Hello, we're Tradify.
Tradify is an application which specializes in preserving traditional food. With tradify, both local and foreign tourists will be able to detect their own traditional foods & get the information from there. Our first prototype consists of the main features that are, food detection and providing information including the food itself, the history and, its origin. Our project is a submission for Bangkit 2022 Final Project.
| Student ID | Name | Path |
|---|---|---|
| C2200F1889 | Muhammad Ishaq | Cloud Computing |
| C2012F1246 | Farah Az Zahra | Cloud Computing |
| A2433G3012 | Riza Adi Kurniawan | Mobile Development |
| A2118F1489 | Shalsa Billa Dwi P | Mobile Development |
| M2002F0123 | Bryan Vergus S | Machine Learning |
| M2224W2071 | Wilda Nurjannah | Machine Learning |
you can clone our master branch and try the application. we're already putting all of the requirements on the repository. for trying the model, you can go to the tradify_model branch because it included the model and also the dataset
- Machine Learning (Bryan and Wilda) :
- Make dataset that consist of 8 classes traditional foods
- Building first model with CNN
- Improving the model performance with several data augmentations and using transfer learning method (VGG-19)
- convert the model into TensorFlow Lite format
- Cloud Computing (Ishaq & Farah) :
- Create a new project named Tradify under Bangkit.Academy Organization.
- Add 2 new principals from MD path and give them roles as owners so they can manage and use firesote database.
- Enable App Engine API, cloning the Application from Github using cloud shell, Deploy application and Machine Learning Model to Google Cloud Platform using app engine.
- Prepare database environment using Firestore (Create Cloud firestore in native mode, Create Firebase Project using Firebase console, Enable Google Analytics, apply region to the project and connect the firestore to the application)
- Mobile Development (Riza and Shalsa) :
- Designing UI application in Figma
- Implement design into the application project
- Implement firebase from Cloud Computing backend
- Feature testing