Recommendation system based on visual recognition.

When the reader has completed this, they will understand how to:

Connect to Mobile First Foundation using a mobile application.
Take inputs from mobile application and do required processing on IBM Cloud.
Use Watson Visual Recognition using a mobile application.
Deploy and use cloud foundry applications.
Access images from Cloud Object Storage using a mobile application.
Connect and access Db2 on Cloud.

Flow

Take input from user's mobile.
The input is passed via Mobile First Foundation.
Mobile First Foundation passes the user's input to the visual recognition application.
The visual recognition application interacts with the Watson Visual Recognition service, which returns appropriate output.
The output(age and gender of user) is then send to user's mobile application.
The user clicks on "Get Recommendations" button.
Requests the recommendation engine to return appropriate recommendation based the visual recognition applications output.
Recommendation engine interacts with IBM Db2 to get the necessary product details for the recommended products.
Images of the recommended products is retrieved from Cloud Object Storage.
Images and details of the recommended products is retrieved by the recommendation engine.
Recommendation engine returns the images and details of the recommended products to the user's mobile application.
User can now add items to the cart and view them.

Pre-requisites

IBM Cloud account : Create an IBM Cloud account.
Python 3: Install python 3.
Java 1.8.x: Make sure you have required version (Java 1.8.x).

Steps

Please follow the below to setup and run this code pattern.

Clone the repo
Recomendation Engine Setup
Watson Visual Recognition Setup
Mobile Application Setup

1. Clone the repo

Clone this git repo. Else, in a terminal, run:

$ git clone https://github.com/IBM/recommender-with-watson-visual-recognition.git

2. Recommendation Engine Setup

In this step we will be building a recommendation engine which takes users's age and gender as input ,and gives out a recommendation accordingly.

2.1. Sign up for IBM Cloud Object Storage

We use IBM Cloud Object Storage to store the jewellery images required for recommendation and the dataset.

2.1.1 Create IBM Cloud Object Storage

In the IBM Cloud Dashboard, click on Catalog and select Object Storage service under Infrastructure -> Storage. Click on Create as shown below.
The IBM Cloud Object Storage dashboard will get shown. In the Buckets tab, click on Create bucket. Give an unique name for the bucket. Set the selections for Resiliency (Cross Region), Location (us-geo) and Storage class (Standard), and click on Create as shown below.

Note: Make a note of the Bucket Name as it is Important and will be used in step 4.4.2

2.1.2 Create Service ID and API Key for accessing objects

Create Service ID
- In a separate browser tab/window, launch the IBM Cloud Identity & Access Management dashboard using URL https://cloud.ibm.com/iam/.
- In case you have multiple IBM Cloud accounts, then select the target Account, Region, Organization and Space.
- Under Identity & Access (on the left side of the page), select Service IDs and click Create on the right top of the page. Give a name and description, and click Create.
- Make a note of the name of the Service ID as shown below.

Note: Make a note of the name of the Service ID as it is Important and will be used in step 4.4.2

Add Cloud Object Storage Writer role to that service ID
- Back in IBM Cloud Object Storage dashboard, select Bucket permissions under Buckets click on policies.
- Click on Service IDs tab. Under Select a service ID, select the service ID created in the above step. Under Assign a role to this service ID for this bucket, select Writer. Click Create policy as shown below.

You should get a confirmation dialog saying “Service permission created“.

Create API Key
- Back in IBM Cloud Identity & Access Management dashboard, under Service IDs, click on the service ID created earlier. Under Access policies, you should see the Writer role for your bucket.
- Click on API keys tab and then click on Create button. In the Create API key dialog, give a name and description for the API key and click on Create. You should get a confirmation dialog saying API key successfully created as shown below.
- Click on Download and save the API key as shown below. Note: This is the only time you will see the key. You cannot retrieve it later.
- You can now close the tab.

