Enhance image quality with a CNN Autoencoder, leveraging deep learning. Image upscaling is crucial in various domains where high-resolution visuals are paramount. Often, low-resolution images suffer from pixelation, blur, or lack of detail, hindering their utility. This project focuses on employing a CNN-based approach to upscale images while mitigating issues like blur and noise. The incorporation of blur reduction techniques ensures sharper edges and clearer details, while noise reduction enhances the overall image quality, eliminating artifacts. Moreover, the transformation from black and white to color images expands the application spectrum, breathing life into monochromatic visuals.
Consider applications in medical imaging, where enhanced resolution aids in precise diagnostics. Similarly, in surveillance systems, upscaling with noise reduction significantly improves the accuracy of object recognition. Additionally, historical image restoration benefits from this process, reviving aged photographs into vivid, detailed representations. These features collectively empower diverse fields, ranging from art and entertainment to scientific analysis, by providing enhanced, more interpretable visual data.
● Run pip install requirements.txt in the terminal
● Run all the Python files in the Kaggle notebook(recommended) given in the folder to get h5 files and add them to the folder in which the flask file is located
● Run app.py file
● Navigate to the localhost where you can view your web page.
● Select an Enhancement type
● Upload an image you want to enhance
● Click on the Check button to see the result.
It contains the home page button(ImgUp), About us, About Project, and the upload button where you can upload the image that you want to enhance.
In this we have given a brief description and the role played by each of them in the project, contact information.
In this, we have a brief explanation of our project and use cases.
This is a customized 404 page not found page which is shown when you search for a directory that doesn’t exist in the server.
