@@josetomasl.4611 have all the stuff available for free on my TH-cam channel! Almost 500 videos. My courses are just structured, with help and other stuff like quizzes etc. creating 500 videos is not easy and takes 3-4 years. I have recorded videos getting back after New Year’s Eve at 3am in the morning. Of course I can sell some courses to make some money when I do it all for free. Bet all my money on you are and have been paying for education your whole life and everyone is. TH-cam is the best platform for free education and I do my part
how to save yolov10 training process in Google Drive, in order to be able to resume the training if it was interrupted and i want to continue the training from the last checkpoint?
Thanks for this useful tutorial. In the last part of the video for the inference, you don't put the model in eval mode 'model.eval()' , and you don't use 'with torch.no_grad()' for the inference. Is it useless in your case?
Awesome video Nicolai, yolov10 is great news for the space. I have been doing some tests with the models exported to OpenVino and i can get some pretty decent inference time results on CPU with this new family of models, a good 20-30% improvement w.r.t the equivalent yolov8 models.
@@NicolaiAI Thanks to you for the informative videos, your channel is awesome. Here are the simplified results from the tests using the c++ OpenVino inference engine on specific target hardware (Intel Core i5-1135G7 - 8 GB RAM). Yolov10n: 25.8471 ms (38.68 fps) Yolov10s: 70.372 ms (14.21 fps) Yolov10m: 185.095 ms (5.40 fps) Yolov10l: 376.334 ms (2.66 fps) I strongly believe this preliminary tests show that yolov10 models could be deployed in real-world, real-time applications where the only available hardware for inference are Intel CPUs, specially for the small (nano to medium models) and/or if you further explore the quantization techniques available within the Ultralytics repository or the NNCF tools from OpenVino.
I live on a busy street and would like to do traffic counting. I would like to track pedestrians, bicyclists, cars, buses, etc. I am a newbie but would anyone recommend a specific wireless web camera? I am thinking of installing on a tree and looking for a solar recharge option. I would also like to track things 24/7 so night capability is needed. Just wondering what camera(s) and features I should look for. Just started to do some stuff in Python, but could be an interesting project. Thanks very much.
HI! I have a basic question sorry I am new in this world if I want to change in the code of yolov10 or v11 (ex: backbone) which file should I work in and how to run that new code? is there any tutorial of how to do that? please help\
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please create open source courses, it would help much more people, education should be free
@@josetomasl.4611 have all the stuff available for free on my TH-cam channel! Almost 500 videos. My courses are just structured, with help and other stuff like quizzes etc. creating 500 videos is not easy and takes 3-4 years. I have recorded videos getting back after New Year’s Eve at 3am in the morning. Of course I can sell some courses to make some money when I do it all for free. Bet all my money on you are and have been paying for education your whole life and everyone is. TH-cam is the best platform for free education and I do my part
Hello Sir can we also embed this project with the custom dataset of single classification on roboflow?
Nicolai Nielsen, You're the best! I subscribed because I love your content!
Thanks a lot for the words man! Hope you will enjoy future videos too
how to save yolov10 training process in Google Drive, in order to be able to resume the training if it was interrupted and i want to continue the training from the last checkpoint?
Where can I find the Google Drive?
Nicolai Nielsen, This made me laugh so much! Thanks for sharing!
Glad you enjoyed it!
the consumption seems better, but actually it doesnt give me the thought like disruptive
100% correct!
Thank you so much for sharing this.
I want to use the same in fish fingerlings tracking and counting, any advices on how I should go about it
Would it be possible to label events? For example, a highway camera and labelling where it's should label it as "traffic_congestion"?
Yeah that would just be classification if u want to assign a label to the whole image
Thanks for this useful tutorial. In the last part of the video for the inference, you don't put the model in eval mode 'model.eval()' , and you don't use 'with torch.no_grad()' for the inference. Is it useless in your case?
Awesome video Nicolai, yolov10 is great news for the space.
I have been doing some tests with the models exported to OpenVino and i can get some pretty decent inference time results on CPU with this new family of models, a good 20-30% improvement w.r.t the equivalent yolov8 models.
