The road damage detection model used in this project is based on the architecture mobilenet single shot detector. It has been implemented using the tensorflow object detection api
The model's weights are present in the finetuned folder. Pre-trained coco model was used as a base for training. The model was trained on this dataset, combined with some examples we created and labelled ourselves. In total the datset was divided into 1697 training examples and 716 test examples.
In order to run the model, run the detection notebook using the command:
This project was bootstrapped with Create React App.
In the project directory, you can run:
Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
You can learn more in the Create React App documentation.
To learn React, check out the React documentation.
This section has moved here: https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify