Teachable Machine might be a bit more popular than OpenCV. We know about 55 links to it since March 2021 and only 50 links to OpenCV. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Not sure if I've seen anything of the sort, seems rather specific. Maybe try a Teachable Machine project? https://teachablemachine.withgoogle.com/. - Source: Hacker News / 22 days ago
Train a computer to recognize your images, sounds, and poses. Use this resource to gain a better understanding. - Source: dev.to / 5 months ago
We will create an machine learning model that can classify Arabic and English books. To collect, train, and test data, we will use Teachable Machine from Google. - Source: dev.to / 8 months ago
a lot of places! But for a high schooler, better to focus at what you want to do first. Or if you still haven't gotten any idea, try a simple explanation on what ml is without the math on youtube and tinker around a no code machine learning platform like https://teachablemachine.withgoogle.com/. Source: 12 months ago
The principle is roughly the same as it is possible with teachablemachine.withgoogle.com. Source: 12 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 5 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 9 months ago
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 9 months ago
You also need C++ if you're going to do things which aren't built in as part of the engine. As an example if you're looking at using compute shaders, inbuilt native APIs such as a mobile phone's location services, or a third-party library such as OpenCV, then you're going to need C++. Source: 11 months ago
Google Cloud Machine Learning - Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
AngryTools Online Gradient Generator - Angrytools - Online CSS Gradient Generater interface to generate cross browser CSS gradient code as well as Android gradient code. generator produce linear or radial gradients that can be used in your web page design or android apps.
NumPy - NumPy is the fundamental package for scientific computing with Python