ProcessAeye - Echtzeit Kamera Inpainting
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Date
2024
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Abstract
The core idea of ProcessAeye is to restore missing or damaged parts of an image in real-time. The goal is to develop an application that reads images from a camera and restores them based on the missing areas, which are defined by the user.
To achieve this goal, three main components are required:
The NVIDIA Jetson Nano is a small, powerful computer designed specifically for AI applications, enabling real-time processing and restoration of images through machine learning models.
Through a Deep Learning model or a classical image processing algorithm, the images are reconstructed. Various models and classical algorithms have been compared in terms of the time required per restoration run and the quality of the results, with the best approaches being used for real-time restoration.
The reconstructed images are displayed in a graphical user interface alongside the original image. In the original image, the user can mark the missing parts of the image using a drawing module. To clearly demonstrate the difference between classical algorithms and deep learning models, users can choose from six different approaches, including three classical algorithms and three machine learning models.
The result is a desktop application optimized for the NVIDIA Jetson Nano which offers six approaches to image restoration. Because the user can draw the mask themselves, the application is ideally suited to illustrate the difference between classical algorithms and deep learning models.