Planning for IBM Visual Insights

You must meet the software and hardware requirements and understand the supported file types before you can install IBM® Visual Insights.

Hardware requirements

IBM Visual Insights requires the following hardware:
The following devices are supported:
  • 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
Required specifications
Your device must meet these minimum requirements:
  • 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.
  • The Nvidia GPU must be configured in the Default compute mode. The Exclusive Process mode will cause trainings to fail. See nvidia-smi usage for details on compute modes.
  • There are multiple options for deploying the model for testing. Deploying a model to a Xilinx FPGA requires the Xilinx Alveo U200 Accelerator card.

Software requirements

You must install the following software before you install IBM Visual Insights:
  • Red Hat Enterprise Linux® (RHEL) RHEL 7.6 ALT (little endian) for POWER9™
  • RHEL 7.7 for x86
  • Ubuntu 18.04
    Note: The Ubuntu Hardware Enablement (HWE) kernel is not supported. Kubernetes services do not function correctly, preventing IBM Visual Insights from starting successfully.
10.1 Update 1 (if fix pack 1 is not installed) or later drivers. If fix pack 1 is installed, 10.2 or later drivers are required. For information, see the NVIDIA CUDA Toolkit website.
  • RHEL: docker-1.13.1
  • Ubuntu: Docker CE or EE 18.06.01

Networking requirements

Your environment must meet the following networking requirements:
  • A default route must be specified on the host system.
    • For instructions to do this on Ubuntu, refer to the IP addressing section in the Ubuntu Network Configuration. Search for the steps to configure and verify the default gateway.
    • For instructions to do this on Red Hat Enterprise Linux (RHEL), refer to 2.2.4 Static Routes and the Default Gateway in the Red Hat Customer Portal.
  • For RHEL, docker0 must be in a trusted firewall zone. If it is not in a trusted firewall zone, modify the RHEL settings as follows:
    sudo nmcli device set docker0 managed yes
    sudo nmcli connection modify docker0 trusted
    sudo systemctl stop NetworkManager.service
    sudo firewall-cmd --permanent --zone=trusted --change-interface=docker0
    sudo systemctl start NetworkManager.service
    sudo nmcli connection modify docker0 trusted
    sudo systemctl restart docker.service
  • IPv4 port forwarding must be enabled.

    If IPv4 port forwarding is not enabled, run the /sbin/sysctl -w net.ipv4.conf.all.forwarding=1 command. For more information about port forwarding with Docker, see UCP requires IPv4 IP Forwarding in the Docker success center.

  • IPv6 must be enabled.

Disk space requirements

IBM Visual Insights has the following storage requirements for the initial product installation and for the data sets that will be managed by the product.

Standalone installation
  • /var - The product installation requires at least 75 GB of space in the /var file system for the product Docker images. IBM Visual Insights also generates log information in this file system. The installation process requires additional space because all Docker images are extracted to disk requiring about 40 GB of space, then the images are loaded by Docker. When the image is loaded, the extracted image is deleted but while images are being extracted and loaded, space is needed for both copies. All application Docker images are extracted and loaded in parallel.

    Recommendation: If you want to minimize the root (/) file system, make sure that /var has its own volume.

  • /opt - IBM Visual Insights data sets, models, and runtime data are stored in this file system. This file system must have at least five GB of free space, in addition to any data sets, models or other runtime data for IBM Visual Insights to operate successfully. The storage needs will vary depending on the data sets and the contents. For example, video data can require large amounts of storage.

    Recommendation: If you want to minimize the root (/) file system, make sure that /opt has its own volume. The /opt file system should have at least 40 GB of space, although this value might be more depending on your data sets.

IBM Cloud Private installation
IBM Visual Insights will use the configured persistent storage for the deployment, the requirements are documented in Installing IBM Visual Insights with IBM Cloud Private.

