Watermark Removal: open source image watermark removal tool, picture watermark recovery original image

General Introduction

Watermark Removal is an open source project that utilizes machine learning and deep learning techniques for image restoration, specifically for removing watermarks from images. The project is developed by Chimzuruoke Okafor , inspired by Contextual Attention and Gated Convolution and other image restoration techniques . Using the TensorFlow framework, the project automatically removes watermarks from images without affecting the quality of the image, making the restored image virtually indistinguishable from the original.

Function List

• Watermark Removal: Automatically removes watermarks from images using machine learning techniques.
• Image Restoration: Restores the original state of the image and maintains high quality.
• open source: A complete code base is provided for free use and modification.
• Model Download: Provide pre-trained models to facilitate users to get started quickly.
• Google Colab Support: Supports running on Google Colab for easy experimentation and testing.

Using Help

Installation process

1. clone warehouse: First, clone the project's GitHub repository.

   git clone https://github.com/zuruoke/watermark-removal
cd watermark-removal

2. Installation of dependencies: Since this project uses TensorFlow version 1.15.0, you need to install the corresponding version of TensorFlow and other dependencies.

   pip install tensorflow==1.15.0
pip install git+https://github.com/JiahuiYu/neuralgym

3. Download model: Download the pre-trained model and place it in the model/ Catalog.

   # Download the model and extract it to the model/ directory

Usage Process

1. Prepare the image: Places the image to be watermarked in the specified directory.
2. Running Scripts: Run the main script with the following command to remove the watermark from the image.

   python main.py --image path-to-input-image --output path-to-output-image --checkpoint_dir model/ --watermark_type istock

3. View Results: The repaired image will be saved in the specified output path.

Detailed Function Operation

• Watermark Removal: by running main.py Scripts that allow users to specify input images and output paths to automatically remove watermarks from images.
• model training: Users can retrain the model as needed and adjust the parameters for better restoration results.
• code modification: As the project is open source, users can modify the code according to their own needs to achieve more customized features.