openvino/inference-engine/samples/style_transfer_sample

Neural Style Transfer Sample

This topic demonstrates how to build and run the Neural Style Transfer sample (NST sample) application, which does inference using models of style transfer topology.

Running

Running the application with the -h option yields the following usage message:

./style_transfer_sample --help
InferenceEngine:
    API version ............ <version>
    Build .................. <number>

style_transfer_sample [OPTION]
Options:

    -h
                            Print a usage message.
    -i "<path1>" "<path2>"
                            Required. Path to a folder with images or path to an image files: a .ubyte file for LeNet
                            and a .bmp file for the other networks.
    -m "<path>"
                            Required. Path to an .xml file with a trained model.
        -l "<absolute_path>"
                            Optional. Absolute path to library with MKL-DNN (CPU) custom layers (*.so).
        Or
        -c "<absolute_path>"
                            Optional. Absolute path to clDNN (GPU) custom layers config (*.xml).
    -pp "<path>"
                            Path to a plugin folder.
    -p "<name>"
                            Plugin name. For example MKLDNNPlugin. If this parameter is pointed, the sample will look for this plugin only
    -d "<device>"
                            Specify the target device to infer on; CPU, GPU, FPGA or MYRIAD is acceptable. Sample will look for a suitable plugin for device specified
    -nt "<integer>"
                            Number of top results (default 10)
    -ni "<integer>"
                            Number of iterations (default 1)
    -pc
                            Enables per-layer performance report

Running the application with the empty list of options yields the usage message given above and an error message.

You can do inference on an image using a trained model of NST network on Intel® Processors using the following command:

./style_transfer_sample -i <path_to_image>/cat.bmp -m <path_to_model>/1_decoder_FP32.xml

Outputs

The application outputs an styled image(s) (out(1).bmp) which were redrawn in style of model which used for infer. Style of output images depend on models which use for sample.

See Also

• [Using Inference Engine Samples](@ref SamplesOverview)