Note: Make a note of the API Key as it is Important and will be used in step 4.4.2

2.2.Add the IBM Cloud Object Storage credentials to the python application

To access the Cloud Object Storage service programmatically, you need to copy in your credentials, which you can find in your IBM Cloud Object Storage service credentials in IBM Cloud.

Open your IBM Cloud Data Resource list. A list of your provisioned resources is displayed.
Locate your Cloud Object Storage instance under Storage tab and click on that.
Open the Service Credentials tab on the right left side of the page, click new credential and give a name.
Select Include HMAC Credentials as shown bellow.
View your credentials by clicking View Credentials.
Copy your credentials. Create a file credentials1.json and paste the copied credentials into this file.Place this file in the directory JewelleryRecommendation and also in the directory UploadProductsCOS.
Replace xxxxxx in the place holder bucket_name with your corresponding bucket name in the file KMeans_200.py.

2.2.1 Upload Images to cloud object Storage

Replace xxxxxx in the place holder bucket_name with your corresponding bucket name in the file upload.py.
Run the file upload.py locally to upload images and dataset to Cloud Object Storage.

$ python3 upload.py

2.3. Sign up for IBM Db2 on Cloud Service

Create a IBM Db2 instance IBM db2.

2.4. Load product details into Db2

Lanch your Db2 on cloud and click on load, as shown below.

Click on browse files and upload data.csv, as shown below. data.csv can be found in the root folder of ProductDetailsDB2.

Choose the default schema and create a table PRODUCTS, as shown below.

Click on Next, as shown below.

Click on Next.
Click on Begin Load, as shown below.

Once the data is loaded, you can view the table which will look like the image, shown below.

NOTE: Make sure you note down the table name. In my case the table name is ZJN44169.PRODUCTS.

2.5. Add the IBM db2 credentials to the python application

Replace the placeholder username, password, sg_service_url, database, host, port under credentials_1 in the file KMeans_200.py.
Replace XXXX.YYYY in the place holder insert with your corresponding table name in the file KMeans_200.py.

NOTE: You can get username, password, sg_service_url, hostname, port number and Database credentials by creating/clicking New Credentials from your Db2 service instance on cloud.

2.6. Deploy python application to cloud foundry

Create a cloud foundry instance IBM Cloud Foundry Service and follow set of instructions for deploying python application to IBM Cloud Foundry.

NOTE: Make Sure the Cloud Foundry App gets at least 256MB of Memory. You can verify it by going to IBM Cloud Dashboard > Resources > Cloud Foundry Apps > YOUR_APP_NAME.

Use IBM Cloud command line interface to download, modify, and redeploy your Cloud Foundry applications and service instances.
Before you begin, download and install the IBM Cloud CLI.
After you install the command line interface, you can get started.
Change to the directory.

$ cd JewelleryRecommendation

Note : Make sure that KMeans_200.py, credentials1.json, requirements.txt, manifest.yml and Procfile is present in the directory JewelleryRecommendation.

Connect and log in to IBM Cloud.

$ ibmcloud api https://api.eu-gb.bluemix.net

$ ibmcloud login -u example@in.ibm.com -o example@in.ibm.com -s dev

NOTE: If you are using a federated ID, use the -sso option.

$ ibmcloud login  -o example@in.ibm.com -s dev -sso

NOTE: You must add single or double quotes around username, org_name, and space_name if the value contains a space, for example, -o "my org".

Finally Deploy the application by following command.

$ ibmcloud cf push YOUR-APP-NAME

Example: ibmcloud cf push recommendation-engine

Once you have deployed the application Make a note of the URL of the instance by right clicking on the Visit app URL and copying the link.

Note: This URL is Important as it will be used in step 4.4.2

2.7. Test your deployment

To Test your deployment use any REST Clients like Postman. After Installing postman type https://YOUR-APP-URL/?age=40&name=Kavya&gender=F to test whether Recommendation engine works.

