This demo demonstrates an example of using neural networks to colorize a video. You can use the following models with the demo:
colorization-v2
colorization-v2-norebal
For more information about the pre-trained models, refer to the model documentation.
On the start-up, the application reads command line parameters and loads one network to the Inference Engine for execution.
Having received the image, the program: 1) converts the frame of video into LAB color space 2) uses the L-channel to predict A and B channels 3) restores the image, by converting it into BGR color space
Running the application with the -h
option yields the following usage message:
To run the demo, you can use public or pre-trained models. To download the pre-trained models, use the OpenVINO Model Downloader or go to https://download.01.org/opencv/.
NOTE: Before running the demo with a trained model, make sure the model is converted to the Inference Engine format (*.xml + *.bin) using the Model Optimizer tool.
The demo uses OpenCV to display the colorized frame.