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Skill Level: Beginner
N.B: All services used in this repo are Lite plans.
Read this in other launguages: 한국어
In this code pattern, we will identify industrial equipment for various damages upon visual inspection by using machine learning classification techniques. Using Watson Visual Recognition, we will analyze the image against a trained classifier to inspect oil and gas pipelines with six identifiers - Normal, Burst, Corrosion, Damaged Coating, Joint Failure and Leak. For each image we will provide a percent match with each of the category, on how closely the image matches one of the damaged identifiers or the Normal identifier. This data can then be used to create a dashboard to the pipelines needing immediate attention to no attention.
The images data is stored in a Cloudant database which makes it easier to connect remote devices (including drones) to capture images. The database can store different properties of the images like location and description. This code pattern demonstrates IBM Cloud Functions (OpenWhisk) to trigger microservice as an image is added to the Cloudant database. The microservice performs the Visual Recognition analysis and updates the Cloudant database with the analysis data.
When the reader has completed this code pattern, they will understand how to:
- Train Visual Recognition to classify images
- Configure Cloudant database to store and retrieve image data
- Set up IBM Cloud Functions to trigger Visual Recognition analysis and store result in Cloudant database
- Launch a web app to view a dashboard of the Visual Recognition analysis, and deploy to IBM Cloud
- User uploads the image through the web UI
- The image data is send to the Cloudant database
- As the image is added into the database, the Cloud Functions triggers microservice
- The microservice analyzes the image using the trained Watson Visual Recognition service
- The analyzed data is fed back into the Cloudant database
- The dashboard on the web UI displays the Visual Recognition analysis and images requiring attention
Follow these steps to setup and run the application. The steps are described in detail below.
- Watson Visual Recognition Setup
- Cloudant NoSQL DB Setup
- IBM Cloud Functions Setup
- Run Web Application
Create the Watson Visual Recognition service in IBM Cloud. You will need the API Key.
- Open a command line interface (CLI) on your desktop and clone this repo:
git clone https://github.com/IBM/Predictive-Industrial-Visual-Analysis
- Go to the folder where the images are placed
cd Predictive-Industrial-Visual-Analysis/vr-image-data
Here we will create a classifier using the zipped images to train the Watson Visual-Recognition service. The images in each zipped folder are used to make the Watson VR service become familiar with the images that relate to the different categories (Corrosion, Leak, etc.). Run the following command to submit all 6 sets of images to the Watson service classifier:
curl -X POST -u "apikey:{INSERT-YOUR-APIKEY-HERE}" -F "Bursted_Pipe_positive_examples=@Burst_Images.zip" -F "Corroded_Pipe_positive_examples=@Corrosion_Images.zip" -F "Damaged_Coating_positive_examples=@Damaged_Coating_Images.zip" -F "Joint_Failure_positive_examples=@Joint_Failure_Images.zip" -F "Pipe_Leak_positive_examples=@Leak_Images.zip" -F "Normal_Condition_positive_examples=@Normal_Condition.zip" -F "name=OilPipeCondition" "https://gateway.watsonplatform.net/visual-recognition/api/v3/classifiers?version=2018-03-19"
The response from above will provide you with a status on the submission and will give you a CLASSIFIER_ID. Please copy this for future use as well. After executing the above command, you can view the status of your Watson service and whether it has finished training on the images you submitted. You can check the status like this:
curl -X GET -u "apikey:{INSERT-YOUR-APIKEY-HERE}" "https://gateway.watsonplatform.net/visual-recognition/api/v3/classifiers/{INSERT-CLASSIFIER-ID-HERE}?api_key={INSERT-API-KEY-HERE}&version=2018-03-19"
You can find more information on working with your classifier here
Create the Cloudant NoSQL service in IBM Cloud.
Create a new database in Cloudant called image_db
Next you need to go to create a view of the database. Click on Launch Cloudant Dashboard button.
Next, select the data base you just created image_db. Then select the + next to Design Documents and click on New View.
Next, create a view on the database with the design name image_db_images, index name image_db.images, and use the following map function:
function (doc) {
if ( doc.type == 'image_db.image' ) {
emit(doc);
}
}
We will now set up the IBM Cloud Functions (OpenWhisk) using Bluemix CLI.
- Install the Cloud Functions Plugin
ibmcloud plugin install Cloud-Functions -r Bluemix
- Log in to IBM Cloud, and target a Region (i.e api.ng.bluemix.net), Organization (i.e Raheel.Zubairy) and Space (i.e dev).
ibmcloud login -a {INSERT REGION} -o {INSERT ORGANIZATION} -s {INSERT SPACE}
We will need the API authentication key and host.
- Command to retrieve API host:
ibmcloud wsk property get --apihost
- Command to retrieve API authentication key:
ibmcloud wsk property get --auth
N.B: make sure what plan (Lite, etc.) you are associating when creating this service.
