Vriddhi is a desktop application that uses deep learning algorithms to perform super resolution on images and videos. By upscaling low-resolution content to high-resolution, it provides users with a better viewing experience, especially in low-bandwidth and remote areas where expensive digital infrastructure is not available.
Vriddhi uses a pre-trained Enhanced Super Resolution Generative Adversarial Network (ESRGAN) model to upscale images and videos by 4x. ESRGAN is a state-of-the-art deep learning method that enhances the visual quality of images beyond the original resolution.
To install and run Vriddhi, follow these steps:
- Clone the repository:
git clone https://github.com/ujjwaltyagi2000/vriddhi.git
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Install dependencies:
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If using pip:
pip install -r requirements.txt
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If using Anaconda:
conda env create -f environment.yml conda activate vriddhi
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Run the application:
python main.py
To use Vriddhi, follow these steps:
- Open the application.
- Click on the "Enhance Image" or "Enhance Video" button to select the file you want to upscale.
- Select the path where you wish to save the enhanced result.
- Once the process is complete, you will be able to see the 4x upscaled result in your selected folder.
Apart from providing high-quality videos in low-bandwidth and remote areas, Vriddhi has many other potential applications, such as:
- Enhancing the resolution of medical images for better diagnosis.
- Improving the quality of security camera footage for better identification of suspects.
- Enhancing satellite images for better analysis of environmental changes.
- Upscaling low-resolution images for printing or display purposes.
- The ESRGAN model used in this project was trained by the authors of the ESRGAN paper.
- This the link to the trained model.