Hi !
Quick post today. And it’s mostly as a brain reminder on the best way to perform a Frames Per Second calculation when we are analyzing images using a ONNX model. In the final UWP app, I added a top right label displaying the current date and time, and the processed FPS
And the code behind all this is very simple, specially line 10
| private Stopwatch _stopwatch; | |
| private async Task LoadAndEvaluateModelAsync(VideoFrame videoFrame) | |
| { | |
| _stopwatch = Stopwatch.StartNew(); | |
| _predictions = await _objectDetection.PredictImageAsync(videoFrame); | |
| _stopwatch.Stop(); | |
| await Dispatcher.RunAsync(CoreDispatcherPriority.Normal, () => | |
| { | |
| var message = $"{DateTime.Now.ToLongTimeString()} – {1000f / _stopwatch.ElapsedMilliseconds,4:f1} fps"; | |
| TextBlockResults.Text = message; DrawFrames(); | |
| }); | |
| } |
So, I’ll search for my sample next time I need to display this.
The full app can be seen in https://github.com/elbruno/events/tree/master/2019%2001%2010%20CodeMash%20CustomVision/CSharp/CustomVisionMarvelConsole01
Happy Coding!
Greetings @ Burlington
El Bruno
References
- Custom Vision
- Quickstart: Create an image classification project with the Custom Vision .NET SDK
- Quickstart: Create an object detection project with the Custom Vision .NET SDK
- ONNX Documentation
- Sample application for ONNX1.2 models exported from Custom Vision Service
- Windows Community Toolkit
- Visual Studio Tools for AI
My Posts
- Object recognition with Custom Vision and ONNX in Windows applications using WinML (1)
- Object recognition with Custom Vision and ONNX in Windows applications using WinML (2)
- Object recognition with Custom Vision and ONNX in Windows applications using Windows ML, drawing frames (3)
Windows 10 and YOLOV2 for Object Detection Series
- Introduction to YoloV2 for object detection
- Create a basic Windows10 App and use YoloV2 in the camera for object detection
- Transform YoloV2 output analysis to C# classes and display them in frames
- Resize YoloV2 output to support multiple formats and process and display frames per second
- How to convert Tiny-YoloV3 model in CoreML format to ONNX and use it in a Windows 10 App
- Updated demo using Tiny YOLO V2 1.2, Windows 10 and YOLOV2 for Object Detection Series
- Alternatives to Yolo for object detection in ONNX format
25 thoughts on “#WinML – #CustomVision, object recognition using Onnx in Windows10, calculate FPS”