Thanks a lot for watching! And also sharing your insights and test. Thanks man
@@NicolaiAI Thanks to you for the informative videos, your channel is awesome. Here are the simplified results from the tests using the c++ OpenVino inference engine on specific target hardware (Intel Core i5-1135G7 - 8 GB RAM).
Yolov10n: 25.8471 ms (38.68 fps)
Yolov10s: 70.372 ms (14.21 fps)
Yolov10m: 185.095 ms (5.40 fps)
Yolov10l: 376.334 ms (2.66 fps)
I strongly believe this preliminary tests show that yolov10 models could be deployed in real-world, real-time applications where the only available hardware for inference are Intel CPUs, specially for the small (nano to medium models) and/or if you further explore the quantization techniques available within the Ultralytics repository or the NNCF tools from OpenVino.
Couldn’t able to import Yolov10 from ultralytics in pycharm
Pip install the yolov10 repo as I do in the video. It’s not supported by Ultralytics own package yet
@@NicolaiAI thanks. It worked!!
Why do a whole bunch of boxes show up on my object detection?
I live on a busy street and would like to do traffic counting. I would like to track pedestrians, bicyclists, cars, buses, etc.
I am a newbie but would anyone recommend a specific wireless web camera? I am thinking of installing on a tree and looking for a solar recharge option. I would also like to track things 24/7 so night capability is needed.
Just wondering what camera(s) and features I should look for.
Just started to do some stuff in Python, but could be an interesting project.
Thanks very much.
Why in logs at 15:15 wrote that using yolov8. And a little bit later will be download yolov8n??
I got error attribute error that v10 detectloss please help me to solve
Best tutorial ever
Hey man, thanks a lot for watching!
Thanks! Does YOLOv10 have segmentation model as well? I haven't seen on the official website.
Nope not yet
HI! I have a basic question sorry I am new in this world
if I want to change in the code of yolov10 or v11 (ex: backbone) which file should I work in and how to run that new code?
is there any tutorial of how to do that? please help\
Amazing tutorial. Thanks a lot.
Thanks a ton man! Definitely check out the new video with training in Ultralytics as well. It’s added now into the framework
hello, i have get error (cannot import name 'YOLOv10' from 'ultralytics') and i install in local my ultralytics==8.2.48 version
Think you might have to change v8
@@FlyWithSergio why?
I want to request on how to do this project on classification sir, please.
can you do it from tge very first step? im new, i need this for my school proj
This is from the very first step of generating a dataset and training a model and inference
@@NicolaiAI the cv2 said could not be resolved
@@jaimeabug9090 if cv2 module is not recognized try reinstalling cv2, or install it in conda if ur using python
where is the collab link?
hello, i have error (cannot import name 'YOLOv10' from 'ultralytics')
Did u pip install the yolov10 GitHub repo as I do in the video?
@@NicolaiAI yes
@DarhanZhaksalykov locally or in colab? In colab it should work. Locally it might be because u already have another version installed of Ultralytics
How to display confidence score
U can extract that directly from the results variable as well
@@NicolaiAI how can I display it in the box?
Will come back to this 😊
Definitely do!
how to installl v10
You can use Ultralytics now! But I show how to install v10 here in the video but also have a new one for Ultralytics
Nice video!
Thanks mate!
How can i contact you sir
Have all my social media’s in the description
I think I love you
Love u too
This shit is so complicated
TypeError: unhashable type: 'numpy.ndarray'
how do i fix this error? i just need it with my project its due on this..
how do i fix this error nicolai? TypeError: unhashable type: 'numpy.ndarray'
same :,c
I am facing these errors in training cell!
TypeError: unhashable type: 'numpy.ndarray'
TypeError: Caught TypeError in DataLoader worker process 0.
i'm facing it too, have you solved it ?
Yes I resolve the problem
@@taliqamuhib8968 !pip install albumentations==1.4
RUN THIS BEFORE TRAINING
@@taliqamuhib8968 did you guys already fix it? and how?
@@taliqamuhib8968 how?