Now click on Send button to run the GET / API. The API response should be shown in the Response Body as shown in snapshot below.

3. Watson Visual Recognition Setup

The Watson Visual Recognition service take the user's Image as Input and predicts the age and gender of the user.

3.1 Create a Visual Recognition service

Create a Visual Recognition service in the IBM Cloud.
Copy the Api Key from the Visual Recognition Dashboard as shown bellow.
Go to the VisualRecognition directory.

$ cd VisualRecognition

In the credentials.json file, for the key vrapi paste the copied Api key value in the place of YOUR-API-KEY-HERE as shown bellow.


{
    "vrapi": "YOUR-API-KEY-HERE"
}

3.2 Create a Cloud Foundry Instance & Deploy

Create a cloud foundry instance IBM Cloud Foundry Service and follow set of instructions for deploying JavaScript application to IBM Cloud Foundry.

NOTE: Make Sure the Cloud Foundry App gets at least 256MB of Memory. You can verify it by going to IBM Cloud Dashboard > Resources > Cloud Foundry Apps > YOUR_APP_NAME.

Use IBM Cloud command line interface to download, modify, and redeploy your Cloud Foundry applications and service instances.
Before you begin, download and install the IBM Cloud CLI.
After you install the command line interface, you can get started.
Go to the VisualRecognition directory.

$ cd VisualRecognition

Connect and log in to IBM Cloud.

$ ibmcloud api https://api.eu-gb.bluemix.net

$ ibmcloud login -u example@in.ibm.com -o example@in.ibm.com -s dev

NOTE: If you are using a federated ID, use the -sso option.

$ ibmcloud login  -o example@in.ibm.com -s dev -sso

NOTE: You must add single or double quotes around username, org_name, and space_name if the value contains a space, for example, -o "my org".

Finally Deploy the application by following command.

$ ibmcloud cf push YOUR_APP_NAME

Example: ibmcloud cf push watsonvr

Once you have deployed the application Make a note of the URL of the instance by right clicking on the Visit app URL and copying the link.

Note: This URL is Important as it will be used in step 4.4.2.

4. Mobile Application Setup

The Mobile Application is the component that connects Virtual Mirror and Recommendation Engine.

4.1 Setup Ionic and MFP CLI

Install Node.js by downloading the setup from https://nodejs.org/en/ (Node.js 8.x or above)

$ node --version
v10.15.0

Install Cordova

$ sudo npm install -g cordova@8.1.2
$ cordova --version
8.1.2

Note: Please refer MFP documentation for compatible versions of Cordova - https://mobilefirstplatform.ibmcloud.com/tutorials/en/foundation/8.0/application-development/sdk/cordova/

Install Ionic

$ sudo npm install -g ionic@4.12.0
$ ionic --version
4.12.0

Install IBM MobileFirst Platform CLI

$ sudo npm install -g mfpdev-cli
$ mfpdev --version
8.0.0-2018121711

Note: If you are on Windows, instead of using sudo, run the above command without sudo in a command prompt opened in administrative mode.

Note: While installing MFP CLI, if you hit an error saying npm ERR! package.json npm can't find a package.json file in your current directory., then it is most likely due to MFP CLI not being supported in your npm version. In such a case, downgrade your npm as below, and then install MFP CLI. $ sudo npm install -g npm@3.10.10

Install Java SDK 8 from https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html

$ java -version
java version "1.8.0_101"

Note: Java version 1.8.x is required for cordova to compile apks. Do not Download Java version 11.x. If you already have java version above 1.8.x then you can follow the guide in TROUBLESHOOTING.md to uninstall the java and reinstall 1.8.x.

Install Maven: On Mac, you can use brew install for installing Maven as shown below:

$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
$ brew install maven
$ mvn --version
Apache Maven 3.6.0 ...

On Windows, you can follow this Tutorial to install Maven.

Install Gradle: On Mac, you can use brew install for installing Maven as shown below:

$ brew install gradle
$ gradle --version
Gradle 5.1.1 ...

