IBM Visual Insights makes computer vision with deep learning more accessible to business users. The software includes an intuitive toolset that empowers subject matter experts to label, train, and deploy deep learning.
LICENSE
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What is IBM Visual Insights Evaluation Edition 1.2.0.1?
IBM Visual Insights makes computer vision with deep learning more accessible to business users. The software includes an intuitive toolset that empowers subject matter experts to label, train, and deploy deep learning vision models, without coding or deep learning expertise.
Designed for business users, the platform provides auto labelling and data augmenting capabilities to accelerate labelling of volumes of images & videos and even work with limited datasets. Bundled with several deep learning frameworks, models for training classifiers, object detectors, image segmentation and Action recognition are core features of the software. Once the models are trained, IBM Visual Insights lets you export the models to iOS devices, NVIDIA TX2/Nano and even to the cloud of your choice.
System Requirements
Before running the containers for IBM Visual Insights Evaluation Edition, please ensure that your system meets the following HW and SW requirements.
Software requirements
- Red Hat Enterprise Linux® (RHEL) RHEL 7.6 ALT (little endian) for POWER9™
- RHEL 7.7 for x86
- Ubuntu 18.04
Hardware requirements
- POWER8 S822LC (8335-GTB) or POWER9 AC922 with at least one NVIDIA NVLink capable GPU
- POWER9 IC922 with at least one NVIDIA T4 GPU
- x86 system with at least one NVIDIA Pascal, Volta, or Turing-architecture GPU
- 64 GB of memory
- Ethernet network interface
- 75 GB of storage for installation, and at least 40 GB of storage for runtime. See Disk space requirements for details.
Installation Instructions for NGC Clients
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Ensure Helm 2 / Tiller is available in your cluster.
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Ensure an Ingress is configured for your cluster.
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Create a namespace for the application. This is optional, but recommended. Subsequent commands will use
CustomNamespacenamespace as an example. Replace this with your own custom namespace.kubectl create namespace CustomNamespace -
Create an appropriate ClusterRoleBinding to enable PowerAI Vision to query Kubernetes. To create this, copy the below text into a crb.yaml file, where CustomNamespace is your custom namespace name:
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: CustomNamespace-crb roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: cluster-admin subjects: - kind: ServiceAccount name: default namespace: CustomNamespace -
Apply the ClusterRoleBinding:
kubectl create -f crb.yaml -
Verify that you have a minimum of 40 GB of persistent storage. If your kubernetes cluster has dynamic provisioned storage, you can use it for your persistent storage. To manually create persistent volumes, see the Kubernetes Storage Topics to learn how to work with persistent volumes. After you create the persistent volume, you must make the volume sharable across all nodes in the cluster.
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IMPORTANT: Containers within IBM Visual Insights run as non-root users for security reasons. You must set appropriate permissions in order for the application to start up correctly.
AIV_USER=1979 VOL_DIR=/insert/persistent/volume/path/here mkdir -p ${VOL_DIR}/data ${VOL_DIR}/run/logstash ${VOL_DIR}/run/elasticsearch ${VOL_DIR}/run/mongodb ${VOL_DIR}/run/pgsql chown ${AIV_USER}:${AIV_USER} ${VOL_DIR} ${VOL_DIR}/run chown -R ${AIV_USER}:${AIV_USER} ${VOL_DIR}/data chown 1000:1000 ${VOL_DIR}/run/logstash ${VOL_DIR}/run/elasticsearch chown 999 ${VOL_DIR}/run/mongodb chown 999 ${VOL_DIR}/run/pgsql -
Create an appropriate
imagePullSecretto allow IBM Visual Insights to dynamically pull container images from NGC as needed. Be sure to associate the secret with the namespace you created earlier. Refer to the Kubernetes documentation for details about how to pull an image from a private registry.#Note: This is a simple example. Your cluster may be different. Please note the '$oauthtoken' below. This is to provide NGC with the literal '$oauthtoken' username beginning with a dollar sign ($) expected to log in. kubectl create secret docker-registry --namespace CustomNamespace ngc --docker-server=nvcr.io --docker-username='$oauthtoken' --docker-password=YOUR-NGC-TOKEN --docker-email=o@auth.com kubectl patch serviceaccount --namespace CustomNamespace default -p '{"imagePullSecrets": [{"name": "ngc"}]}' # where: YOUR-NGC-TOKEN is your API token to access the NGC private registry -
Fetch the helm chart per the
helm pullcommand provided by NGC above. -
Deploy the chart with variables set based on your processor architecture (POWER9 or x86):
For x86 architecture with NVIDIA GPUs (amd64 or x86_64): helm install --name trial --namespace CustomNamespace ./ibm-visual-insights-prod-2.0.0.tgz --set image.pullPolicy=IfNotPresent --set image.releaseTag=1.2.0.0 --set image.repoPrefix=nvcr.io/partners/ibm For IBM Power architecture with NVIDIA GPUs (ppc64el or ppc64le or POWER): helm install --name trial --namespace CustomNamespace ./ibm-visual-insights-prod-2.0.0.tgz --set image.pullPolicy=IfNotPresent --set image.releaseTag=1.2.0.0 --set image.repoPrefix=nvcr.io/partners/ibmpower -
Wait for all pods to become ready, then log in via your cluster ingress. By default, the chart will create an
ingress-controllerthat follows thevisual-insights-HELMRELEASENAMEpattern (e.g./visual-insights-trial).helm status trial -
Log in to the application at https://ingress.hostname/visual-insights-trial . IMPORTANT: If you changed the chart deployment name from
trialto another value , log in athttps://ingress.hostname/visual-insights-HELMRELEASENAMEThe default username/passwordadmin / passw0rd. -
Change the default admin password. Note that you may not create new users in the Trial edition of this software.
kubectl run --rm -i --restart=Never usermgt --namespace CustomNamespace --image=nvcr.io/partners/ibm/vision-usermgt:1.2.0.0 -- modify --user admin --password INSERT-PASSWORD-HERE --release trial
Reach us
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Next Steps
Suggested Reading
- Product documentation
- Train deep leaning models to analyze x-rays for COVID-19
- Learning path to custom solutions with IBM Visual Insights
- Development assets and blogs
- Bringing insights to iOS devices with IBM Visual Inspector
- Visual insights for manufacturing
- Containers to deploy models to TX2
- Customize deployment of models to TX2
- REST APIs to customize a solution
- Art of possibilities
- Watch how IBM Visual Insights help COVID-19