Object Identification & Animal Recognition With Raspberry Pi + OpenCV + Python
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Article with All Steps - core-electronics.com.au/tutor...
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
Backyard BirdCam Project (Amazing Project that utilises this exact technology) - core-electronics.com.au/proje...
Flashing 'Buster' OS onto a Raspberry Pi - core-electronics.com.au/tutor...
Facial Recognition with the Raspberry Pi - core-electronics.com.au/tutor...
Face and Movement Tracking System For Raspberry Pi - core-electronics.com.au/tutor...
Controlling a Servo Motor with a Raspberry Pi - core-electronics.com.au/tutor...
Speed Camera with Raspberry Pi - core-electronics.com.au/tutor...
Hand Tracking & Gesture Control With Raspberry Pi - core-electronics.com.au/tutor...
Control Your Raspberry Pi Remotely Using Your Phone (RaspController Guide) - core-electronics.com.au/tutor...
Coco Dataset Library - cocodataset.org/#home
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.
If you have any questions about this content or want to share a project you're working on head over to our maker forum, we are full time makers and here to help - coreelec.io/forum
Core Electronics is located in the heart of Newcastle, Australia. We're powered by makers, for makers. Drop by if you are looking for:
Raspberry Pi 4 Model B (4GB) Ultimate Kit Bundle (AVALIABLE!) - core-electronics.com.au/raspb...
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Raspberry Pi High Quality Camera (Used Here): core-electronics.com.au/catal...
Raspberry Pi 6mm Wide Angle Camera Lens (Used Here): core-electronics.com.au/catal...
Raspberry Pi Official Camera Module V2 : core-electronics.com.au/catal...
Makeblock 9g Micro Servo Pack (used here): core-electronics.com.au/catal...
Raspberry Pi 4 Power Supply: core-electronics.com.au/catal...
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
![ตรงที่เดิม - ฝน พรสุดา [ต้นฉบับ :เบส ขวางหวัน]](http://i.ytimg.com/vi/c5YnbGEztI8/mqdefault.jpg)
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.
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!
Very glad you have your system all up and running 🙂 and I absolutely agree. Something about a machine learned system that runs on a palm-sized computer that you have put together yourself really feels like magic ✨✨
this was exactly the thing i was looking for. i will be buying things from their store as compensation!
Thank you very much for your work!
Just perfect, thanks a lot man!
And a really big thanks to you for explaining this so well😁😁
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 :-)
Thanks for sharing, this is really good and easy to follow
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?
You're a life saviour. Thank you so much ❤
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
Oh man that sounds like an amazing project 😊! Definitely keep me posted on how it goes. The Forum is a great place for a worklog - forum.core-electronics.com.au/
brother i too am working on this project can you leave any leads i am sending you an email if you have time please reply
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?
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!
Such a good idea. Yet to find a project talk about it directly, but where I added the extra code in for the Servo control if you instead replace that with code to set up a speaker and activate it, you would be off to the races.
Here is a related guide on speakers - core-electronics.com.au/tutorials/how-to-use-speakers-and-amplifiers-with-your-project.html
@@Core-Electronics Supertar, thanks!
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.
Thank you man! This was really helpful.
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
At this current stage I would recommend using the older 'Buster' OS with this guide. If you want to use Bullseye with machine scripts come check this guide on the OAK-D Lite - core-electronics.com.au/guides/raspberry-pi/oak-d-lite-raspberry-pi/
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.
Should work perfectly fine 😊. If the video data is coming into the Raspberry Pi through the ribbon cable I don't think you would even need to change anything in the script.
This is amazing ! this is soo very cool! Thank you for introducing me to coco!
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)
Trust me . I just find everything I was looking for about my raspberry pi 🌹
Great video, thank you for sharing.
do you have any guides for using an ultra low light camera module such as Arducam B0333 camera module (Sony Starvis IMX462 sensor)
Hey tim! I successfully have managed to run this project in about an hour. I didn't compile opencv from source though. I installed it through pip but still got it working and its running pretty smooth. Hope you could change the opencv compiling part as it takes tooo long (took me 3 days and was still unsuccessful)and is unnecessary. Thank you
I have used the raspberry 3b+
If you use raspberry pi 4, it could be much faster and smoother
If you can provide some more information I'd happily update the guides 😊 (Perhaps jump onto our core electronics forum and do a quick write up on your process)
Hello, great video but how do I get the coordinates of the tracked objects I am trying to build a robot that can identify and pick up objects, how would I find the coordinates
Great video, I just came up with an idea for a project using this. I have no experience with Pi's but basically it would be using a camera to detect a squirrel on a bird feeder and then playing some loud noise through a speaker. Would this be a difficult thing to do?
