What is Car ROI Detection?

The aim of this project is to develop an automated system to detect and extract regions of interest (ROIs) within 360-degree car interior images. Specifically, the goal was to detect the car's characteristic parts, such as the Dashboard, Steering, Vents, Speedometer, etc., and identify them from the 360 images. In order to implement these functionalities, the features included in this project are image preprocessing, accurate classification, precise localization, and user-friendly coordination mapping.

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Other key Features

  • Users can easily upload 360-degree car interior images through a user-friendly interface, eliminating technical barriers and making the system accessible.
  • The system excels in identifying and extracting multiple ROIs within a single 360-degree image. This capability allows analysts to study various interior components comprehensively, saving time and effort.
  • The classification model specializes in extracting accurate data from the Dashboard and can provide precise outputs based on its identification.
  • The image classification model delivers pinpoint accuracy in identifying the Dashboard region. This precision ensures that the most critical areas of car interiors are consistently and reliably extracted for analysis.
  • With mapped ROI coordinates, users can effortlessly explore different car interior regions. This intuitive feature allows for seamless navigation and in-depth examination of specific design elements, enhancing the overall user experience.

Tech Stack Used

Choosing the right tech stack is very crucial as it will have an impact on the entire development lifecycle and beyond. Our tech stack will make no compromise in providing the best solutions to the clients and fulfilling their expectations.

  • Python
  • AI & ML

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