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nilab id:nilab

imageprocessingã«é–¢ã™ã‚‹nilabã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (25)

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[ãƒ…]äººé–“ä»¥å¤–ã®å†™çœŸã§ Microsoft ã®æ„Ÿæƒ…èªè˜ã‚’è©¦ã™ (2015-11-12)
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nilab 2015/11/13
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microsoft

imageprocessing
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nilab 2015/05/25
ã€Œäººå·¥çŸ¥èƒ½æŠ€è¡“ Deep Convolutional Neural Networksã€ã€Œwaifu2xã¯ã€SRCNNã«ã‚¤ãƒ³ã‚¹ãƒ‘ã‚¤ã‚¢ã€ã€Œç”»åƒã‚’æ‹¡å¤§ã™ã‚‹ã®ã§ã¯ãªãã€ç¸®å°ã•ã‚Œã‚‹å‰ã®çŠ¶æ…‹ã«æˆ»ã—ã¾ã™ã€ã€ŒãƒŽã‚¤ã‚ºã‚’å–ã‚Šé™¤ãã®ã§ã¯ãªãã€ç”»åƒã‚’JPEGåœ§ç¸®ã•ã‚Œã‚‹å‰ã®çŠ¶æ…‹ã«æˆ»ã—ã¾ã™ã€

imageprocessing
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Node.jsã§è¤‡æ•°ã®ç”»åƒãƒ•ã‚¡ã‚¤ãƒ«ã‚’ãƒªã‚µã‚¤ã‚ºã™ã‚‹æ–¹æ³• - 40æ³ã‹ã‚‰ã®ã‚ãƒ£ãƒªã‚¢ãƒã‚§ãƒ³ã‚¸
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nilab 2015/04/03
Node.jsã§è¤‡æ•°ã®ç”»åƒãƒ•ã‚¡ã‚¤ãƒ«ã‚’ãƒªã‚µã‚¤ã‚ºã™ã‚‹æ–¹æ³• - TitaniumMobileå‹‰å¼·è¨˜ : ImageMagick + easyimage

node.js

ImageMagick

imageprocessing
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ã€Žã€ŒMangaMeeyaï¼ˆãƒžãