Hello Autoresize Classification Sample

This topic describes how to run the Hello Autoresize Classification sample application. The sample is simplified version of Image Classification Sample. It's intended to demonstrate using of new input autoresize API of Inference Engine in applications. Refer to Integrate with customer application New Request API for details.

There is also new API introduced to crop a ROI object and set it as input without additional memory re-allocation. To properly demonstrate this new API it's required to run several networks in pipeline which is out of scope of this sample. Please refer to Object Detection for SSD Demo app or Security Barrier Camera Demo or Crossroad Camera Demo with an example of using of new crop ROI API.

Running

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

./hello_autoresize_classification <path_to_model>/alexnet_fp32.xml <path_to_image>/cat.bmp CPU

NOTE: Before running the sample with a trained model, make sure the model is converted to the Inference Engine format (*.xml + *.bin) using the Model Optimizer tool.

Outputs

The application outputs top-10 inference results.

See Also

• Using Inference Engine Samples