Integrated Colorization and Styling Approach for Enhancing Image Clarity
Gollapalli Madhu Shalini, Rakam Anand, Thalloju Sankeerth, H. Venkateswara Reddy, Shanmugasundaram Hariharan, Vinay Kukreja · 2024
Image exploration adopts several dimensionalities with web-based tasks, integrating Streamlit and OpenCV to create an interactive platform for advanced image enhancement. Alongside the transformative tool enabling conversion of black and white images into vibrant compositions, an innovative styling suite offers diverse artistic filters. Notably, the addition of a camera option allows users to capture photos directly within the interface. Through Streamlit’s intuitive interface and OpenCV’s robust image processing, users experience real-time previews for seamless colorization and filtering. The proposed methodology involves designing a responsive web interface, optimizing Streamlit widgets for file uploads and style selection, and leveraging OpenCV for image processing. Results demonstrate the application’s effectiveness, providing immediate insights into style impact. Challenges include processing speed optimization, with future research directions exploring advanced Machine Learning (ML) models for dynamic style transfer. In summary, this research advances interactive image processing, offering a refined platform for creative visual content enhancement. The results obtained is promising leading to effective image colorization and styling, thereby improving the quality of the image.