colors.
  • Annotate images manually or with the assistance of an AI model.
  • Save annotations in YOLO Format.

Requirements 🛠️

  • Python 3.x
  • tkinter
  • OpenCV (cv2)
  • Pillow (PIL)
  • matplotlib
  • autodistill
  • autodistill_grounding_dino

Usage 🚀

  1. Clone the repository:
git clone https://github.com/Marinto-Richee/Image-annotation.git
  1. Navigate to the project directory:
cd image-annotator
  1. Install the required dependencies:
pip install -r requirements.txt
  1. Run the application:
python image_annotator.py
  1. Load images by clicking on the "Load Images" button.
  2. Draw bounding boxes around objects in the images by clicking and dragging the mouse.
  3. Choose classes from the "Annotation Classes" section to assign to the bounding boxes.
  4. Optionally, use the "AI Annotate" button to annotate images with the assistance of an AI model.
  5. Save annotations using the "Save Annotations" button.

Screenshots 📸

image image

image image

License 📝

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