Food Classifier App with TensorFlow 2 model on Google Cloud Run
This repo contains a web app for classifying 3 types of local Singaporean Food using the following APIs and platforms
- TensorFlow 2: using tf.image, tf.keras.models and tf.data (for training)
- Google Cloud Platform: Cloud Run, Cloud Build, Cloud Storage
- Starlette, a lightweight ASGI framework/toolkit
Deploy with Google Cloud Run
Pre-requisites
- Google Cloud Account
- Enable Cloud Run and Cloud Build API
Deploy
To run the webapp on Google Cloud Run, launch Cloud Shell from your Dashboard.
- export PROJECT_ID={your project id here}
- Run
gcloud config set project $PROJECT_ID - Run
git clone https://github.com/yoke2/food_classifier_tf2_cloud_run.git - Change directory:
cd food_classififer_tf2_cloud_run - Build container image with Google Cloud Build by running
gcloud builds submit --tag gcr.io/$PROJECT_ID/food_classifier- If prompted that Cloud Build API not enabled on the project, enter 'y' to enable and retry
- Deploy container built:
gcloud run deploy --image gcr.io/$PROJECT_ID/food_classifier --platform managed --allow-unauthenticated --memory 1024M- You will be prompted for the service name: press Enter to accept the default name
- You will be prompted for region: select the region us-central1
- You will receive an URL to access the app. This can be seen on the Cloud Run page for
dimsumappin the Dashboard as well
Docker Installation
You can test your changes locally by installing Docker and using the following command:
docker build -t food-tf2-cr . && docker run --rm -it -p 8080:8080 food-tf2-cr
Local Installation
- Install dependencies
$ pip install packaging
$ pip install -r requirements.txt
Run app
$ python app/server.py serve