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.

References

• Mask R-CNN paper
• COCO dataset