Raspberry Pi LESSON 61: Finding and Tracking Faces and Eyes In OpenCV

Moving forward we will now want to move the camera (pan/tilt) in response to the movement of the object of interest. I do this using the Sunfounder pan/tilt hat. You can order the hat I am using at this affiliate amazon link:
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If you are able, I suggest you consider getting some spare servos for the pan tilt hat. During development if you are not careful, it is possible to damage a servo by crashing the camera into something. I like to keep a couple spares on hand:
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Announcing the Most Awesome Raspberry Pi Lessons of All Times! This time we RUMBLE!
In this class series, we will be using the most excellent Sunfounder Ultimate Raspberry Pi kit, available here: (Affiliate Link)
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or for our UK friends, amzn.to/3I5d401
In today's video I will show you how to find and track faces and eyes in openCV on the Raspberry Pi using Haar Cascades. I show how to find, track, and box the face and then the eyes.
If you want to grab those cool little straight jumper wires I am using to keep my breadboard builds neat and clean you can snag a box of them here:
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If you guys are interested in the oscilloscope I am using, you can pick one up here (affiliate link):
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You guys get your hardware ordered so you can follow along at home!
You will also need a Raspberry Pi. I suggest the Raspberry Pi 4. If you do not already have one, this is the most suitable gear I could find:
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The Raspberry Pi's are sort of pricy right now, so you can look on ebay or elsewhere to see if there are any deals. You will need a SD card. If you do not already have one, this is a good one:
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I like using a wireless keyboard and mouse to have fewer wires. You can certainly use your USB keyboard and mouse, but if you want a nice wireless one, this one works on the pi. We demonstrate this by using a button switch to control a LED.
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You guys can help me out over at Patreon, and that will help me keep my gear updated, and help me keep this quality content coming:
/ paulmcwhorter
#facerecognition
#opencv
#raspberrypi

[@christiansariol5018]

Thank you Paul! I need another lifetime to learn all you have to offer.

[@amarbakshi2839]

I am binge watching your videos..cant stop..

[@stephenlightkep1621]

Thanks Paul. I love it. Things are happening in that head of mine. I love your neighbors, to spend one day over there would be cool! Then the next two weeks in a hospital.

[@daveCotterill]

Great Lesson, many thanks Paul.

[@jameslewellen150]

Paul, you always make it seem easy. Nice video.

[@charlotteswift]

Most excellent lesson. Thanks, Paul

[@larryplatzek9017]

This was a most excellent video lesson, will be working on the homework this week!

[@alldaypancakes7058]

it all started when my teacher said you shold do robotics you know english almost no one knows english in this class and i write arduino lesons and i saw you and clickt it and sins then i been only lerning python raspberry pi fiusion 360 from you for 3 years

[@scottwait3585]

Thanks Paul!

[@maxpayne7302]

Hi! Its very hard to find any help for facial recognition on this new Bulleye OS. Could you please do a tutorial on training the Pi and the execution for facial recognition?

[@marioalbers887]

Hi thanks great lessons … has some combine the lessons of the security into one script …

[@aprilwoods8651]

Thankyou

[@Matcha-uv4mv]

Hi sir Paul! Good day! Your video is very helpful but I wonder if you can create a tutorial of drowsiness detection through eyes, mouth and head positioning using raspberry pi camera. Thank you!

[@charlotteswift]

Here is a video about Pan/Tilt Hats and a demo of my program written to help do the lessons : th-cam.com/video/BzjA3608XbI/w-d-xo.html

[@paulmcwhorter]

LEGEND!

[@qzorn4440]

Paul, this is getting most exciting. The Orange Pi5 running Lesson-61 "Faces & Eyes" is producing about {20-25 FPS} Htop: 8-cores= 71% 56-77 Degree_C, cooling is important! Wow, only one more lesson to do. This is really a good starting place for Computer Vision. The Orange Pi5 has a GPU and I would like to see what it will do? Just thought I would share the information.
Orange Pi 5B 16GB Rockchip RK3588S 8 Core 64 Bit WiFi6,BT5.0 SBCwith 128GB eMMC, 2.4GHz Frequency with 5V4A Type-C Supply Amazon $173.99
Also, the camera is an USB webcam with OpenCV (1280 X 720) frame size as in lesson 61. The RPi4 camera will not work on the OPi5. Thank you.
Amazon $20 USB WiFi Bluetooth Adapter, 1300Mbps Dual Band 2.4/5Ghz Wireless Network External Receiver, Mini WiFi Dongle for PC/Laptop/Desktop

[@keithlohmeyer]

Sounds interesting. I know many would love more details. You can't post links here but if you made your own vid you can put links in the description of where you found info on getting this up and running. Thanks

[@qzorn4440]

@@keithlohmeyer Hi. I left a comment with the Orange Pi5 Lesson-61 code. I was not sure what would be a good simple way to provide the information? The next thing to do is getting the OPi.GPIO PWM pins setup with no errors? Best regards.

[@qzorn4440]

@@keithlohmeyer Bummer. Well I thought I left the code? Today I do not see it? 🙈 Sorry.

[@DrDave327]

I am kicking myself that I didn't think of that opportunity to improve performance when doing my homework. Thanks for the exercise, Paul!!
I have one question, off topic: Do bananas taste better, sweeter, or any different if they are not picked until they are fully ripe? I have always wondered about that .

[@paulmcwhorter]

Yes, Bananas off the tree are MUCH sweeter than those in the grocery store. If you tasted one, you would say, Wow, I have never had a real banana before. In general all fruits are better here as they are picked ripe, not picked green and then ripen on the shelf.

[@jameslewellen150]

Here is my homework for this video. th-cam.com/video/XJZ6A3eQPYs/w-d-xo.html

[@paulmcwhorter]

LEGEND!

[@lukecipparrone210]

No