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[P] Experiment: 70fps real-time object detection with Google’s Coral Dev Board with Edge TPU

Maybe you have already heard of Google’s Coral Dev Board with Edge TPU and ask yourself how well it performs. We made a video to share our experience: https://youtu.be/bOYWx1jJCZo

In the video, we tested an object detection live stream under the following conditions:

– a pretrained MobileNet v2 model, trained on the common objects in context (coco) dataset

– a bounding boxes threshold of 45% confidence because there were way too many boxes displayed in the default configuration

– a camera connected via USB, not the official camera from Coral

We used this command to run the object detection server described above:

edgetpu_classify_server –source /dev/video1:YUY2:800×600:24/1 –model path/to/model/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite –labels path/to/labels/coco_labels.txt –threshold=0.45

You can find more demos to play around here:

https://coral.withgoogle.com/docs/dev-board/camera/

We hope this example helps you to get started with your own project!

If you have any idea, what we could build with it, let us know 🙂

Paul

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.