Sounds like an absolutely excellent idea that could definitely be implemented using this kind of Object Detection. We just had a new project posted on our website worth checking out all about using a Raspberry Pi to track Kangaroos and when it does it sends photos of them to a website server - core-electronics.com.au/projects/rooberry-pi
Thanks for this. I want to use my pi to do custom recognition of trees from their bark in a portable field unit. I already tried an tensorflow lite and off the shelf database to do common object recognition.
If I had a small need to recognize say 50 trees, how many labelled images do I need of each tree for the training data?
Hi Charles, some Australian scientists concluded in a 2020 paper “How many images do I need?” (Saleh Shahinfar, et al) that the minimum number of data points for a class should be in the 150 - 500 range. So if you had 50 species of trees to identify from you'd need roughly between 7,500 - 25,000 images/data points.
@@Core-Electronics thanks so much for this info. I have to get to work! I’m checking out the paper.
Hi Great Video! I know this may be unrelated but how about recognition of objects on screen without a camera? Is there any projects you know of that use AI detection to control the cursor of the computer when it detects an object on screen? Cheers
Cheers mate and excellent ideas. You can definitely feed this system data that has been pre-recorded or streamed in from another location, would require some adjustments to the script. Also in regards to AI detection to control a cursor on a Raspberry Pi come have a look at this video - th-cam.com/video/hLMfcGKXhPM/w-d-xo.html
You are a legend bro
i have a question what if when it detects particular image in my case (garbage) it has to generate a gps location or it has to send the location of that point to another vehicle like you did to your servo motor
To use a USB cam install fswebcam then change cv2.VideoCapture(0) to cv2.VideoCapture(0, cv2.CAP_V4L2) in the script
I have a imx219 apparently it will not work with opencv. Is there a way to use gstreamer to make it work in open cv?
I got error
Traceback (most recent call last):
File "", line 35
cv2.putText(img,classNames[classId-1].upper(),(box[0] 10,box[1] 30),
SyntaxError: invalid syntax
What mean with this error, i already install cv2
hi awesome video and great content, pls can I also get this same code to identify FIRE ? can you guide me to how i can do that.
also can i get the trained dataset for Fire and how do i get the library into the folder
instead of raspberry pi 4 can we use a raspberry pi zero 2w if the speed doesn't matter to me?
Hi great videos! How do I add to the dataset, is there a file to add to or is it an adjustment in the code Thanks again
Great video! I’m wondering if instead of the green rectangle with the name of the object, I can get the names of the objects into a string so I can print. I am trying to use a Text To Speech software so that whatever the object’s name, it is said out loud. Do you have any tips, help, or advice to give me?
Definitely something you can do! Theres a lot of great text to speech packages that will work with Raspberry Pi, Pico TTS is a great example of one. With a little bit code adjustment you'll be off to the races.
Come make a forum post (link in description) on your idea and then we can give you a much better hand than I can here 😊
@Niseem Bhattacharya Did you figure out how to do that? I need help with it.
Lost two nights trying to run it on the latest OS! Use the previous one, it is mentioned in the article.
thank you, I was struggling with this and was utterly confused.
Ty for a great video
Where could i found library for specific stuff i need?
I am looking for Cans, Bottles, glass bottles etc
Hello, did you ever find a library of the things you needed? I also need a library for specific items and was wondering if you found a good resource.
i did not
made myself a model by training it using Roboflow
@@kos309
This video helped a lot! 👍
Sweet! 😊
great video! good for beginner.
I want to get the name of the objects into a string and print it when object detected.
Can you give me any tips or help to me? Thank you so much.
Cheers mate! In the main script underneath the line | result, objectInfo = getObjects(img,0.45,0.2) | is another line stating | #print(objectInfo) |. If you delete that | # | then save and run it again you will be printing the name of the identified object to the shell script.
Hope that helps 😊
Amazing , thank you !
Our pleasure!😊😊
Hi is there a way that then creates a log with all recognized animals/humans so data can be consumed ?
