Merge Yolov5 with LSTM for Human Activity Recognition task

alina15andreeva commented 4 months ago

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Hello! I want to know if it is possible to somehow merge Yolov5 with LSTM for Human Activity Recognition task. Yolov5 should be trained to detect certain objects on the video and LSTM should be able to recognize an action being performed. I already have a trained LSTM model but I wish to increase the accuracy by introducing the presence of certain objects typical for certain kind of actions. Does anyone can help me with that? I am new to this and I am not sure how and whether this can be implemented at all.

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github-actions[bot] commented 4 months ago

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glenn-jocher commented 4 months ago

@alina15andreeva hello! 🌟

Absolutely, integrating YOLOv5 with an LSTM for Human Activity Recognition is a feasible and exciting approach. You can use YOLOv5 to detect objects in each frame of the video, and then feed the detection results (like object classes and possibly their bounding box coordinates) as a sequence into the LSTM to recognize actions over time.

Here's a simplified workflow:

Object Detection: Use YOLOv5 to detect objects in each frame.
Data Preparation: Prepare the detection results in a format suitable for the LSTM. This might involve encoding the detected objects and their properties into a numerical format.
Action Recognition: Feed the prepared data into your LSTM to classify the action.

For integrating these components, you might need to write custom code that bridges the output of YOLOv5 with the input requirements of your LSTM model.

Remember, the key to success in such a project is experimentation. Try different ways of representing the YOLOv5 detections for the LSTM, and see what works best for your specific use case.

For more details on using YOLOv5, you can always refer to our documentation at https://docs.ultralytics.com/yolov5/.

Best of luck with your project, and feel free to reach out if you have more questions! 🚀

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