The idea behind MLGC is to support any organization in their efforts of becoming more sustainable. More precisely, the proposed solution consists in a waste sorter based on image recognition.
As part of the project, the team has applied the TYOM feautre on SAP Cloud Platform and created a mobile interface for image recognition in order to simulate a trash scanner. The training datasample consisted in approximtely 300 pictures per category, available on Kaggle.
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Clone the repository.
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Navigate to the root directory of the repository.
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Create .env file and add the following fields:
- clientID="**************'"
- clientSecret="*******"
- authenticationURL="************************/oauth/token?grant_type=client_credentials"
- baseURL="https://mlftrial-image-classifier.cfapps.eu10.hana.ondemand.com/api/v2/image/classification"
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Run the following commands in the root directory:
- npm install
- npm start
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Open the browser and navigate to http://localhost:19002/
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Install the Expo app in the mobile phone.
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Open the Camera in the mobile and scan the QR code.
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Expo will generate a notification, open Expo using notification and let Expo do the rest.