Hey tim! Here's a question, Is the model trained by your coco generated by the yolo algorithm? This is related to the writing of my graduation thesis. I will be more grateful if you can provide more suggestions.
Sorry for getting to this so late. A lot can be learned here - cocodataset.org/ . Also there are a ton of research papers as people are unraveling this technology that are worth exploring (or adding to the bottom of a graduation thesis). Good luck mate!
@@Core-Electronics thanks so much！I believe that with your help I can get a high score.best wish！
very good video and explanations are well detailed. please I have a project that consists of detecting paper your technique works with other objects but does not work with paper. I don't know if it's possible to teach the system to recognize paper. Thank you
Edge Impulse is your friend here - www.edgeimpulse.com/
This will let you customise already created AI systems like the CoCo Library. Stepping through this system you will be able to modify CoCo library to recognise paper 😊
Hi this was a really great project and helped me a lot but can you help in how can we change the size of the box made around our object?
Size of the boxes tend to be based on the size of the detected object. But the Colour and Width of box can definitely be altered. Inside the code look for the section | if (draw): |
Then below that the line | cv2.rectangle(img,box,color=(0,255,0),thickness=2) |
By altering the (0,255,0) numbers you can change the colour of the box. By changing the thickness number you can have very thin lines or very bold lines. Font and other aesthetic changes can be done in the following lines.
@@Core-Electronics Thank you very much
Can I run your project on MacBook if possible and in this case what kind of modifications to have with hardware please. Thanks
Excuse me, i need help please, tiny yolo is better to raspberry pi or normal yolo can be used?
Amazing sir how can add speak module beacause easily to understand to detect of any object and after to speak a text in any objects
I wanted to apply this for feedback system for blind can it be adjusted on the cap
hey tim ! i seem to encounter a problem while following your instructions on the make -j $(nproc) it stops every time on the 40% and i re-typed and entered the same line several times but it didnt work is there any solution thanks for answering
Check the description for the article page. Scroll down to the questions section and you'll find the answer
Hi Great video! can I use a usb webcam instead of the pi cam, is it just a case of changing the code
Will I be able to add an entire category to the list of objects to be displayed in real-time? So instead of saying ['horse'], could I possibly mention a broader category of ['animal'] in the objects parameter? If not, please do let me know the correct way to approach this.
The fastest way would be to just add a long list like ['horse', 'dog', 'elephant'] etc. If you check the full-write up I do something very similar there.
Hi tim, how to add gTTS in the program when the object is detected
great video, big help for my thesis. it can be used also to the pest?
Glad to be of help 🙂 not quite sure what you mean though.
For anyone it might help out later. I followed the commands on the guide verbatim and was having issues on the, "cmake -D CMAKE_BUILD_TYPE=RELEASE \" and 4 following commands that are all grouped together. I was using, "Right click highlighted text - copy, from the web page and CTRL+Shift+V paste to Terminal to input commands. And that worked great for most of the commands but doesn't appear to work for that last paragraph. I had to manually type it in myself in order for it to work correctly.
Tim if you do read this, first of all thanks. But I am a tad lost on exactly when to change back the CONF_SWAPSIZE to 100. I assume after the installation is fully complete but to some of us noobs, its a bit unclear I guess. Also, don't know exactly why, but it says that, "sudo pip3 install numpy" already had its bits installed to Buster so it "might" be redundant. Unless its more of a full proof guild for other versions of the OS.
Finally able to finish up my project! Once this finishes installing...
:P
Cheers for this write up mate 🙂 I'll legit jump into the guide and make it a little clearer when to swap back the CONF_SWAPSIZE. I'll make it more similar to what I have in my Face Recognition written up guide. My intention is to 'Noob proof' it as best as I can so everyone can have Open-Source Machine learned systems in the palm of their hands that they've created themselves.
Very glad you now have it all up and running too!
@@Core-Electronics I didn't think to check your guild on the other OpenCV videos. I'll go do that now. Finally have the next 2 days off so I can fully jump into it.
I got past this issue, but now when I run the script its having issues no one else in the forums had. I assume this was due to some issues I may have made when trying to get the multi line command working. Idk so lost with all of this lol.
