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Thank you so much for this tutorial! Exactly what I was trying this weekend. Spent my time annotating 3000 coca cola images with 26 classes. My model is so bad right now. Something that I experienced was over fitting. Your ducks video is very simple but it is likely that if there was more complex background you would see over fitting on 4000 images. Another issue was that for some reason when you have many classes and maybe other classes have more images. When tracking you can experience a complete switch of labels.
Thanks, I just needed this, I was training +2000 images per dataset with very limited resources, now I will try with 500 images to improve performance. Saludos desde Chile!!
Wonderful! I was wondering why prediction didn't work with your alpaca tutorial video. No I completely understood. I tested my scripts with only 56 images and did not get any prediction. I will increase the number of images! Bravo! I appreciate your work!!
I love your channel dude! Thank you for all the instructions and testing. I’ve been able to learn a ton and apply it to my own project. I do have a question about training yolo models: I have a model I’m training with 3 classes, 2 of the 3 classes train much higher than the third. Is there any recommendation you have to even out the training? Is it all dataset? Should I be making sure that there are more of 3rd class than the others? I appreciate you!
@@ComputerVisionEngineer I believe so. I would say out of the 500 - 1000 annotated images there is less than 5% that don’t have all 3 classes present. But that is a good point, I’m going to double check that.
Hello. I was trying to code your python sign language detector, but when I ran the code to collect the data of my hand symbols, I couldnt find anything in my data file. Please help
This might be about the amount of data, what about the influence of the images themselves? What is the ideal situation? Should it be very varied? Or is it okay if they are similar, say the background is still the same but the objects are from different perspectives? I'm still confused about the images, sometimes they can't be found on the Internet and I have to take them myself (in the case of my project). Thank you in advance. Your videos have been very helpful.
I have other 'experiments' in mind to see how the performance is affected by different type of issues with the data. Analyzing what happens if the background changes or if it is always the same is a good idea, I could make a video about it! 🙌
@@ComputerVisionEngineer Anyway, for clarification: Could you do a model accuracy test for various tolls like YOLO, Scikit, Teachable. I feel that they are made for various types of problems, and can you do add which toll is better to use for which problems.
@@ComputerVisionEngineer I have tried to do recognition of more complex emotions such as stress and fatigue on the face, but I get very similar results among them and with the neutral state. How would you start that project? 👀 Can you make a video about it?
@@thomschery2800 you trolling? Your questions are so vague. If you’re asking what annotation tools, it really depends on you. I like to run everything locally so label studio is my choice. There is plenty of tutorials here for beginners.
Did you enjoy this video? Try my premium courses! 😃🙌😊
● Hands-On Computer Vision in the Cloud: Building an AWS-based Real Time Number Plate Recognition System bit.ly/3RXrE1Y
● End-To-End Computer Vision: Build and Deploy a Video Summarization API bit.ly/3tyQX0M
● Computer Vision on Edge: Real Time Number Plate Recognition on an Edge Device bit.ly/4dYodA7
● Machine Learning Entrepreneur: How to start your entrepreneurial journey as a freelancer and content creator bit.ly/4bFLeaC
Learn to create AI-based prototypes in the Computer Vision School! www.computervision.school 😃🚀🎓
Can I know your upwork or freelancer? I have the project
Thank you so much for this tutorial! Exactly what I was trying this weekend. Spent my time annotating 3000 coca cola images with 26 classes. My model is so bad right now. Something that I experienced was over fitting. Your ducks video is very simple but it is likely that if there was more complex background you would see over fitting on 4000 images. Another issue was that for some reason when you have many classes and maybe other classes have more images. When tracking you can experience a complete switch of labels.
Glad it is helpful! Yeah in my case it was only one class, so it was simpler. 🙌
Thanks, I just needed this, I was training +2000 images per dataset with very limited resources, now I will try with 500 images to improve performance.
Saludos desde Chile!!
