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program:object-detection-onnx-py (v1.1.1)
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Creation date: 2019-06-03
Source: GitHub
cID: b0ac08fe1d3c2615:4bc385394b7a9350

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Description  

This portable workflow is our attempt to provide a common CLI with Python JSON API and a JSON meta description to automatically detect or install required components (models, data sets, libraries, frameworks, tools), and then build, run, validate, benchmark and auto-tune the associated method (program) across diverse models, datasets, compilers, platforms and environments. Our on-going project is to make the onboarding process as simple as possible via this platform. Please check this CK white paper and don't hesitate to contact us if you have suggestions or feedback!
  • Automation framework: CK
  • Development repository: ck-mlperf
  • Source: GitHub
  • Available command lines:
    • ck run program:object-detection-onnx-py --cmd_key=default (META)
  • Support for host OS: any
  • Support for target OS: any
  • Tags: object-detection,onnx,lang-python
  • Template: Object Detection via TensorFlow (Python)
  • How to get the stable version via the client:
    pip install cbench
    cb download program:object-detection-onnx-py --version=1.1.1 --all
    ck run program:object-detection-onnx-py
  • How to get the development version:
    pip install ck
    ck pull repo:ck-mlperf
    ck run program:object-detection-onnx-py
  • CLI and Python API: module:program

    • Dependencies    

    ReadMe  

    TensorFlow object-detection program

    Pre-requisites

    Repositories

    $ ck pull repo:ck-mlperf

    ONNX libraries

    $ ck install package --tags=lib,onnx
$ ck install package --tags=lib,onnxruntime

    ONNX Object Detection model

    Install one or more object detection model package:

    $ ck install package --tags=model,object-detection,onnx

    Datasets

    $ ck install package --tags=dataset,object-detection,preprocessed,side.1200

    Running

    $ ck run program:object-detection-onnx-py

    Program parameters

    CK_BATCH_COUNT

    The number of images to be processed.

    Default: 1

    CK_SKIP_IMAGES

    The number of skipped images.

    Default: 0

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