I'm good with Arduino, but Raz Pi, Linux, console commands and scripts vs coding. So much to learn at once. You are such a huge help while lost and overwhelmed in this new little world.
hi, this tutorial helped a lot for my project. i successfully set up and run the codes on raspberry 4 model b terminal, i just couldn't figure out how can i see the video output while the code is running on the terminal (not on geany or thonny). maybe u could help me out :>>
Not quite sure why it wouldn't do that for you when you run the script in the terminal. Come write up a post here at our forum and post some pictures of the situation - forum.core-electronics.com.au/. Reference in the post me and I'll best be able to help 😊
Hi, Tim.
I am using your source for my object detection project! Thank you so much!
But, I have a question about delay. So, there seems like about 10 seconds delay in real-time. Is there any way to reduce that delay, such as “decreasing frame rate”, or “reducing the number of images read every second”? I am trying to find where I can adjust those in the code, but it seems hard to do so. Thank you so much!
Awesome! 10 seconds is a very long time though, what hardware are you using? Software wise by limiting the objects it searching for I have found it to increase speed, also deep in code you can find locations to lower camera resolution which will help too.
@@Core-Electronics Thank you for your reply!
So, I am using "Raspberry Pi" and "Logitech C930e 1080P HD Video Webcam" for camera.
I tried limiting the objects it searching, but it didn't help because it anyways detected objects even though the bounding boxes are not displayed in the video.
And I think I am using 640 x 480 resolution, then do I just manually change it to smaller scale?
except those two methods above (limiting objects it searching for, lowering camera resolution), are there any other ways to reduce the delay time? such as "changing FRAME RATE?" or "reducing the number images per second"?
Thank you so much for your help.
-Kyung
Hi did you succeed in lowering your delay?
@@xyliusdominicibayan6215 Hey, I couldn’t reduce delay. My project was done last year, but I just used my laptop instead of Raspberry Pi. If I had more time to fix it, I would have tried to lower the delay using Pi.
@@kyungpark5258 did you find a solution to your problem? I have the same problem also
This is really cool. I wonder how hard it would be to connect to a thermal imaging camera and identify things by body heat?
Sounds like an awesome project, let us know if you manage to get it working.
Also as inspiration check out what this man managed to do with a Pico and a thermal camera! (if only he shared his code) - th-cam.com/video/xO4RsO3nBZ8/w-d-xo.html
Thanks for the tutorial. Can you maybe show how to implement a new library? I want it to just detect If there is an animal, the kind doesnt matter.
I've been learning more about this recently. A great way to create custom libraries that a Raspberry Pi can then implement is through Edge Impulse. With this you will be able to train and expand the amount of Animals that default COCO library comes with. Tutorials on this hopefully soon. www.edgeimpulse.com/
@@Core-Electronics Hi Do you have tutorials for Custom Object Detection using your own model?
Hello I am trying to create a design that will recognize different trash types. Does this image recognition able to perceive things like cardboard, paper, tissue, or silver foil as such? like trash items?
Hey Max, Im currently working on a very similar project. My workshop can get a bit messy so I am setting it up to scream at me when it gets untidy. I will report back to you how it goes, or if you've had some luck I'd be more than interested.
Cheers!
Hi Tim, can the coral accelerator be integrated in this project?
Absolutely
hey time ! i seem to encounter a problem while following your instructions on the "cmake -D CMAKE_BUILD_TYPE=RELEASE \
"
i was getting the error :
" CMake Warning:
No source or binary directory provided. Both will be assumed to be the
same as the current working directory, but note that this warning will
become a fatal error in future CMake releases.
CMake Error: The source directory "/home/pi/opencv/build" does not appear to contain CMakeLists.txt.
Specify --help for usage, or press the help button on the CMake GUI. "
how do i resolve this ? i tried typing it manually and apparently it still didnt work
Heyya mate,
Sounds like a stray command line that didn't get typed in or using 'Bullseye' instead of 'Buster' Raspberry Pi OS. Jump to the comment section of the Article and that will have successful troubleshooting that will help you. If you still run into issues write up a message there with some screenshots of the problem and I'll make sure you get it running 😊
@@Core-Electronics Quick question, does that mean the OS needs to run this project is Raspbian 'Buster'? Not Bullseye? Would this also work for Ubuntu?
I love your videos btw, I've been following it ever since I become a hobbyist for Rpi
Definitely utilise 'Buster' Raspberry Pi OS for this guide. If you work hard at it you'll be able to get Machine Learnt Systems to work on Ubuntu, but the process will be different than what is outlined in the above video.
