🎯 ТОП-5 структур данных для обработки изображений
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Как компьютеры «видят» изображения?
Какие структуры помогают выделять объекты, экономить память и ускорять алгоритмы?
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В этом посте — ключевые структуры, без которых не обойтись в компьютерном зрении:
🔹 Матрицы
🔹 Цепи
🔹 Графы
🔹 Пирамиды
🔹 Квадродеревья
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Если хотите узнать больше — полная статья по ссылке: https://proglib.io/sh/nitr6FEIjR
Библиотека дата-сайентиста #буст
BY Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение
Telegram is an aspiring new messaging app that’s taking the world by storm. The app is free, fast, and claims to be one of the safest messengers around. It allows people to connect easily, without any boundaries.You can use channels on Telegram, which are similar to Facebook pages. If you’re wondering how to find channels on Telegram, you’re in the right place. Keep reading and you’ll find out how. Also, you’ll learn more about channels, creating channels yourself, and the difference between private and public Telegram channels.
You can’t. What you can do, though, is use WhatsApp’s and Telegram’s web platforms to transfer stickers. It’s easy, but might take a while.Open WhatsApp in your browser, find a sticker you like in a chat, and right-click on it to save it as an image. The file won’t be a picture, though—it’s a webpage and will have a .webp extension. Don’t be scared, this is the way. Repeat this step to save as many stickers as you want.Then, open Telegram in your browser and go into your Saved messages chat. Just as you’d share a file with a friend, click the Share file button on the bottom left of the chat window (it looks like a dog-eared paper), and select the .webp files you downloaded. Click Open and you’ll see your stickers in your Saved messages chat. This is now your sticker depository. To use them, forward them as you would a message from one chat to the other: by clicking or long-pressing on the sticker, and then choosing Forward.
Библиотека data scientist’а | Data Science Machine learning анализ данных машинное обучение from fr