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mit-han-lab / tinyengine

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory
https://mcunet.mit.edu
MIT License
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person_detection and face_mask_detection #78

Open Super-Karl opened 1 year ago

Super-Karl commented 1 year ago

Hello, may I ask what are the hardware devices and models of the demo OpenMV Cam H7? I want to repeat that. Thank you very much!!

meenchen commented 1 year ago

Hi @Super-Karl,

Feel free to try our example demos on OpenMV Cam H7: https://github.com/mit-han-lab/tinyengine/tree/main/examples/openmv_person_detection https://github.com/mit-han-lab/tinyengine/tree/main/examples/openmv_vww

You can find the models here with the tflite format: https://github.com/mit-han-lab/tinyengine/tree/main/assets

Super-Karl commented 1 year ago

Hi @meenchen , Thank you for your reply, I want to ask about the specific model of the development board and the model of the display screen that is required to implement the above demo. I'm going to buy these hardware resources now, and I see that I may still need lithium batteries?

meenchen commented 1 year ago

Sure, please check out the following links:

https://openmv.io/products/openmv-cam-h7 https://openmv.io/products/lcd-shield https://www.digikey.com/en/products/detail/sparkfun-electronics/PRT-13851/6605199?utm_adgroup=Batteries%20Rechargeable%20%28Secondary%29&utm_source=google&utm_medium=cpc&utm_campaign=Shopping_Product_Battery%20Products&utm_term=&utm_content=Batteries%20Rechargeable%20%28Secondary%29&gclid=CjwKCAjwuqiiBhBtEiwATgvixCRDUClOIApdczfA13Es6Z2KNa57i1ctGeKnutDYb4yPZYfcTYDm2BoCg1AQAvD_BwE