And big thanks 😊 Raspberry Pi Single Board Computers are really rad.
Can I use a normal usb camera with this?
Hey great video, May I know where to tinker if i will be using esp32 camera to stream the video? Thank you in advance!
Hey mate cheers 🙂 the line to alter in code is | cap = cv2.VideoCapture(0) | changing that 0 to another index number that will represent your esp32 camera stream. Come make a forum post if you need any extra hand.
@@Core-Electronics Hi would like to some extra hands on this one. How can I implement esp32 cam as my video stream for real time object detection using the code. Thankss!
Definitely a great question for our Core Electronics Forum 😊
Hi, thank you for the explanation and code. I tried the code with the V3 HD camera, but it didn't work. Additionally, can you tell me how to create an autostart for this design? The 5 ways to autostart don't work ("Output:957): Gtk-WARNING **: 19:31:41.632: cannot open display:"). I'm sending a relay with it to keep the chickens away from the terrace with a water jet. Beautiful design! Greetings, Luc.
Hey Luc,
To start you will need to update a new driver for the V3 Camera so it can work with the older 'Buster' Raspberry Pi OS. Check out how to do it here - forum.arducam.com/t/16mp-autofocus-raspbian-buster-no-camera-available/2464 -
And if you want to autostart your system come check out how here (I would use CronTab) - www.tomshardware.com/how-to/run-script-at-boot-raspberry-pi
Come pop to our forum if you need any more help 😊 forum.core-electronics.com.au/latest
Kind regards,
Tim
Tengo ese error no me coge el codigo
Traceback (última llamada más reciente): Archivo "/home/pi/Desktop/Object_Detection_Files/object-ident.py", línea 15, en net = cv2.dnn_DetectionModel(weightsPath,configPath) AttributeError: module 'cv2.cv2' no tiene atributo 'dnn_DetectionModel'
You're the most closet project of my idea in fact it's practically that.
But I would like to run it 7/24 during a 10 day period ( my holiday)
I would like it press a button 10 minutes after each time it identify a cat (mine) and nothing else :
Here is a cat :
wait 10 minute
press the smart button ( I looking for a way to flush the toilet each time after my cats have done their needs )
is this possible/faisable with this?
Definitely possible and an excellent project to eliminate a chore 😊 or make for an even more in-dependent kitty. The Coco Library used in this guide has | Cat | as one of the animals it can identify. And Raspberry Pi's are excellent at running 24/7. So I reckon your in for a project winner.
If you follow through the Full Write up you'll be able to have a system that can Identify Cats (and only cats). That the hard bit done. Solenoids are a way to trigger the button, check this guide for the process on getting one to run with Raspberry Pi - core-electronics.com.au/guides/solenoid-control-with-raspberry-pi-relay/
Nicely explain. Please do I apply this on new dataset different from this?
It will require some dedicated effort but you can customise this object detection dataset using edge impulse. www.edgeimpulse.com/
That way you can add whatever object or creature you'd like 😊 I hope I understood correctly.
How do you transfer a data set to the pi do you store it in a file or does it need adding to the code.
can i use webcam logitech c310?
hi good sir can i use 0v7670 camera for this program?
I am getting cv2.imshow error while running object-ident.py in pi terminal, I connected pi via ssh. What should I do?
Very clever doing it through SSH 😊. It shouldn't be an issue doing it that way so long as you go through all the set up process. If you come write me a message on the core electronics forum under this topic I'll best be able to help you. That way you can sent through screen grabs of your terminal command errors.
ohhh man where are , i spent a week trying to install lib's thank u sooooo much
Hi, I keep getting that error message at 41% on the make-j $(nproc). no matter how many times i reenter the command it wont progress. any help?
thank youu veryy muchh🙇
❤😍
just dowload and extract this zip file. trust me
Does it work ?
How can I fuse this code with the face recognition one?
does this work with raspberry pi bullseye os?
I am currently trying to follow this on a pi 4b with Bullseye. I am really struggling to get the files to download and build properly, any tips?
Check the article G you'll see it in the description
Great video! Can you run this portable on a battery not connected to the internet?
All the processing is done on the edge, thus you only need the hardware (no calculations happen over Wifi or via the Cloud). So if you had a big enough battery you could definitely run this system via a battery without Internet 😊.
