Project description

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This sample project shows off how to prepare and deploy to Azure Web Apps a simple Python web service with an image classifying model produced in CNTK (Cognitive Toolkit) using FasterRCNN

[x] Web Service written in Python using Flask module
[x] Python scripts that allow to evaluate images using CNTK and pretrained model
[x] Custom deployment scripts for Azure Web Apps
[x] Automatic setup of custom Python 3.5.x environment with all the required dependencies
[ ] HTML UI for testing image classification
[ ] Virtual Python environments for each application deployed to Azure Web Apps

Results

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Website Demo:
Demo

Sample request and response in Postman: Demo

Deployment steps

Setup

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Download content of this repo

You can either clone this repo or just download it and unzip to some folder
Setup Python environment

In order for scripts to work you should have a proper Python environment. If you don't already have it setup then you should follow one of the online tutorials. To setup Python environment and all the dependencies required by CNTK on my local Windows machine I used this tutorial
Download CNTK model and class map file

Go to /CNTKModels folder in the location were you unzipped this repo and run download_model.py. It will automatically download the pretrained model and class map file required for our evaluation to run properly.
Install Azure CLI tools

If you don't have it then you can easily do it by openning Windows Command Prompt and running this command:
```
pip install azure-cli
```
Get Azure subscription

If you don't own any Azure subscriptions you can always create a new free trial with $200 credits to spend

Deploy demo

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Set variables

Open Command Prompt to the location where you unzipped the contents of this repository (for example: cd C:\Poligon\WebService) and type in as follows (but make sure to replace the [] with a proper value):
```
set uname=[username]
set pass=[password]
set appn=[web_app_name]
set rgname=[resource_group_name]
```
Login to Azure

In the same CMD type in:
```
az login
```
You should see something like this:

Now go to the https://aka.ms/devicelogin website and type in the code:

You will then be asked to login with an email connected to your Azure subscription

If everything goes ok you should see the verification message on the website and in console you should see a list of your Azure subscriptions
Setup deployment credentials

We're setting this up to later be able to remotely deploy code to our Azure Web App
```
az webapp deployment user set --user-name %uname% --password %pass%
```
Create resource group

Resource groups help you to better manage your stuff in subscription and it's a basic method of deploying services to Azure. Read more here
```
az group create --location westeurope --name %rgname%
```

Create new Azure App Service Plan and new Azure Web App

az appservice plan create --name %appn% --resource-group %rgname% --sku S1
az webapp create --name %appn% --resource-group %rgname% --plan %appn%

Configure Azure Web App and add Python extension

Azure Web Apps by default support only Python 2.7 and 3.4. Because I used Python 3.5 I had to use special extension to setup the environment

First you need to change some Application Settings on your Web App (the pink ones): Changing Platform is required and changing Always On is optional but I recommend to use it so that our web service stays awake even if not used.

After we properly save Application Settings we can now add Python 3.5.x extension. In order to this, just type in extensions into the search box

And then simply add new extension

It should take around a minute or two to properly install the extension
Setup deployment source for newly created Azure Web App

This code will not only setup the deployment source for your app but will also retrive the URL you will need in next steps
```
az webapp deployment source config-local-git --name %appn% --resource-group %rgname% --query url --output tsv
```
It should return something like this:
Initialize git and add remote repository

Make sure to replace [remote_repo_address] with the URL returned in step number 7.
```
git init
git remote add azure [remote_repo_address]
```
Command with URL should look like this:
Push application to Azure Web App remote repository

Last step is to simply push our applications code to Azure Web App
```
git add -A
git commit -m "init"
git push azure master
```
This will trigger our custom deployment script, copy all the files, setup Python environment and install all the required dependencies from requirements.txt file
Test the application

If everything went smooth you should now have a running Python application and you should be able to test it. I used Postman to test HTTP requests and responses

Website Demo:

Sample request and response in Postman:

Code highlights

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config.py - most important variables for scripts are set in this file

Variables used by web service to point out directories for temp images and CNTK models:

# directories for web service:
__C.CNTK.TEMP_PATH = "./Temp" # temp folder for image processing - do not change
__C.CNTK.MODEL_DIRECTORY = "./CNTKModels" # directory for storing models and class map files

Variables for chosing the specific model:

__C.CNTK.MODEL_NAME = "HotailorPOC2.model" # model file name
__C.CNTK.CLASS_MAP_FILE = "HotailorPOC2_class_map.txt" # class map file name

Variables used by evaluate.py to properly preprocess images and use CNTK eval function:

__C.CNTK.IMAGE_WIDTH = 1000
__C.CNTK.IMAGE_HEIGHT = 1000
__C.CNTK.NUM_CHANNELS = 3

app.py - main application - startup file for Flask

There is one very important line for running CNTK:
```
[..]
import os
os.environ['PATH'] = r'D:\home\python354x64;' + os.environ['PATH']    
[..]
```
It adds the location of CNTK libraries to PATH variable. It's very important because our code strongly relies on that PATH. As for now I'm doing this in code but in future I want to move it to deployment script

