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that's cool and if YOLO detect it without me specifying an object?

Will detection work in grayscale images or videos?

Source code!

Hello good sir I know this is an old video but it is the one that has worked for me. Though I get an error: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first. DO you know of this if so thank you for any help you can give.

Hi, Can you help me with this error. silvatpu-linux-setup Illegal instruction

Do you think this would work on the google coral devboard too?

How did you set up the google collab storage session? I have been trying but I cant link my folders. I tried but I was unable to access the sub folders inside the folders. Each train, valid, and test folder contains two more folders called images and labels.

i have trained a yolov8-seg model on a custom dataset...but when i downloaded the model in my local system and tried it on vs code it is giving me unexpected output

Thanks for the video. Could you link to the man_working.mp4 video? I would like to benchmark up against what you are outputting in terms of fps. Also, did you change the size of the videoframe in that video to be 192/240 in width(and/or height)?

Hi there. It shows the error called "TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first."

@Koby_n_Code make some more videos bro, your content is exceptional! Can you make a video on implementing yolo into an arduino/raspberry pi?

very nice video but it will be better if you had a little better quality !!!

The GitHub link in the description is incorrect can you give me your account GitHub , please , I want to see code

colab notebook mil sakti ha? i need colab nootebook

can you provide this video github repo..please

Hello Koby. Many thanks for this tutorial. I was earlier using RPI4 (32 bit legacy os) along with google coral accelerator and using edge tpu i was able to recognize object with my pi camera. I think it was using SSD model. I want to extend by using YOLO model and referring to this project. I am having a short query that this model work on edge tpu correct since we are using coral accelerator

Can i use this set up for Raspberrypi zero 2w

switched to a usb camera, but still struggling with getting it to run the model with a video feed. Is there an example code somewhere that does this using this model? No matter what I try I still get the "ValueError: Failed to load delegate from libedgetpu.so.1" error.

one issue I can't seem to get around when going back to Python 3.9 is that I cannot get libcamera to work for the pi camera module 3...either coral doesn't work with 3.11 or libcamera doesn't work with 3.9...driving me crazy!

Hye sir, i have run the yolo basic.py to test the image tensor, however the terminal shows None on dir. How to fix this? thankyou

nice video~

is it possible if i use ESP32-cam as the live camera?

thank you so much, man. you helped me a lot :)

Hello Koby..Thanks for this video...I just bought dual edge coral TPU but in pci case for raspberry pi 5. . Can not this be used with this library?

Please help me in that , i have a rpi 4 with 64 bit os , and i want to use camera module ip , with script ultrlytics

Great video. Thanks!

Hello Koby, i have a problem when i run the code like you did at 28:41 my RP4 reboot, i do not know why i have tried many time and it reboot again , i need to finish your tutorial so i could use my usb web cam to for live object detection, thank you in advance Edit: the RP does not reboot it closed remotely

Hello Koby. Can you help me pls? I want to run an object detection model on my raspberry pi 4 with a Coral USB accelerator and a model 3 wide camera. But I am having big problems with FPS currently only 3-4fps. Can you recommend me the best approach? I need to detect objects at a long distance but I have only class 1. I have been using mobilenet ssd fpn lite 320 and 640. I need to have minimum 25fps to close my project. I would appreciate any help. Thank you.

Can I create my own model using yolov8? How do I convert it to tflite?

can i get ur number in wasup app please i need ur brain

/.venv/lib/python3.7/site-packages/edge_tpu_silva/silva/silva_detect.py", line 34, in process_detection model=model_path, task="detect", verbose=False TypeError: __init__() got an unexpected keyword argument 'verbose' getting this error when trying to run cli. additionally can you give some definitive example on formatting camera input. specifically using camera 0 on rpi5. thanks

What name command you write

Hi! We are creating a system that classifies tomato ripeness levels using image processing in CNN architecture with the YOLOv8 model. We are using Raspberry Pi 4 OS with 4GB RAM and we have encountered a problem - the system has 2-3 minute delay/lag in classifying the ripeness level. Would you happen to have any recommendation/suggestion sir on this problem?

Hi! We are creating a system that classifies tomato ripeness levels using image processing in CNN architecture with the YOLOv8 model. We are using Raspberry Pi 4 OS with 4GB RAM and we have encountered a problem - the system has 2-3 minute delay/lag in classifying the ripeness level. Would you happen to have any recommendation/suggestion sir on this problem?

Thank you for your video. How much FPS did you get for YOLOv8 and YOLOv9 respectively?

‏‪35:24‬‏ Thank you. The explanation was very good. But I have one problem. At this time 35:24 , I keep getting the same error. I could not solve it.

github link is not working can u reply with the link ? thank you...!

Thank you so much for this amazing tutorial, it helped a lot with my project! Could you please help me with some informations about how I could use this setup for an USB webcam live inference object detection? Instead of being on .mp4 video files. I tried using the ultralytics script, but it didn’t work. Thanks again!

Thank for your tutorial maybe it's have possible to deploy YOLOv7 model on TPU with RPI4 I will try it when i'm get some time

Thank you for this amazing tutorial

A great tutorial to get you started

Thank you, thank you, thank you! I've been struggling to get my YOLOv8 + RPi 4 + Coral TPU up and running. I'm going to follow your tutorial this weekend and see if I can get everything working. Exciting!!

Hey I would like to know how we get the output on another terminal as you get as when I'm running the code it only giving the index and array as the output

tysm for this tutorial! I just have a question, if I add a valid object that's not in the coco.txt file say "paper", can the model now detect paper?

i have intel i5 and ram =8 G. but the video running slowly . and i have raspberry pi 3 cant running this program because the yolo algorithm need a more performance the CPU and RAM. Is my analysis correct? Thank you very much for your excellent explanation.

can you help me in detection with voicefeedback how i can do this? thanks waiting

hey brother no matter what i do its howing no module named 'torch' even though i am trying to install that it says no matching dist found for torch what should i do somebody help me

Hi there, thanks much. This is very useful. When is the next video coming up?

if i have a video that shows only a hand moving, how can i set a class hand to te model? The hand is classificated as 'person'

What should I do if I want to create an output video at the end?