On Windows, you can follow this Tutorial to install Gradle.

4.2 Create Mobile Foundation service and configure MFP CLI

In the IBM Cloud Dashboard, click on Catalog and select Mobile Foundation service under Platform -> Mobile. Click on Create as shown below.
In the Mobile Foundation service overview page that gets shown, click on Service credentials. Expand View credentials and make a note of the url, user and password as shown below.

NOTE: The user, password and url is Important as it will be used in subsequent steps.

NOTE: Make Sure the Cloud Foundry App for Mobile Foundation-Server gets at least 768MB of Memory.(Recommended is 1GB) You can verify it by going to IBM Cloud Dashboard > Resources > Cloud Foundry Apps > MobileFoundation-Server as shown below.

Note: If Mobile Foundation service is not available with your current account type, then you can either:

Upgrade your account, and avail the Mobile Foundation service's free Developer plan which allows the use of the service free for up to ten daily client devices for development and testing activities, or

Back on your local machine, configure MFP CLI to work with Mobile Foundation server by running the following command in console.

Note: For Enter the fully qualified URL of this server:, enter the url mentioned in credentials followed by :443 (the default HTTPS port).

$ mfpdev server add

Follow the Instructions.

? Enter the name of the new server profile: MyServer
? Enter the fully qualified URL of this server: https://mobilefoundation-xxxx-xxxxx.xx-xx.mybluemix.net:443
? Enter the MobileFirst Server administrator login ID: admin
? Enter the MobileFirst Server administrator password: **********
? Save the administrator password for this server?: Yes
? Enter the context root of the MobileFirst administration services: mfpadmin
? Enter the MobileFirst Server connection timeout in seconds: 30
? Make this server the default?: Yes
Verifying server configuration...
The following runtimes are currently installed on this server: mfp
Server profile 'MyServer' added successfully.

Next Verify If the Server is added.

$ mfpdev server info
Name         URL
---------------------------------------------------------------------------------------
MyServer  https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net:443  [Default]
---------------------------------------------------------------------------------------

Note: If this step fails check TROUBLESHOOTING.md to fix commonly occuring errors.

NOTE: This URL is Important as it will be required in subsequent Steps.

4.3 Customize the App (Optional)

Go to the JewelleryStoreApp directory.

$ cd JewelleryStoreApp

Update App ID, Name and Description in JewelleryStoreApp/config.xml as below. Change id, name, description and author details as shown bellow.


<?xml version='1.0' encoding='utf-8'?>
<widget id="com.ibm.mfpthejewellerystore" version="1.0.0" xmlns="http://www.w3.org/ns/widgets" xmlns:cdv="http://cordova.apache.org/ns/1.0" xmlns:mfp="http://www.ibm.com/mobilefirst/cordova-plugin-mfp">
    <name>The Jewellery Store</name>
    <description>A virtual mirror integration into ecommerce products with the help of mobilefirst foundation.</description>
    <author email="example@in.ibm.com" href="/">Code Patterns Team </author>
...Specify Cloud Object Storage credentials in MFP Adapter
Recommendation Engine API & Virtual Mirror API in MFP Adapter

4.4 Deploy the MFP Adapter and Test it

4.4.1 Build and Deploy the MFP adapters

Go to the MobileFoundationAdapter directory inside JewelleryStoreApp directory.

$ cd MobileFoundationAdapter

$ cd ImagesFetch

Add the URL along with the port number :443 appended with /mfpadmin, User and Password in the pom.xml file which is present in ImagesFetch directory as show bellow.


...
<mfpfUrl>https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net:443/mfpadmin </mfpfUrl>
<mfpfUser>admin </mfpfUser>
<mfpfPassword>******** </mfpfPassword>
<mfpfRuntime>mfp </mfpfRuntime>
...

Build the ImagesFetch adapter as shown below.

