<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Computer Vision on Amine El Farssi</title><link>https://amineelfarssi.github.io/tags/computer-vision/</link><description>Recent content in Computer Vision on Amine El Farssi</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 Amine El Farssi</copyright><lastBuildDate>Sun, 01 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://amineelfarssi.github.io/tags/computer-vision/index.xml" rel="self" type="application/rss+xml"/><item><title>DeepSeek OCR: Running State-of-the-Art OCR Locally</title><link>https://amineelfarssi.github.io/blog/deepseek-ocr-local-guide/</link><pubDate>Sun, 01 Feb 2026 00:00:00 +0000</pubDate><guid>https://amineelfarssi.github.io/blog/deepseek-ocr-local-guide/</guid><description>&lt;h2 class="relative group"&gt;Introduction
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&lt;p&gt;In the age of AI, Optical Character Recognition (OCR) has evolved from simple pattern matching to sophisticated vision-language models that can understand context, preserve formatting, and handle complex documents. &lt;strong&gt;DeepSeek-OCR&lt;/strong&gt; represents the cutting edge of this evolution — and the best part? You can run it entirely offline on your own hardware.&lt;/p&gt;</description></item></channel></rss>