Thanks for the quick reply!
Will this work on an Orange Pi5? Raspberry Pi's are out of stock everywhere except from scalpers charging five times normal.
I'm not sure honestly mate, if you can get it to run 'Buster' Raspberry Pi OS then I'll give it a solid positive maybe.
Hello can it be possible if you can join the animal, object and person or facial recognition at the same time? I'm working that kind of project could you help me sir? Please...
Aww what an excellent idea! You will start wanting more powerful hardware very quickly going down this path. Come check out the Oak-D Lite (which is an excellent way to start stacking multiple AI system whilst still using a Raspberry Pi) - th-cam.com/video/7BkHcJu57Cg/w-d-xo.html
@@Core-Electronics how about just identifying if it is an animal, things or a person or some kind of moving object and at the same time it will capture a preview picture of it? How can you make this? and also how to create like if the raspberry pi detects a person in can email to you but if it is not a person it will not email you. Hoping you can help me with my research
hi, i am using raspberry pi 3 model B+ in this project. I uploaded the codes and was successful. But there is a delay of 8-10 seconds and it detects an object many times. You mentioned in the forum that we can reduce the latency by lowering the camera resolution. I can't find where to set this setting, can you help me? (I am using raspberry pi camera module v2 as camera.)
Sure mate, lower the values you find in the line here | net.setInputSize(320,320) |. Make sure both numbers are matching. Most AI Vision systems depend on the inputted video data to be square. If you type | net.setInputSize(160,160) | it will yield faster responses.
@@Core-Electronics The image became faster, but object recognition worsened. It draws the boundaries in different parts of the object. Thanks for your reply.
I hadn't realised it would do that, without a doubt there is some code lines in there that when adjusted would fix up the boundary boxes.
@@Core-Electronics any update with this issue?
can you make a tutorial on how to install the packages sir?
Would this program be able to email somebody about what object is seeing, like instead of turning the servo email somebody?
Absolutely! Here is a straight forward code to send an email through a Python Script. If you merge those two lands together you'll be smooth sailing - raspberrypi-guide.github.io/programming/send-email-notifications#:~:text=Sending%20an%20email%20from%20Python,-Okay%20now%20we&text=import%20yagmail%20%23%20start%20a%20connection,(%22Email%20sent!%22)
Hi,
Can I execute this project with a Raspberry Pi 3 A+ ?
You definitely can, it will just run a little bit slower.
I want to get output when alghoritm recognize an animal. I want to send this output to firebase. What am i suppose to do ?
I wanted to use for custom data set but how to train
Hello, tried this on my raspberry pi 3b+. Im using camera module v2. I can't see the camwra in the raspberry pi configuration. Any ideas how to fix it? Or i can use a webcam as alternative? Pls i need your reply
You have the right OS? Buster?
Hello
I'm verry happy to see this tuto
Thank for help
Is it possible to detect drugs or pills ?
For sure but you will need to create a custom Machine Learnt Edge system. Come check out Edge Impulse, personally I think they are the best in the game for this kind of stuff (and totally free for a maker) - www.edgeimpulse.com/
Can you do this with your own dataset and if so how? Need it for a school project. Thank you to whoever answers.
Yes you can but you have to train your dataset. Watch some other tutorials on how to train dataset.
@@arafatsiam4060 Will a dataset made from TensorFlow lite work? Or is there a different one compatible with the program?
Hi, currently completing the installation code for The Long Way to Set Up OpenCV and Facial Recognition
And I am receiving the following error:
"CMake error The current CMakeCache.txt directory /home/pi/opencv/CMakeCache.txt is different than the directory /home/pi/opencv/build where CMakecche.txt was created. This may result in binaries being created in the wrong place. If you are not sure, reedit the CMakeCache.
How should I complete this step, and get CMake to properly install on my Raspberry pi?
Heyya buddy, if your able to continue the installation then do so. Otherwise type and enter the line | sudo rm /home/pi/opencv/CMakeCache.txt | and then retype the line you got stuck on.
I am sure I can make this whole installation process much easier, will spend some of today figuring it out - will link here if I get it working.