$ mfpdev adapter build
Building adapter...
Successfully built adapter

Deploy the adapter as shown bellow.

$ mfpdev adapter deploy
Verifying server configuration...
Deploying adapter to runtime mfp on https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net:443/mfpadmin...
Successfully deployed adapter

Note: In [Step 4.2], if you specified No to Make this server the default?, then you need to specify the name of your server profile (MyServer in our case) at the end of mfpdev adapter deploy command as shown below.

$ mfpdev adapter deploy MyServer

4.4.2 Launch MFP dashboard and update adapter configurations

Launch MFP Dashboard as below:

In the IBM Cloud dashboard, under Cloud Foundry Services, click on the Mobile Foundation service you created in [Step 4.2]. The service overview page that gets shown, will have the MFP dashboard embedded within it. You can also open the MFP dashboard in a separate browser tab by appending /mfpconsole to the url https://mobilefoundation-xxxx-xxxxx.xx-xx.mybluemix.net.

Example: https://mobilefoundation-xxxx-xxxxx.xx-xx.mybluemix.net/mfpconsole

NOTE: username & password can be found in Service credentials in step 4.2.

Inside the MFP dashboard, in the list on the left, you will see the VisualRecognition adapter listed.

Update MFP Adapter configuration as below:

Inside the MFP dashboard, click on the ImagesFetch adapter. Under Configurations tab, you should see the various properties for accessing Cloud Object Storage, recommendation Engine Api and Visual Recognition Api as shown below.
The Cloud Object Storage Bucket Name can be found in step 2.1.1, Cloud Object Storage API Key can be found in step 2.1.2, Cloud Object Storage Endpoint can be found by going to IBM Cloud Dashboard > Resources > Storage > Cloud Object Storage and clicking on Endpoint and the public link for Resiliency and Location as selected in step 2.1.1 and Cloud Object Storage Service ID can be found in step 2.1.2.
The Recommendation Engine API URL is your python app url and can be found in step 2.7, Visual Recognition API URL is your NodeJs app url and can be found in step 4.2.
Save the changes by clicking Save.
Click on Resources tab. You should see the various REST APIs exposed by VisualRecognition adapter as shown below.

4.4.3 Test the ImagesFetch adapter

To Test the adapter use any REST Clients like Postman. After Installing postman type the url created in [step 4.2] and append it with /mfp/api/adapters/ImagesFetch/resource and /objectStorage to test whether the adapter is establishing connection with Cloud Object Storage.

Example: https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net/mfp/api/adapters/ImagesFetch/resource/objectStorage

Now click on Send button to run the GET / API. The API response should get shown in the Response Body as shown in snapshot below.
The GET API on /objectStorage should return a JSON object containing baseUrl and authorizationHeader as shown below.

The GET API on /recommendationEngine should return a JSON object containing recommendationEngineApi as shown below.

Example: https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net/mfp/api/adapters/ImagesFetch/resource/recommendationEngine

The GET API on /visualRecognition should return a JSON object containing VisualRecognitionApi as shown below.

Example: https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net/mfp/api/adapters/ImagesFetch/resource/visualRecognition

4.5 Run application on Android phone

4.5.1 Install Android Studio and Android SDK platform

Download and install Android Studio from https://developer.android.com/studio/
Install Android SDK Platform 23 (or higher) as below:
- Launch Android Studio.
- Click on Configure -> SDK Manager
- Make a note of the Android SDK Location.
- Under SDK Platforms, select Android 6.0 (Marshmallow) API Level 23 or higher. Click Apply and then click OK. This will install Android SDK Platform on your machine.

4.5.2 Enable developer options and USB debugging on your Android phone

Enable USB debugging on your Android phone as per the steps in https://developer.android.com/studio/debug/dev-options
- Launch the Settings app on your phone. Select About Device -> Software Info. Tap Build number 7 times to enable developer options.
- Return to Settings list. Select Developer options and enable USB debugging.
If you are developing on Windows, then you need to install the appropriate USB driver as per instructions in https://developer.android.com/studio/run/oem-usb.
Connect the Android phone to your development machine by USB cable, you will get a prompt displaying adb access required, allow the access.

