🚀 Visual Recognition Sample Application
This Node.js app demonstrates some of the Visual Recognition service features.
DEPRECATED: this repo is no longer actively maintained. It can still be used as reference, but may contain outdated or unpatched code.
This demo application has been replaced by a newer version, and thus this repo has been deprecated. You can view the updated application running live here. The new application has not been made public yet, so in the meantime this repo can still be used as reference.
The Visual Recognition Service uses deep learning algorithms to analyze images for scenes, objects, faces, text, and other subjects that can give you insights into your visual content. You can organize image libraries, understand an individual image, and create custom classifiers for specific results that are tailored to your needs.
- Sign up for an IBM Cloud account.
- Download the IBM Cloud CLI.
- Create an instance of the Visual Recognition service and get your credentials:
- Go to the Visual Recognition page in the IBM Cloud Catalog.
- Log in to your IBM Cloud account.
- Click Create.
- Click Show to view the service credentials.
- Copy the
- Copy the
Configuring the application
In the application folder, copy the .env.example file and create a file called .env
cp .env.example .env
Open the .env file and add the service credentials that you obtained in the previous step.
Example .env file that configures the
urlfor a Visual Recognition service instance hosted in the US East region:
Install the dependencies
Run the application
View the application in a browser at
Deploying to IBM Cloud as a Cloud Foundry Application
Login to IBM Cloud with the IBM Cloud CLI
Target a Cloud Foundry organization and space.
ibmcloud target --cf
Edit the manifest.yml file. Change the name field to something unique.
- name: my-app-name.
Deploy the application
ibmcloud app push
View the application online at the app URL.
For example: https://my-app-name.mybluemix.net
VISUAL_RECOGNITION_IAM_API_KEY: This is the IAM API key for the vision service, used if you don't have one in your IBM Cloud account.
PRESERVE_CLASSIFIERS: Set if you don't want classifiers to be deleted after one hour. (optional)
PORT: The port the server should run on. (optional, defaults to 3000)
OVERRIDE_CLASSIFIER_ID: Set to a classifer ID if you want to always use a custom classifier. This classifier will be used instead of training a new one. (optional)
Changing the Included Images
The sample images are the first 7 images when the site loads. They
are called from a Jade mixin found in
views/mixins/sampleImages.jade. If you just want to replace those
images with different images, you can replace them in
public/images/samples and they are numbered 1 - 7 and are
Custom Classifier Bundles
Adding new/different custom classifer bundles is much more invovled.
You can follow the template of the existing bundles found in
Or, you can train a custom classifier using the api or the form and then use the classifier ID.
Getting the Classifier ID
When you train a custom classifier, the name of the classifier is displayed in the test form.
If you hover your mouse over the classifier name, the classifier ID will be shown in the tooltip. You can also click on the name, and it will toggle between the classifier name and the classifier ID.
You can then use this custom classifier id by placing it after the hash
in the request URL. For example, lets say you are running the system
locally, so the base URL is
http://localhost:3000 and then you train
a classifier. This newly trained classifier might have an id like
SatelliteImagery_859438478. If you wanted to use this classifier
instead of training a new one, you can navigate to
http://localhost:3000/train#SatelliteImagery_859438478 and use the
training form with your existing classifier.
This sample code is licensed under Apache 2.0. Full license text is available in LICENSE.
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