Lots of ready-to-use opensource project can be found on internet for raspberry PI object detection. Most of them can do very well to motion detection or object classification. I am thinking how to merge them together to make a practical security system that can help all of us to make our home safety. Since It is open source, I will share my design, source code and project milestone. ( mostly to push myself to finish it eventually 🙂
Design:
- start camera to capture each frame
- save the first frame as reference. and this reference frame will be replaced every 5 mins when there is no movement detected.
- continuously compare the current frame with the reference frame.
- if any movement detected, draw some interesting areas.
- loop these interesting areas, if its size out of threshold, move it to next DNN network.
- use DNN network to classify the object.
- if object is human, trigger dedicated process “Event process”. includes, recording video, send notification and make speaker noise.
- loop to the next frame.
Milestone:
Oct 10th-15th: finish basic function to detect movement, recording video and send mail.
Oct 16th-22th: add DNN network
Oct 22th-30th: add speaker and integration test.
Potential update:
- GPU accelerate on Cuda device
- GUI
- restful API
Source:
https://github.com/neoaksa/raspiberry-security
Demo(till Oct 15th):
Reference:
Deep learning: How OpenCV’s blobFromImage works. https://www.pyimagesearch.com/2017/11/06/deep-learning-opencvs-blobfromimage-works/
Raspberry Pi: Deep learning object detection with OpenCV. https://www.pyimagesearch.com/2017/10/16/raspberry-pi-deep-learning-object-detection-with-opencv/
how to install opencv on the raspberry pi 3 Model b+ (with camera) https://pysource.com/2018/10/31/raspberry-pi-3-and-opencv-3-installation-tutorial/
Home surveillance and motion detection with the Raspberry Pi, Python, OpenCV, and Dropbox. https://www.pyimagesearch.com/2015/06/01/home-surveillance-and-motion-detection-with-the-raspberry-pi-python-and-opencv/
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