You will need to provide credentials to your Cloudant NoSQL database and Watson Visual Recognition service, and Cloud Functions Host/Auth information retrieved in the previous step, into a .env file. Copy the sample .env.example file using the following command:
cp .env.example .env
and fill in your credentials and your VR Classifier name.
#From cloudant NoSQL database
CLOUDANT_USERNAME=
CLOUDANT_PASSWORD=
CLOUDANT_HOST=
CLOUDANT_URL=
CLOUDANT_DB=image_db
#From Watson Visual Recognition Service
VR_KEY=
VR_URL=
VR_CLASSIFIERS=OilPipeCondition_1063693116
#From OpenWhisk Functions Service in IBM Cloud
FUNCTIONS_APIHOST=
FUNCTIONS_AUTHORIZATION=
We will now run the setup_functions.sh file to set up the microservice which triggers the Visual Recognition analysis as an image is added to the Cloudant database.
chmod +x setup_functions.sh
./setup_functions.sh --install
The above command will setup the OpenWhisk actions for you, there should be no need to do anything else if you see an Install Complete message with green OK signs in the CLI.
In IBM Cloud, look for Functions in Catalog. There you will see a UI to configure the service including Actions, Triggers and Monitor the service.
If you encounter an error in your Monitor tab, check this section on Trigger Error to resolve.
To run the app, go to the Industrial-Visual-Analysis folder and run the following commands.
- Install the dependencies you application need:
npm install
- Start the application locally:
npm start
Test your application by going to: http://localhost:3000/
You can push the app to IBM Cloud by first editing the manifest file file and then using cloud foundry cli commands.
Edit the manifest.yml file in the folder that contains your code and replace with a unique name for your application. The name that you specify determines the application's URL, such as your-application-name.mybluemix.net. Additionally - update the service names so they match what you have in IBM Cloud. The relevant portion of the manifest.yml file looks like the following:
applications:
- path: .
memory: 256M
instances: 1
domain: mybluemix.net
name: {industrial-visual-analysis}
disk_quota: 1024M
services:
- {cloudant-service}
- {visual-recognition-service}
Create a cloud foundry service as alias for the visual recognition service:
ibmcloud resource service-alias-create "{visual-recognition-service}" --instance-name "{visual-recognition-service}" -s Dev
In the command line use the following command to push the application to IBM Cloud:
bx app push YOUR_APP_NAME
The app has the following functions:
-
The homepage displays a quick dashboard showing the number of images in the Cloudant database and how many of them have Watson VR analysis completed. It will also provide a count of how many images were deemed as "Needing attention" based on the response the Watson service provided when classifying the images.
-
You have the ability to see all the images in one single page.
-
Click on each image to pull up a detailed page providing information on one single event (image). You will be able to see information on what the Watson Visual Recognition service saw in the image and the confidence levels. You can continue to train the service by using the thumbs up and thumbs down next to each percent match.
-
You can click the
Upload New Imagebutton to send images to the Cloudant database. There are sample images in thesample-imagesfolder to try out.
This code pattern can be extended by adding a Drone to take images. A DJI drone can be used to capture images and configured to send images to our Cloudant database. As the image is received by the Cloudant database, the VR analysis and image detail can be displayed through the web UI.
If you invoke GET /classifiers with verbose=1 what do you see? If that list is empty, and you get this error message, you should open an IBM Cloud support ticket. If it's not empty, you should use DELETE /classifiers/{classifier_id} to remove the existing classifier so that you can create your new one.
The setup_functions.sh have different commands to uninstall, re-install or update IBM Cloud Functions. And to view the env credentials used by IBM Cloud Functions.
- Uninstall:
./setup_functions.sh --uninstall
- Re-install:
./setup_functions.sh --reinstall
- Show env cred:
./setup_functions.sh --env
If your images are not being analyzed, open the Monitor window in your IBM Cloud Functions. If you receive an error At least one of filter or query_params parameters must be supplied:
You can manually add the parameter by going to the Trigger option on the left side menu and opening the image_db-cloudant-update-trigger:
Here click on the Parameters option on the left side menu and manually add the parameters with Parameter Name: dbname, and Parameter Value: "image_db"
Try running the application again.
To troubleshoot your IBM Cloud application, use the logs. To see the logs, run:
bx app logs <application-name> --recent- Artificial Intelligence Code Patterns: Enjoyed this Code Pattern? Check out our other AI Code Patterns.
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This code pattern is licensed under the Apache Software License, Version 2. Separate third party code objects invoked within this code pattern are licensed by their respective providers pursuant to their own separate licenses. Contributions are subject to the Developer Certificate of Origin, Version 1.1 (DCO) and the Apache Software License, Version 2.