Glad it was helpful! Saludos! 😃🙌
Wonderful! I was wondering why prediction didn't work with your alpaca tutorial video. No I completely understood. I tested my scripts with only 56 images and did not get any prediction. I will increase the number of images! Bravo! I appreciate your work!!
Glad the content is helpful! 😃🙌
keep it coming bro, your videos are informative and helping me learn new things.
Glad the content is helpful! 😃 I will keep it coming! 💪💪
I love your channel dude! Thank you for all the instructions and testing. I’ve been able to learn a ton and apply it to my own project.
I do have a question about training yolo models: I have a model I’m training with 3 classes, 2 of the 3 classes train much higher than the third. Is there any recommendation you have to even out the training? Is it all dataset? Should I be making sure that there are more of 3rd class than the others?
I appreciate you!
Hey thank you! Glad the content is helpful. Is your dataset balanced? (balanced = same amount of objects in each class)
@@ComputerVisionEngineer I believe so. I would say out of the 500 - 1000 annotated images there is less than 5% that don’t have all 3 classes present. But that is a good point, I’m going to double check that.
Hello. I was trying to code your python sign language detector, but when I ran the code to collect the data of my hand symbols, I couldnt find anything in my data file. Please help
great video! just wanna ask, how did you split your data into train and val? is it 70-30?
90-10 if I remember correctly
This might be about the amount of data, what about the influence of the images themselves? What is the ideal situation? Should it be very varied? Or is it okay if they are similar, say the background is still the same but the objects are from different perspectives? I'm still confused about the images, sometimes they can't be found on the Internet and I have to take them myself (in the case of my project). Thank you in advance. Your videos have been very helpful.
I have other 'experiments' in mind to see how the performance is affected by different type of issues with the data. Analyzing what happens if the background changes or if it is always the same is a good idea, I could make a video about it! 🙌
In my experience if you keep the background the same the model starts detecting the background as the image to detect instead of your desired object
Thank you for this tutorial
You are welcome. 🙂
Would this also apply to keypoint detection using YoloV8 please?
I think it is likely to have similar results in a keypoints detection problem.
Ciao Filipe can you do same thing with various model generation tools(YOLO, Scikit, Teachable... ), pls?
I will try to 🙌
@@ComputerVisionEngineer Anyway, for clarification: Could you do a model accuracy test for various tolls like YOLO, Scikit, Teachable. I feel that they are made for various types of problems, and can you do add which toll is better to use for which problems.
Bro could you please make a GAN tutorial playlist along with some projects ?
I will try to make some videos about gans. 🙌
Can u share any intermediate or expert label project u did on upwork ? What would be great help for us🥰
Sure, I will find some. 🙌
Could you create a video demonstrating how to develop facial recognition for tiredness and stress?
Do you mean an image classifier the input is a face and the output is tired / not tired?
@@ComputerVisionEngineer I have tried to do recognition of more complex emotions such as stress and fatigue on the face, but I get very similar results among them and with the neutral state. How would you start that project? 👀 Can you make a video about it?
@@fitox1234 oh I see, yes it is very challenging to tell those categories apart, I will try to do a video about it.
Thanks you for your tutorial,btw can you make tutorial yolo v9😁?
I will try to. 🙌
@@ComputerVisionEngineer ok thanks bro👍
Let's say he wants it to determine which player won a duel in some game based on the uploaded video. Is this possible?
Not sure if I understand, what is the machine learning problem you are trying to solve?
@@ComputerVisionEngineer Which player won the game. Would AI be able to give me such information?
What information is available on screen to determine that? You can train the model to detect health bars, score, ect
@TheJAM_Sr OK, so what would be the most preferable tools?
@@thomschery2800 you trolling? Your questions are so vague.
If you’re asking what annotation tools, it really depends on you. I like to run everything locally so label studio is my choice.
There is plenty of tutorials here for beginners.
argentina mentioned
How many epochs?
I trained the models for 20 epochs.