I am using Flask module to run my web service. In order to make it work I needed to first create an instance of Flask app and then run it on a proper port:
```
[..]
app = Flask(__name__)
[..]    
if __name__ == '__main__':
    HOST = os.environ.get('SERVER_HOST', 'localhost')
    try:
        PORT = int(os.environ.get('SERVER_PORT', '5555'))
    except ValueError:
        PORT = 5555
    app.run(HOST, PORT)
```
I also used routes to set up specific methods for our RESTful web service. Currently I expose 2 routes for my API, one returning a collection of classified tags and the second one returning an image with plotted results of evaluation. '/' route simply sets the default landing page
```
[..]
@app.route('/')
[..]
@app.route('/hotelidentifier/api/v1.0/evaluate/returntags', methods=['POST'])
[..]
@app.route('/hotelidentifier/api/v1.0/evaluate/returnimage', methods=['POST'])
[..]
```
evaluate.py - main script for image classification with CNTK model

This script strongly depends on config.py and it also uses cntk_helpers.py, plot_helpers.py and bunch of scripts from utils folder. Most of those scripts were copied from original CNTK source on github, some of them with slight changes

plot_helpers.py - helper script for dealing with image ploting

While working with headless server environment (non-GUI) such as Azure Web Apps you need to change the default mode of matpotlib module to not rely on GUI

[..]
# this is important when deploying to headless server environment (non-GUI)
###################################################
import matplotlib
# force headless backend, or set 'backend' to 'Agg'
# in your ~/.matplotlib/matplotlibrc
matplotlib.use('Agg')

import matplotlib.pyplot
# force non-interactive mode, or set 'interactive' to False
# in your ~/.matplotlib/matplotlibrc
from matplotlib.pyplot import imsave
matplotlib.pyplot.ioff()
###################################################    
[..]

requirements.txt

It holds all the dependencies required by my application and CNTK libraries to work.

easydict==1.6
pytest==3.0.3
opencv-python
https://pypi.python.org/packages/be/5c/670e88bc3ae6afa23c1f09d52a77bbbc7d2e476e7449ad3b6750040a0ac6/scipy-1.0.0b1-cp35-none-win_amd64.whl#md5=dcc90577f2eebc264ec60a2d5729e30b
https://cntk.ai/PythonWheel/CPU-Only/cntk-2.1-cp35-cp35m-win_amd64.whl
Flask==0.12.2
numpy==1.11.2
matplotlib==1.5.3
ipython==6.2.0
Pillow==4.1.1
PyYAML==3.12

As you can see in most cases we use specific versions of modules and sometimes we even explicitly point out the correct .whl file to use for installation

.deployment

If this file is present, Kudu will use custom deploy.cmd file instead of the default one. We use custom deployment script to chose Python3.5 and install all the necesary dependencies. To learn more about Kudu and deploying to Azure Web Apps - go here
```
[config]
command = deploy.cmd
```
deploy.cmd

Custom script for our deployment with Kudu. Main difference from the default script is that I'm setting Python3.5 (installed from extension) as my main environment
```
[..]
SET PYTHON_DIR=%SYSTEMDRIVE%\home\python354x64
SET PYTHON_EXE=%SYSTEMDRIVE%\home\python354x64\python.exe
[..]
```
I'm also using deploy.cmd to install all the required dependencies:
```
[..]
:: 4. Install packages
echo Pip install requirements.
echo "Installing requirements"
%PYTHON_EXE% -m pip install -r requirements.txt
[..]
```
TODO: I was told that it is better to have virtual Python environment for each app hosted on Azure Web Apps so that there is no chance of conflicts in different versions of modules used by different apps. That is what I need to fix in future.

web.config

I used web.config to point out the directory of my custom Python 3.5 installation and to successfully run my Flask based Python web service. I based my web.config on Azure Web Apps documentation.

<?xml version="1.0" encoding="utf-8"?>
<configuration>
<system.webServer>
    <handlers>
        <add name="PythonHandler" path="*" verb="*" modules="httpPlatformHandler" resourceType="Unspecified"/>
    </handlers>
    <httpPlatform processPath="D:\home\python354x64\python.exe"
                arguments="D:\home\site\wwwroot\app.py --port %HTTP_PLATFORM_PORT%"
                stdoutLogEnabled="true"
                stdoutLogFile="D:\home\site\wwwroot\logs\log_file2.log"
                startupTimeLimit="220"
                processesPerApplication="5">
        <environmentVariables>
            <environmentVariable name="SERVER_PORT" value="%HTTP_PLATFORM_PORT%" />
        </environmentVariables>
    </httpPlatform>
</system.webServer>
</configuration>

Table of contents

Project description

Results

Deployment steps

Setup

Deploy demo

Code highlights