Image Classification custom data train yolov8 in Google Colab for free | Computer vision tutorial
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- Опубликовано: 7 июл 2024
- Code: github.com/computervisioneng/...
🎬 Timestamps ⏱️
0:00 Intro
0:24 Data
1:43 How to structure the data
5:32 Execute notebook on Google Colab
10:32 More comprehensive explanation
11:13 Outro
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Number 1, thanks Felipe!!
Thank you so much for the tutorial. I have trained the model and it gives satisfied results on images that I now give it. Please tell me (or please make a video about this) the process that how do i save that model and use it in a mobile application in Python that uses this model to detect the ingredients and then processes that list of those ingredients to generate further results. Also which platforms should I use for the coding and stuff. Please let me know, I have a project to complete, by the end of this week.
Nice
I love you, you are awesome
What about data.yaml file is that needed for training. Or we only need train test data only?
Image classification seems to be unable to classify pictures with very small differences. For example,I am working in a garment factory, different necklines and armholes are very similar. Yolo classification only get 70% accuracy.
Hey
Please publish a video with YOLOv8 and tracking, including car or truck counting and speeeeed estimation 🙏🙏🙏🙏
Sure, I will try to. 🙌
Thank you for your video
I want to train model that can know brands of shoes like jordan nike Adidas etc ...
What should i use ?
So the input is the image of a shoe and the output is the brand of that shoe? You could try with yolov8 following this tutorial. Let me know how it goes! 🙌
@@ComputerVisionEngineer yeah sure
But problem is when i detect for example shose brand i need to know version of it
Like jordan (air force)
So there is two filters shose it self brand and model of it
Hello, I wonder if you would like to make multilabel classification video.
Hello, this video is about multilabel classification.
F, that feels too easy
Sometimes training a machine learning model is a very simple process! 😃🙌
Nice