Computer Vision Course Project 1 (2023)

This repository contains codes and demonstrations for the Computer Vision Course Project 1 on Image Watermarking.

Demo video

Run the following commands in the master root to create a new virtual env to run the files in local:

conda create -n <ENV NAME> python=3.9
conda activate <ENV NAME>
conda install -r requirements.txt

To test any of the watermarking techniques just run the relevant python file such as python3 LSB.py. Inside the .py file replace the already existing image path with the path of the image you want to test on.
Alternatively you can use it as a library. The demonstration for the same has been shown in the relevant test.ipynb file.

The folder "visual" consists of code relevant to the visual watermarking attack and dataset generation.
- Modify the image directory path in the prepare_dataset.py as per your requirements.
- first prepare the dataset by running the prepare_dataset.py. Make sure to create the folders outputs and removal_results.
- Now run the remove_watermark.py file to see the results.
The folder "util" contains helper facilities to run the encryption algorithms on different inputs and check their output.
The file metrics.py consists of several metrics which we have implemented to evaluate the performance of the algorithms. To add another metric just create a function and add the mapping in the dictionary at the bottom of the file as has been illustrated.
For more comprehensive analysis and comparison, refer to report.

Aaditya Baranwal baranwal.1@iitj.ac.in ; Github: eternal-f1ame
Ayush Anand anand.5@iitj.ac.in ; Github: iamayushanand