DLR image classification model store - AWS IoT Greengrass

DLR image classification model store

The DLR image classification model store is a machine learning model component that contains pre-trained ResNet-50 models as Greengrass artifacts. The pre-trained models used in this component are fetched from the GluonCV Model Zoo and are compiled using SageMaker Neo Deep Learning Runtime.

The DLR image classification inference component uses this component as a dependency for the model source. To use a custom-trained DLR model, create a custom version of this model component, and include your custom model as a component artifact. You can use the recipe of this component as a template to create custom model components.

Note

The name of the DLR image classification model store component varies depending on its version. The component name for version 2.1.x and later versions is variant.DLR.ImageClassification.ModelStore. The component name for version 2.0.x is variant.ImageClassification.ModelStore.

Versions

This component has the following versions:

  • 2.1.x (variant.DLR.ImageClassification.ModelStore)

  • 2.0.x (variant.ImageClassification.ModelStore)

Type

This component is a generic component (aws.greengrass.generic). The Greengrass nucleus runs the component's lifecycle scripts.

For more information, see Component types.

Operating system

This component can be installed on core devices that run the following operating systems:

  • Linux

  • Windows

Requirements

This component has the following requirements:

  • On Greengrass core devices running Amazon Linux 2 or Ubuntu 18.04, GNU C Library (glibc) version 2.27 or later installed on the device.

  • On Armv7l devices, such as Raspberry Pi, dependencies for OpenCV-Python installed on the device. Run the following command to install the dependencies.

    sudo apt-get install libopenjp2-7 libilmbase23 libopenexr-dev libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libgtk-3-0 libwebp-dev
  • Raspberry Pi devices that run Raspberry Pi OS Bullseye must meet the following requirements:

    • NumPy 1.22.4 or later installed on the device. Raspberry Pi OS Bullseye includes an earlier version of NumPy, so you can run the following command to upgrade NumPy on the device.

      pip3 install --upgrade numpy
    • The legacy camera stack enabled on the device. Raspberry Pi OS Bullseye includes a new camera stack that is enabled by default and isn't compatible, so you must enable the legacy camera stack.

      To enable the legacy camera stack

      1. Run the following command to open the Raspberry Pi configuration tool.

        sudo raspi-config
      2. Select Interface Options.

      3. Select Legacy camera to enable the legacy camera stack.

      4. Reboot the Raspberry Pi.

Dependencies

When you deploy a component, AWS IoT Greengrass also deploys compatible versions of its dependencies. This means that you must meet the requirements for the component and all of its dependencies to successfully deploy the component. This section lists the dependencies for the released versions of this component and the semantic version constraints that define the component versions for each dependency. You can also view the dependencies for each version of the component in the AWS IoT Greengrass console. On the component details page, look for the Dependencies list.

2.1.7

The following table lists the dependencies for version 2.1.7 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.8.0 Soft
2.1.6

The following table lists the dependencies for version 2.1.6 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.7.0 Soft
2.1.5

The following table lists the dependencies for version 2.1.5 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.6.0 Soft
2.1.4

The following table lists the dependencies for version 2.1.4 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.5.0 Soft
2.1.3

The following table lists the dependencies for version 2.1.3 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.4.0 Soft
2.1.2

The following table lists the dependencies for version 2.1.2 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.3.0 Soft
2.1.1

The following table lists the dependencies for version 2.1.1 of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus >=2.0.0 <2.2.0 Soft
2.0.x

The following table lists the dependencies for version 2.0.x of this component.

Dependency Compatible versions Dependency type
Greengrass nucleus ~2.0.0 Soft

Configuration

This component doesn't have any configuration parameters.

Local log file

This component doesn't output logs.

Changelog

The following table describes the changes in each version of the component.

Version

Changes

2.1.7

Version updated for Greengrass nucleus version 2.7.0 release.

2.1.6

Version updated for Greengrass nucleus version 2.6.0 release.

2.1.5

New features
  • Adds sample image classification models for Windows core devices.

  • Version updated for Greengrass nucleus version 2.5.0 release.

2.1.4

Version updated for Greengrass nucleus version 2.4.0 release.

2.1.3

Version updated for Greengrass nucleus version 2.3.0 release.

2.1.2

Version updated for Greengrass nucleus version 2.2.0 release.

2.1.1

New features
  • Add a sample ResNet-50 image classification model for Armv8 (AArch64) platforms. This extends machine learning support for Greengrass core devices running NVIDIA Jetson, such as the Jetson Nano.

2.0.4

Initial version.