Note: If you have android adb tools you can check whether your device is connected or not by entering adb devices.

4.5.3 Register the Virtual Mirror App to MFP server

Go back to JewelleryStoreApp directory.

$ cd ../JewelleryStoreApp

Register the app as Shown bellow.

$ mfpdev app register
Verifying server configuration...
Registering to server:'https://mobilefoundation-xxxx-xxxxxx.xx-xx.mybluemix.net:443' runtime:'mfp'
Updated config.xml file located at: .../Ionic-MFP-App/IonicMobileApp/config.xml
Run 'cordova prepare' to propagate changes.
Registered app for platform: android

Note: In [Step 4.2], if you specified No to Make this server the default?, then you need to specify the name of your server profile (MyServer in our case) at the end of mfpdev app deploy command as shown below. $ mfpdev app register MyServer

Note: To Propagate changes by running cordova prepare

4.5.5 Build/Run the Ionic application on Android phone

Build Android application

$ ionic cordova build android

Note: The build & run commands should be executed in the JewelleryStoreApp directory and not else where.

Note: Make sure you Connect the Android phone to your development machine by USB cable, and accept the adb access permissions.

Run application on Android device

$ ionic cordova run android

Allow the Camera Permission and Storage Permission when prompted. Without this the virtual mirror will not work.

NOTE: Storage Permission will be asked only if you choose to select a picture from camera.

NOTE: If there is not camera prompt in your mobile device follow step 4 from TROUBLESHOOTING.md to fix it.
To get your age and gender either click a picture or choose an existing picture.
A list of Jewellery will be Recommended based on your age and gender.
You can add any Jewellery to the cart.

4.5.6 Update App Logo and Splash (Optional)

Reference: Automating Icons and Splash Screens https://blog.ionicframework.com/automating-icons-and-splash-screens/

Copy your desired app icon to JewelleryStoreApp/resources/icon.png and app splash to JewelleryStoreApp/resources/splash.png.

$ ionic cordova resources

For running ionic cordova resources command, you would need to sign up on ionicframework.com and specify the credentials on the command line.

4.6 Build APK for uploading to Google Play Store (Optional)

Reference: https://ionicframework.com/docs/intro/deploying/

Add following lines at the end of JewelleryStoreApp/platforms/android/app/src/main/proguard-project-mfp.txt:

-dontwarn okhttp3.internal.huc.**

Create release build as below:

$ cd ../JewelleryStoreApp

$ ionic cordova build android --prod --release

Set ANDROID_HOME environment variable as per instructions in [Step x.x]. On Mac, this is usually:

export ANDROID_HOME=/Users/<username>/Library/Android/sdk

Zip align release build as below:

$ cd ./platforms/android/build/outputs/apk/
$ ls
android-release-unsigned.apk
$ $ANDROID_HOME/build-tools/28.0.3/zipalign -v -p 4 android-release-unsigned.apk android-release-unsigned-aligned.apk
$ ls
android-release-unsigned-aligned.apk	android-release-unsigned.apk

Create self signing certificate as below:

Make a note of the Keystore password that you set. You would need it for signing your APK.