@@Core-ElectronicsWe were able to get all of the CMD lines to run, but are now dealing with a new issue. When running the object-ident.py file in Thonny it is producing the following error:
%Run object-ident.py
Traceback (most recent call last):
File "/home/pi/Desktop/Object_Detection_Files/object-ident.py", line 1, in
import cv2
ModuleNotFoundError: No module named 'cv2'
We think it is because our RPI is running version 2.7.16 and are troubleshooting do you have any tips on how to solve this?
I feel like it should be working at this point if you went through all the commands. Just as a quick double check did you do the last two terminal commands after the | make -j $(nproc) |? This will give the system its much-needed restart.
sudo make install && sudo ldconfig
sudo reboot
(Also working right now on that better method, fingers crossed I can make the whole process easier and faster + jump onto the article page to see other troubleshooting solutions at the bottom of the page)
@@Core-Electronics I turned on my RPI and tried typing those commands into the terminal.
New Error: "make: ''' No rule to make target "install". Stop."
I also tried re-entering the "make -j $(nproc)" line which produced this error: "make: ''' No targets specified and no makefile found. Stop."
Should I retry from the start? I can reformat the card and try again if necessary.
I appreciate your help!
Sorry for leaving you stranded. I believe this all comes down to the new Raspberry Pi OS update 'Bullseye' which has removed support for the old Camera system. The team at Open-CV will eventually iron out these compatibility issues, I'm sure they're working frantically.
If you flash and utilise the old ' Buster' OS you will be up and running with this Facial Recognition system. Official Link to this OS here - downloads.raspberrypi.org/raspios_armhf/images/raspios_armhf-2021-05-28/
Weird question, how did you manage to record the Raspberry Pi screen so smoothly. I am a fellow content creator not as big as you haha and I don't know any good Raspian software that does this
Well spotted, there's no decent way to screen record a Pi internally without a terrible framerate. We run our Raspberry Pi through an Elgato capture card, just like you would capture gameplay footage from a console.
Good to know, will be buying one today. Thanks@@Core-Electronics
how much time it will take after make -j $(nproc). Because on my side, after 3 hour my system reboot automatically. Help me out in this situation
3 Hours is definitely too long for installation! Come jump into the full written up article. At the bottom is a whole bunch of successful troubleshooting that you utilise.
@@Core-Electronics Thanks for Reply. I did that successfully. Thanks for your help.
One more thing, I want to connect multiple camera with Raspberry pi via GPIO. Is it possible? Can you help me in that?
oop last question sirs, can you use any type of type c and power supply cable for raspberry??
You may be able to run a Pi with other power supplies but it's recommended to use the official Raspberry Pi Power Supply. They actually provide 5.1V to prevent issues from voltage drop that you might run into with a generic power supply.
Hii I'm having some problem in my raspberry pi 4 model B while update & upgrade it shows some errors I'm. Going to do object detection on raspberry pi project on my engineering college I have to compete the project before 28 th April so please kindly reply to my comment and pls help me 🙏
Heyya mate, if you are running into errors come check the comment section on the full write up as there is a lot of successful troubleshooting to learn from and you can post some screenshots of your errors there. I'll help get your system running proper 😊
Hi, How can I run the object detection even without connection to laptop or manually running the code.
You got heaps of different options. For example, you could run the script automatically every time the Raspberry Pi boots (using Cron Jobs, check here for a guide - th-cam.com/video/rErAOjACT6w/w-d-xo.html) or you could run the code remotely using your phone (check here - core-electronics.com.au/tutorials/raspcontrol-raspberry-pi.html)
Can we run a 5v buzzer onobject detection for a specific object ?
Absolutely, you will just need to add in some extra code to activate that buzzer whenever the desired object is spotted. Very swell idea.
Can you add a guide to make it simpler for me? Would love to see it.
Is the OpenCV for RPI can be use to RPI 4 with 2gb RAM?
Absolutely sorted mate, If your using a Raspberry Pi 4 then you'll be good to go 😊
how to detect waste like
lays packets ?
Hi there I run into this error when following the steps: error: externally managed-environment can you assist with video to fix this error so that I can complete the steps thanks
Hey Mate, with the new Bookworm OS, we have been forced to use virtual environments (not using one gives the "externally managed environment"). We have a workaround for it here: core-electronics.com.au/guides/raspberry-pi/using-virtual-environments-in-thonny-on-a-raspberry-pi/
Can this be performed on a Raspberry Pi 3B+?
Yes but there will be a slight delay in the video feed.