Based on our record, Laravel should be more popular than OpenCV. It has been mentiond 194 times since March 2021. 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.
Laravel is a popular PHP framework known for its expressive syntax and rich ecosystem of features. Here's why it shines for building RESTful APIs:. - Source: dev.to / 25 days ago
Implementation In this article, we'll delve into the concept of rate limiting in Laravel; a popular PHP framework. We will explore how to set it up, customize it to suit your application's needs, and handle common scenarios. By the end, you'll have the knowledge and confidence to implement rate limiting in your Laravel applications, enhancing their security and stability. - Source: dev.to / about 2 months ago
Delving into PHP frameworks like Laravel or Symfony is like building a skyscraper, with Composer acting as your "construction foreman," guiding you step by step to ensure your code is robust and awe-inspiring. This stage involves getting familiar with popular PHP frameworks such as Laravel, Symfony, CodeIgniter, etc., and utilizing the functionalities provided by these frameworks to rapidly develop efficient,... - Source: dev.to / about 2 months ago
Your very first starting point should be the Laravel documentation. Known for its clear explanations and user-friendly layout, the Laravel documentation makes setup a breeze, ensuring you get off to the best possible start. - Source: dev.to / about 2 months ago
In this tutorial, we will learn how to create a GraphQL API with Laravel, a popular PHP web framework. We will be creating a simple student model, seeding the database with dummy data, setting up a database connection, and creating a GraphQL server by defining our API's schema, queries, and mutations. We’ll also learn how to make requests to our API (test our endpoints) using a tool like Insomnia or Postman. By... - Source: dev.to / 3 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
Django - The Web framework for perfectionists with deadlines
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
CodeIgniter - A Fully Baked PHP Framework
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
NumPy - NumPy is the fundamental package for scientific computing with Python