A picture says more than a thousand words. This is why the world is moving away from text to images and videos. We, as Makers, can profit from this movement because we get dirt cheap hardware to play with. And if it works with an ESP32, even better. Time for a closer look.
I am a proud Patreon of GreatScott, Electroboom, Electronoobs, and others.
In this video I will:
- Compare the features of the four boards
- Try to get all of them working. Here we will see that we have to overcome the usual obstacles
- Try to use the new class of I2S MEMS microphones presented in my last mailbag. Two of the modules have such a microphone included
- Try out two sorts of camera lenses
ESP-CAM: http://s.click.aliexpress.com/e/pdyJnZgU or http://bit.ly/2Zyo6cc
TTGO ESP32 camera Black: http://s.click.aliexpress.com/e/Enh3I63Q or http://bit.ly/2ZpSEMR
TTGO ESP32 camera White: http://s.click.aliexpress.com/e/FpeW9hHm or http://bit.ly/2ZkvRCp
TTGO T-Journal: http://bit.ly/2ZzlPgV
Different cameras http://bit.ly/2ZmJEYV
Sketches and overview: https://github.com/SensorsIot/ESP32-Cameras-and-MEMS-Microphones
All use the OV2640 camera and some I2S MEMS microphones
Supporting Material and Blog Page: http://www.sensorsiot.org
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The original idea for this site actually stemmed from another idea to provide a way of benchmarking the popularity of a video against the general population of YouTube videos. There are probably sites that do this by now, but there wasn’t when we started out. Anyway, in order to figure out how popular any one video is, you need a pretty large sample of videos to rank it against. The challenge is that the sample needs to be very random in order to properly rank a video and YouTube doesn’t appear to provide a way to obtain large numbers of random video IDs.
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