Supported web browsers

The following web browsers are supported:

  • Google Chrome Version 60, or later
  • Firefox Quantum 59.0, or later

Image support

  • The following image formats are supported:
    • JPEG
    • PNG
    • DICOM
  • Images with COCO annotations are supported. For details, see Importing images with COCO annotations.
  • IBM Visual Insights has limited support for Pascal VOC annotations. Annotations for multiple files residing in a common XML file are not supported. In other words, each annotation XML file can only contain annotations for a single image, identified by the filename attribute.

    If you have a single XML annotation file containing annotations for multiple images in the data set to be imported, the annotations need to be split out into separate XML files before IBM Visual Insights can import the annotations successfully.

  • The models used by IBM Visual Insights have limitations on the size and resolution of images. If the original data is high resolution, then the user must consider:
    • If the images do not need fine detail for classification or object detection, they should be down-sampled to 1-2 megapixels.
    • If the images do require fine detail, they should to be divided into smaller images of 1-2 megapixels each.
    • There is a 24 GB size limit per upload session. This limit applies to a single .zip file or a set of files. You can, however upload 24 GB of files, then upload more after the original upload completes.
    • Large images will be scaled to the appropriate dimensions for the model as follows:
      • SSD: 512 x 512 pixels

        The original aspect ratio is maintained. If necessary, black bands are added to the image to make it fit.

      • tiny YOLO V2: 416 x 416 pixels

        The longest edge is scaled to 416 pixels and, if necessary, black bands are added to the shorter side to make it 416 pixels.

      • YOLO V3: 608 x 608 pixels
      • Faster R-CNN: 1000 x 600 pixels

        The original aspect ratio is maintained. If necessary, black bands are added to the image to make it fit.

      • Detectron: 1333 x 800 pixels
      • GoogLeNet: 224 x 224 pixels
      • Action detection: 224 x 224 pixels

Supported video types

The following video formats are supported:
Can be played in the IBM Visual Insights GUI:
  • Ogg Vorbis (.ogg)
  • VP8 or VP9 (.webm)
  • H.264 encoded videos with MP4 format (.mp4)
Supported by API only:
  • Matroska (.mkv)
  • Audio Video Interleave (.avi)
  • Moving Picture Experts Group (.mpg or .mpeg2)
Not supported:
Videos that are encoded with the H.265 codec.

Deep learning frameworks

The following frameworks are included with IBM Visual Insights.

Table 1. Included frameworks
Framework Version Python 2.7 support Python3.6 support Notes
Caffe 2 1.0.0 (If fix pack 1 is not installed.)

1.3.1 (If fix pack 1 is installed.)

Yes No Supported for Detectron models
IBM Caffe 1.0.0 Yes No Supported for GoogLeNet, Faster R-CNN, and tinyYOLO V2 models
Keras 2.2.4 (If fix pack 1 is not installed.)

2.3.1 (If fix pack 1 is installed.)

No (If fix pack 1 is not installed.)

Yes (If fix pack 1 is installed.)

Yes Supported for custom models
TensorFlow 1.14 (If fix pack 1 is not installed.)

2.1.0 (If fix pack 1 is installed.)

No Yes Supported for custom models
TensorRT 5.1.3 (If fix pack 1 is not installed.) (If fix pack 1 is installed.)

Yes Yes Supported for SSD models
PyTorch 1.1.0 (If fix pack 1 is not installed.)

1.3.1 (If fix pack 1 is installed.)

Yes Yes Supported for custom models


Following are some limitations for IBM Visual Insights 1.2.0:
  • IBM Visual Insights uses an entire GPU when you are training a dataset. Multiple GoogleNet or Faster R-CNN models can be deployed to a single GPU. Other types of models take an entire GPU when deployed. For details about other differences between model types, see Model functionality.

    The number of active GPU tasks (model training and deployment) that you can run at the same time depends on the number of GPUs on your server. You must verify that there are enough available GPUs on the system for the desired workload. The number of available GPUs is displayed on the user interface.

  • You cannot install IBM Visual Insights stand-alone on a system that already has any of these products installed:
    • IBM Data Science Experience (DSX)
    • IBM Cloud Private
    • IBM Watson Studio Local Edition
    • Any other Kubernetes based applications