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Image Segmentation using Mask R-CNN

This project demonstrates image segmentation using the Mask R-CNN model.

Setup

  1. Clone the repository:

    git clonec https://github.com/matterport/Mask_RCNN.git
    cd Mask_RCNN
  2. Install dependencies:

    pip install -r requirements.txt
  3. Download pre-trained weights:

    wget https://github.com/matterport/Mask_RCNN/releases

Usage

  1. Run the Jupyter Notebook:

    jupyter notebook Image_segmentation.ipynb
  2. Configuration:

    • Set up the environment and import necessary libraries.
    • Configure the Mask R-CNN model for inference.
    • Load pre-trained weights for the COCO dataset.
    • Define class names for the COCO dataset.
  3. Visualization:

    • Visualize the model's predictions on sample images.

Results

The notebook demonstrates how to use Mask R-CNN for image segmentation, including loading pre-trained weights and visualizing predictions.

Example IMG

References

  • Mask R-CNN paper
  • COCO dataset