Hello NV12 Input Classification C Sample
This sample demonstrates how to execute an inference of image classification networks like AlexNet with images in NV12 color format using Synchronous Inference Request API.
Hello NV12 Input Classification C Sample demonstrates how to use the NV12 automatic input pre-processing API in your applications.
For more detailed information on how this sample works, check the dedicated article
Requirements
| Options | Values |
|---|---|
| Validated Models | alexnet |
| Model Format | Inference Engine Intermediate Representation (*.xml + *.bin), ONNX (*.onnx) |
| Validated images | An uncompressed image in the NV12 color format - *.yuv |
| Supported devices | All |
| Other language realization | C++ |
The following C++ API is used in the application:
| Feature | API | Description |
|---|---|---|
| Node Operations | ov_port_get_any_name |
Get a layer name |
| Infer Request Operations | ov_infer_request_set_tensor, |
Operate with tensors |
ov_infer_request_get_output_tensor_by_index |
||
| Preprocessing | ov_preprocess_input_tensor_info_set_color_format, |
Change the color format of the input data |
ov_preprocess_preprocess_steps_convert_element_type, |
||
ov_preprocess_preprocess_steps_convert_color |
Basic Inference Engine API is covered by Hello Classification C sample.