Based on our record, Python should be more popular than OpenCV. It has been mentiond 280 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.
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
F-strings, introduced in Python 3.6 and later versions, provide a concise and readable way to embed expressions inside string literals. They are created by prefixing a string with the letter ‘f’ or ‘F’. Unlike traditional formatting methods like %-formatting or str.format(), F-strings offer a more straightforward and Pythonic syntax. - Source: dev.to / 3 months ago
Import aiohttp, asyncio Async def fetch_data(i, url): print('Starting', i, url) async with aiohttp.ClientSession() as session: async with session.get(url): print('Finished', i, url) Async def main(): urls = ["https://dev.to", "https://medium.com", "https://python.org"] async_tasks = [fetch_data(i+1, url) for i, url in enumerate(urls)] await... - Source: dev.to / 4 months ago
Threading involves the execution of multiple threads (smaller units of a process) concurrently, enabling better resource utilization and improved responsiveness. Python‘s threading module facilitates the creation, synchronization, and communication between threads, offering a robust foundation for building concurrent applications. - Source: dev.to / 4 months ago
FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework. - Source: dev.to / 4 months ago
When you have finished your thirty days, I recommend to go to the official site and read the offical python tutorial at python.org : https://docs.python.org/3/tutorial/index.html . Source: 5 months ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Rust - A safe, concurrent, practical language
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
NumPy - NumPy is the fundamental package for scientific computing with Python
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible