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See development workflow page for developer instructions.

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Here are some useful tutorial documents:

• LOOM - part 1 - intro to 360 cameras
• LOOM - part 2 - developing 3rd party LoomIO plug-ins

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Getting Started with Neural Networks Inference Sample Application with ROCm

Setup and run annInferenceServer

1. Recommended server configuration: EPYC(tm) processor with multiple Vega-based GPUs
2. Install Ubuntu 16.04 64-bit
3. Install ROCm from AMD repositories
4. amdovx-modules: Checkout, Build, and Install
5. Add /opt/rocm/bin to PATH environment variable
6. Add /opt/rocm/lib to LD_LIBRARY_PATH environment variable
7. Run /opt/rocm/bin/annInferenceServer

Setup and run annInferenceApp

1. Use another workstation for annInferenceApp
2. Build annInferenceApp
3. Run annInferenceApp
   • Connect to the server (use port 28282)
   • Upload CAFFE model (such as ResNet-50 for ImageNet)
     • Select .prototxt, .caffemodel, input dimensions, and other optional parameters
     • Click Upload & Compile
   • Run Inference
     • Select synset txt file with one name of each output label per line
     • Select input image folder (such as ImageNet validation data)
     • Click Run