An example of using OpenCV dnn module with YOLOv5. (ObjectDetection, Segmentation, Classification)
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EnoxSoftware 703ffecfa6 v1.0.5 Updated OpenCVForUnity version to 2.5.9. 2024-03-10 04:49:38 +09:00
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README.md
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README.md

YOLOv5 With OpenCVForUnity Example

Environment

  • Windows / Mac / Linux / WebGL / Android / iOS
  • Unity >= 2020.3.48f1+
  • Scripting backend MONO / IL2CPP
  • OpenCV for Unity 2.5.9+

Setup

  1. Download the latest release unitypackage. YOLOv5WithOpenCVForUnityExample.unitypackage
  2. Create a new project. (YOLOv5WithOpenCVForUnityExample)
  3. Import OpenCVForUnity.
  4. Import the YOLOv5WithOpenCVForUnityExample.unitypackage.
  5. Add the "Assets/YOLOv5WithOpenCVForUnityExample/*.unity" files to the "Scenes In Build" list in the "Build Settings" window.
  6. Build and Deploy.

Export YOLOv5 model to ONNX

  1. YOLOv5_export_to_OpenCVDNN_ONNX.ipynb
  2. YOLOv5_segment_export_to_OpenCVDNN_ONNX.ipynb
  3. YOLOv5_classify_export_to_OpenCVDNN_ONNX.ipynb

Works with Multi-Object Tracking (MOT)

  1. MultiObjectTrackingExample

ScreenShot

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Tutorials

  1. How to Train YOLO v5 on a Custom Dataset
  2. Example of custom training for dice roll detection