README.md

annInferenceApp

This Sample Inference Application supports:

• connect to annInferenceServer
  • queries number of GPUs on the server
  • queries pre-loaded neural network models on the server
• upload pre-trained CAFFE models (optional)
  • specify input width and height dimensions
  • browse and pick deploy.prototxt and weights.caffemodel files
  • specify input preprocesor values for normalization (if needed)
  • specify input channel order (RGB or BGR)
  • optionally, you can publish your neural network for use by others
    • select "PublishAs"
    • give a name to your model
    • type password (default passowrd of annInferenceServer is "radeon")
• pick a CNN model, if upload option is not used
• run inference on images from a folder
  • browse and pick labels (i.e., synset words for each output label)
  • browse and pick input images to be classified
  • optionally, pick list of input images from a .txt or .csv file
  • optionally, specify max number of images to be processed from folder or image list

If you want to run a simple test, use annInferenceApp.py (a python script) to simply pick a network model to classify local images.

% python annInferenceApp.py [-v] -host:<hostname> -port:<port> -model:<modelName>
                            [-synset:<synset.txt>] [-output:<output.csv>]
                            <folder>|<file(s)>