Welcome to Herbify Deploy Model Repository!

This is our simple REST API running on Flask.

Prerequisite

Before you can running this server.py you need to provide the following:

• Virtual Machine on GCP (make sure open the port 8080, and have correct permission for Cloud Storage)
• Git, for cloning the repository
• pip, for installing python module
• ML Model that already trained

Let's Rock!

Run the command below step by step to make sure you're on the right track.

1. Update your system package manager (in this case we're using apt) and then installed important programs.

sudo apt update && sudo apt install -y git python3-pip screen

2. Update pip so we can install the newest tensorflow

pip3 install pip --upgrade

3. Clone this repo

git clone https://github.com/herblabsai/herbify-deploy-model.git

4. Change dir to herbify-deploy-model and then install important modules

cd herbify-deploy-model
pip3 install -r requirements.txt

in case you're getting error like MemoryError when installing tensorflow, please use the following command instead

pip3 install --no-cache-dir -r requirements.txt

5. Download our ML model here, and save them in herbify-deploy-model directory
6. Run the command via screen command, so you can leave the terminal safely

screen -S herbify python3 server.py

Known issue(s)

1. When running the server.py you got this error, (Error :
   ImportError: libGL.so.1: cannot open shared object file: No such file or directory). Please install the following library from your system package manager

sudo apt install ffmpeg libsm6 libxext6 -y

How to test?

1. If you have Postman installed, take a look at the screenshot below. You only need to change the your-url-here with your public IP address or domain.
2. If you don't have Postman installed, use the test.py file instead.

Reference

1. tensorflow-image-classification-flask-deployment by faizan170.