object detection and tracking on android Yolov8

aamir0011 commented 2 weeks ago

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Question

I want to do object detection and tracking on android. I am successful in object detection but i dont know how to do tracking please guide Thanks.

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github-actions[bot] commented 2 weeks ago

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pip install ultralytics

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glenn-jocher commented 2 weeks ago

@aamir0011 hello! It's great to hear you've successfully deployed YOLOv8 for object detection on Android. 😊 For object tracking, you can consider exporting the YOLO model to ONNX and using it with an Android-compatible inference framework like OpenCV DNN, which recently added support for ONNX models. Here's a simplified guide:

Export YOLOv8 model to ONNX format:

yolo export model=yolov8n.pt format=onnx

Integrate the ONNX model with OpenCV in your Android app. You'd need OpenCV Android SDK installed in your project. Here's a rough snippet on how you might load and use the model for inference:

// Load the ONNX model using OpenCV DNN
String modelPath = "path_to_your_model.onnx";
Net net = Dnn.readNetFromONNX(modelPath);

// Assuming 'frame' is your input image
Mat blob = Dnn.blobFromImage(frame, 1.0 / 255, new Size(640, 640), new Scalar(0, 0, 0), true, false);
net.setInput(blob);

// Forward pass
Mat detections = net.forward();

For tracking, post-process the detection outputs to maintain object identities across frames. You might need to implement or integrate a lightweight tracking algorithm suitable for mobile devices, such as SORT or a simple centroid-based tracker. Due to the complexity and additional computation, consider the performance and battery impact on the device.

While this approach simplifies the concept, actual implementation might require more steps, and performance optimizations, especially for real-time applications on Android devices.

Feel free to explore more and adjust based on your specific needs. Good luck with your project!

ultralytics / ultralytics