Exmplar Based Object Removal

This is an Implementation of exempler based object removal. https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/criminisi_cvpr2003.pdf

We Have A NICE GUI if you want to run the code

Prerequisites

Make sure you have Python installed on your system. It's recommended to use Python 3.8 or later.

Step 1: Create a Virtual Environment

It is best practice to create a virtual environment to manage your dependencies:

python -m venv myenv
source myenv/bin/activate  # On Windows, use `myenv\Scripts\activate`

Step 2: Install Dependencies

Use the following command to install the required dependencies:

pip install numpy==1.21.5 opencv-python==4.10.0.84 matplotlib==3.5.1

Step 3: Verify the Installation

You can verify that the dependencies are installed correctly by running:

python -c "import numpy, cv2, matplotlib; print('All dependencies are installed successfully!')"

Step 4: Run the GUI

To run the GUI application, execute the Python script responsible for the GUI. Replace your_script.py with the name of your script:

cd src
python gui.py

Notes

• Ensure your virtual environment is activated while running the GUI.
• If you encounter any issues, ensure all required dependencies are correctly installed by running:

pip list

This will show you all installed packages and their versions.

Deep Learning Based Object Removal

• Navigate to DNNs Folder
• Put your Images and Masks in in_lama Folder
• Run command bash RunDNN.sh
• Wait Till it finish and find your results in out_lama

Contributors

Asmaa Abozaid

Ahmed Hamdy

Abdelrahman Sami

shehab khaled