$ keytool -genkey -v -keystore my-release-key.jks -keyalg RSA -keysize 2048 -validity 10000 -alias my-alias

Enter keystore password:
Re-enter new password:
What is your first and last name?
  [Unknown]:  xxxxx xxxxxxxxx
What is the name of your organizational unit?
  [Unknown]:  XXX
What is the name of your organization?
  [Unknown]:  XXX
What is the name of your City or Locality?
  [Unknown]:  Xxxxxxxxxx
What is the name of your State or Province?
  [Unknown]:  Xxxxxxxxx
What is the two-letter country code for this unit?
  [Unknown]:  XX
Is CN=xxxxx xxxxxxxxx, OU=XXX, O=XXX, L=Xxxxxxxxxx, ST=Xxxxxxxxx, C=XX correct?
  [no]:  yes

Generating 2,048 bit RSA key pair and self-signed certificate (SHA256withRSA) with a validity of 10,000 days
	for: CN=xxxx xxxxxxxxx, OU=XXX, O=XXX, L=Xxxxxxxxxx, ST=Xxxxxxxxx, C=XX
Enter key password for <my-alias>
	(RETURN if same as keystore password):
[Storing my-release-key.jks]

$ ls
android-release-unsigned-aligned.apk	android-release-unsigned.apk		my-release-key.jks

Self sign APK as below:

$ $ANDROID_HOME/build-tools/28.0.3/apksigner sign --ks my-release-key.jks --out thejewellerystore.apk android-release-unsigned-aligned.apk
Keystore password for signer #1:
$ ls
android-release-unsigned-aligned.apk	my-release-key.jks
android-release-unsigned.apk		thejewellerystore.apk
$

Distribute thejewellerystore.apk by uploading to Google Play Store or to your company's internal App store.

Troubleshooting

Debugging Android hybrid app using Chrome Developer Tools

Please see troubleshooting guide for solutions to some commonly occuring problems.

Install Google Chrome
Open Google Chrome. Open URL chrome://inspect/#devices
Connect your mobile phone to the deployment device via USB cable and you should see your device name listed on the page as shown.
Under Devices, click on inspect below your connected device.
You can see the console logs here for every action that the app performs.

License

Apache 2.0

Name		Name	Last commit message	Last commit date
Latest commit History 26 Commits
JewelleryRecommendation		JewelleryRecommendation
JewelleryStoreApp		JewelleryStoreApp
ProductDetailsDb2		ProductDetailsDb2
UploadProductsCOS		UploadProductsCOS
VisualRecognition		VisualRecognition
doc/source/images		doc/source/images
.DS_Store		.DS_Store
LICENSE		LICENSE
README.md		README.md
TROUBLESHOOTING.md		TROUBLESHOOTING.md

License

IBM/recommender-with-watson-visual-recognition

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Recommendation system based on visual recognition.

Flow

Pre-requisites

Steps

1. Clone the repo

2. Recommendation Engine Setup

2.1. Sign up for IBM Cloud Object Storage

2.1.1 Create IBM Cloud Object Storage

2.1.2 Create Service ID and API Key for accessing objects

2.2.Add the IBM Cloud Object Storage credentials to the python application

2.2.1 Upload Images to cloud object Storage

2.3. Sign up for IBM Db2 on Cloud Service

2.4. Load product details into Db2

2.5. Add the IBM db2 credentials to the python application

2.6. Deploy python application to cloud foundry

2.7. Test your deployment

3. Watson Visual Recognition Setup

3.1 Create a Visual Recognition service

3.2 Create a Cloud Foundry Instance & Deploy

4. Mobile Application Setup

4.1 Setup Ionic and MFP CLI

4.2 Create Mobile Foundation service and configure MFP CLI

4.3 Customize the App (Optional)

4.4 Deploy the MFP Adapter and Test it

4.4.1 Build and Deploy the MFP adapters

4.4.2 Launch MFP dashboard and update adapter configurations

4.4.3 Test the ImagesFetch adapter

4.5 Run application on Android phone

4.5.1 Install Android Studio and Android SDK platform

4.5.2 Enable developer options and USB debugging on your Android phone

4.5.3 Register the Virtual Mirror App to MFP server

4.5.5 Build/Run the Ionic application on Android phone

4.5.6 Update App Logo and Splash (Optional)

4.6 Build APK for uploading to Google Play Store (Optional)

Troubleshooting

Debugging Android hybrid app using Chrome Developer Tools

License

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