This project is intended to help the car insurance industry with the following idea: leverage object-detection to scan passing cars and determine the most common models and brands on an avenue or other specified location. Our plans were to use a Raspberry Pi 3 model B connected with a Raspberry Pi V2 camera in order to upload the images to a premade model of YoLo v3 or v4 and detect objects, cars in this case. By counting the brands as the cars pass by, we may be able to generate statistics and other metrics that could be useful to car insurance companies.
https://github.com/AlexeyAB/darknet & https://youtu.be/HUQoh0-lY8A
Before running this project, the following must be installed as we installed them for this project:
- Flutter 2.0.6
- Visual Studio Code 1.55.2
In order to run the application, run the following commands in windows command line terminal in Visual Code, after opening the Skynet Folder:
- cd skynet_app
- flutter run -d chrome