This code was sourced from https://github.com/advimman/lama.

This version has been modified from the original source.

Specifically, bin/predict_single.py includes a wrapper class for the model, which streamlines the inpainting process for a single image and mask.

Example usage in example_usage.py file

To Use This Repository

• Download model checkpoint from here
• Move best.ckpt to assets/lama_checkpoint folder. File path should be assets/lama_checkpoint/best.ckpt
• Create virtual environment. See next section for details
• Activate virtual environment.
• Run example_usage.py or your own implementation.

Using a Virtual Environment

Running this repository locally requires a virtual environment. If you have one great, just run 'pip install -r requirements.txt' inside your environment.

Setting up an environment

• Using Python

  You can create a python virtual environment by running 'python -m venv .venv' in your project directory. You can activate the environment by running 'source ./.venv/bin/activate'.

• Using Conda (pre-requisite having conda installed)

  You can create a conda virtual environment by running 'conda create --name env'. You can activate the envionment by running 'conda activate env'

• Installing Requirements

  Once you have a running environment, you can run 'pip install -r requirements.txt' to install the required libraries.

Modifed by Marcus Wright