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This is simply amazing! I always wanted to know if there was a way youtube scares me with recommendations, I don't know how advanced it can go, but, I think this is it. I haven't seen the code yet, but python is just awesome! thanks for showing me this masterpiece!
Hi, looks awesome. Can we use Mediapipe and this code to detect the level of emotions? For example, normal happy, average happy, high happy, extremely happy, etc, by assigning some confidence scores and automatic labeling.
Hi, not sure if you could do it with the confidence score, but you could create new categories like 'normal happy', 'very happy', 'extremely happy', then go through the images and label them accordingly, it could work.
I am currently in the data extraction process and every time I try to execute the prepare_data file it runs for a couple of minutes then crashes. Does it have something to do with the size of my dataset? Do I need to shrink it down?
Try my premium courses! 😃🙌😊
● End-To-End Computer Vision: Build and Deploy a Video Summarization API bit.ly/3tyQX0M
● Hands-On Computer Vision in the Cloud: Building an AWS-based Real Time Number Plate Recognition System bit.ly/3RXrE1Y
● Machine Learning Entrepreneur: How to start your entrepreneurial journey as a freelancer and content creator bit.ly/4bFLeaC
All my premium courses are available to the Computer Vision Experts in my Patreon. 😉
www.patreon.com/ComputerVisionEngineer
this video better than old one, thanks to your labor
Glad you liked it! You are welcome! 🙌
this tutorial was amazing. I've been trying to find something like this for a while. thanks a lot!!!
31:02 Está detectando sad, todo parece estar correcto... se me rompe el corazón. Buen video!! Saludos desde España!
Awesome video! Now I'm a subscriber of your patreon. Thank you.
This is simply amazing! I always wanted to know if there was a way youtube scares me with recommendations, I don't know how advanced it can go, but, I think this is it. I haven't seen the code yet, but python is just awesome! thanks for showing me this masterpiece!
Hi, looks awesome. Can we use Mediapipe and this code to detect the level of emotions? For example, normal happy, average happy, high happy, extremely happy, etc, by assigning some confidence scores and automatic labeling.
Hi, not sure if you could do it with the confidence score, but you could create new categories like 'normal happy', 'very happy', 'extremely happy', then go through the images and label them accordingly, it could work.
Hi sir.I am getting an index error in testmodel.py file .Emotion range out of index
just a question
why did you use Scikit but not YOLOv8
is there a technical reason behind it ?
Hi, Thanks for your video. And can you tell me 'How to add smiley(sad, happy etc) on facial expression video?
I can't install mediapipe , my python version is 3.12.2
You need to install 3.11 and below versions
Thanks for making it but i need one help may you please share the image dataset link....
can you please share with me the dataset ?
need help with how i can get this on my pycharm and how can i execute from there. Do i have to download github desktop for that?
when I run the test_model.py, the process is finished with exit code 0 right away. what's the problem?
check this line: cap = cv2.VideoCapture(2), you may need to input a different device number, try with 0
I am currently in the data extraction process and every time I try to execute the prepare_data file it runs for a couple of minutes then crashes. Does it have something to do with the size of my dataset? Do I need to shrink it down?
What is the size of your dataset?
@@ComputerVisionEngineer about 35.6k examples
@@TheCorruptedComputer try to print the image number to see where it crashes
can a webcam be linked with the system?
where will i get the images?
Can you tell me how to do it on video to add smileys based on our facial expression?
You need something like a smileys dictionary and then select the one you need based on the detected emotion. 🙌
@@ComputerVisionEngineer Thanks buddy