add info on the neural network

example_video_matting/README.md

 # Video Matting Example
-Realtime background substraction using MobileNetV3. Model provided by https://github.com/PeterL1n/RobustVideoMatting
+Realtime background substraction for video or webcam using MobileNetV3. 
+Model provided by https://github.com/PeterL1n/RobustVideoMatting
 
+Shout out to [Natxopedreira 2021](https://github.com/natxopedreira) for providing the initial example.
 
-Example made with love by Natxopedreira 2021  
-https://github.com/natxopedreira
+![](../media/video_matting.gif)
 
+### Notes
+Please check out the [official documentation](https://github.com/PeterL1n/RobustVideoMatting/blob/master/documentation/inference.md) for this model.
+
+Starting with the Turing architecture (e.g. RTX 2070), GPUs can utilize the FP16 data type and are therefore much faster!
+
+##### Choosing the downsample factor
+The table provides a general guideline. Please adjust based on your video content.
+
+| Resolution    | Portrait      | Full-Body      |
+| ------------- | ------------- | -------------- |
+| <= 512x512    | 1             | 1              |
+| 1280x720      | 0.375         | 0.6            |
+| 1920x1080     | 0.25          | 0.4            |
+| 3840x2160     | 0.125         | 0.2            |
+
+Internally, the model resizes down the input for stage 1. Then, it refines at high-resolution for stage 2.
+
+Set `downsample_ratio` so that the downsampled resolution is between 256 and 512. For example, for `1920x1080` input with `downsample_ratio=0.25`, the resized resolution `480x270` is between 256 and 512.
 
-![](../media/video_matting.gif)
 
 
 ### Other References

example_video_matting/src/ofApp.cpp

@@ -43,14 +43,21 @@ void ofApp::setup() {
 	};
 	model.setup(inputNames, outputNames);
 
+	// parameters for the neural network
+	float downsampleRatio = 0.25f;
+	float videoWidth = video.getWidth();
+	float videoHeight = video.getHeight();
+	float batchSize = 1.0f;
+	float numChannels = 3.0f;
+	
 	// model-specific inputs
 	inputs = {
-		cppflow::tensor({0.25f}),                        // downsample ratio
+		cppflow::tensor({downsampleRatio}),
 		cppflow::tensor({0.0f}),                         // r1i
 		cppflow::tensor({0.0f}),                         // r2i
 		cppflow::tensor({0.0f}),                         // r3i
 		cppflow::tensor({0.0f}),                         // r4i
-		cppflow::tensor({1.0f, nnHeight, nnWidth, 3.0f}) // src
+		cppflow::tensor({batchSize, videoHeight, videoWidth, numChannels})
 	};
 
 	imgMask.allocate(video.getWidth(), video.getHeight(), OF_IMAGE_GRAYSCALE);