This topic demonstrates how to run Super Resolution demo application, which reconstructs the high resolution image from the original low resolution one.
The corresponding pre-trained model is delivered with the product:
single-image-super-resolution-0034
, which is the primary and only model that performs super resolution 4x upscale on a 200x200 imageFor details on the model, please refer to the description in the deployment_tools/intel_models
folder of the OpenVINO™ toolkit installation directory.
On the start-up, the application reads command-line parameters and loads the specified network. After that, the application reads a 200x200 input image and performs 4x upscale using super resolution.
Running the application with the -h
option yields the following usage message:
Running the application with the empty list of options yields the usage message given above and an error message.
To run the demo, you can use public models or a pre-trained and optimized model delivered with the package:
<INSTAL_DIR>/deployment_tools/intel_models/single-image-super-resolution-0034
To do inference on CPU using a trained model, run the following command:
NOTE: Before running the sample with another trained model, make sure the model is converted to the Inference Engine format (*.xml + *.bin) using the Model Optimizer tool.
The application outputs a reconstructed high-resolution image and saves it in the current working directory as *.bmp
file with sr
prefix.