Object Identification & Animal Recognition With Raspberry Pi + OpenCV + Python

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Actively search and classify all kinds of household objects and common animals with a palm sized single board computer. Then use specific object detection to control GPIO pins.

Make sure to use the Previous Raspberry Pi 'Buster' OS with this Guide.

Related Information

Have you ever wanted to get your Raspberry Pi 4 Model B to actively search and identify common household objects and commonplace animals? Then you have found the right place. I'll show you exactly how to do this so you can set up a similar system in your own Maker-verse. Furthermore, I will demonstrate how you can refine the identification so it searches only for particular desired targets. Then we’ll take this to the next step and demonstrate how you can alter the code to make the Raspberry Pi control physical hardware when it identifies that particular target. This guide is going to blend machine learning and open-source software together with the Raspberry Pi ecosystem. One of the open-source software used here is Open-CV which is a huge resource that helps solve real-time computer vision and image processing problems. This will be a second foray into Open-CV landscape with Raspberry Pi and Facial Recognition being the first. We will also utilise an already trained library of objects and animals from the Coco Library. The Coco (Common Object in Context) Library is large-scale object detection, segmentation, and captioning dataset. This trained library is how the Raspberry Pi will know what certain objects and animals generally look like. You can also find pre-trained libraries for all manner of objects, creatures, sounds, and animals so if this particular library here does not suit your needs you can find many others freely accessible online. The library used here will enable our Raspberry Pi will be able to identify 91 unique objects/animals and provide a constantly updating confidence rating. Machine learning has never been more accessible and this video will demonstrate this.

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0:00 Intro
0:17 Video Overview
0:56 What You Will Need
1:30 Set Up
3:10 Grab Some Objects
3:35 Its Working!
4:02 Some Values Worth Tinkering
4:55 GPIO Control with Identified Objects
5:36 Acknowledgments
5:47 Outro

[mikerr]

This was the fastest, cleanest comprehensive guide I have found on OpenCV for Pi.
Only thing that would make this better would be an Install script, but even then I think its good for some manual work to be left anyways. Get peoples hands dirty and force them to explore and learn more.

So cool to have the power of machine learning and Computer Vision in our hands to explore and experiment with. What a time to be alive!

[stevenhillman]

Excellent. I came to this after seeing the facial recognition video as it would help with a project I have in mind. However, after seeing this and how easy it is to set up and use my project will be more ambitious. Thanks again and keep up the good work.

[jacksonpark]

this was exactly the thing i was looking for. i will be buying things from their store as compensation!

[thezmanner]

Amazing, Easy to follow, Comprehensive video for object detection. Gonna use this to turn my RC car into a autonomous vehicle.
Thanks Tim, Keep up the great work :D

[joelbay]

You're a life saviour. Thank you so much ❤

[stefanosbek]

Thanks for sharing, this is really good and easy to follow

[biancaar]

And a really big thanks to you for explaining this so well😁😁

[mark-iloo]

Your website, products and educational resources are amazing. I was wondering if you had any advice as to how to further train the machine to identify less common objects? I was hoping to use it for a drone video feed and train it to identify people, for basic search and rescue functions. I am a volunteer in my local community, hence my specific question :-)

[timjx]

Awesome vid, clear fast and accurate 🌟

[nishyu]

This is amazing ! this is soo very cool! Thank you for introducing me to coco!

[ngpsrmn]

Hi Tim, I would like to ask how can I speed up the fps and speed up the recognition rate? Or do I need to use the lite version to speed up the speed?

[ashanperera]

Thank you man! This was really helpful.

[marnierogers]

Hey this is great, thanks for putting this together. Really easy to follow along as a beginner. Is there a tutorial that builds on this and allows you to connect a speaker to the raspi so that whenever a specific object is detected, it makes a specific noise? Would love to see it!

[soulo]

Trust me . I just find everything I was looking for about my raspberry pi 🌹

[elvarzz]

Hey man great video. Any chance you can cover how to use this same concept to detect anomalies instead? Rather than looking for specific objects expected to be there in the camera, the program learns the objects expected to be there and detects when an unusual object is found. Thanks.

[bosss]

Hi Tim, the video was great btw do you know another dataset that i could use with this code, and can you explain how to train a new object to detect?

[_zsebtelep]

cool, but what would it take to make this work with 60 fps (doing the image recognition in every frame and not lagging behind when things move fast)

[suryanarayansanthakumar]

Hi Tim,
Thank you so much on this video for demonstrating how to use OpenCV with the Raspberry Pi.

I am willing to follow along your process to install OpenCV and test it out.

I am just wondering if OpenCV will run on the new Raspberry Pi OS

[maxxgraphix]

To use a USB cam install fswebcam then change cv2.VideoCapture(0) to cv2.VideoCapture(0, cv2.CAP_V4L2) in the script

[zakashii]

Hi.
I wanted to ask, do you think the raspberry pi Zero cam could be used as a substitute? I'm currently working on a project that involved Raspberry Pi's and camera's and have done a lot of research on what hardware to acquire, I haven't seen much benefit in using the V2 camera instead of the Zerocam. I actually think the raspberry pi zero cam has better specs for its price when compared to the V2.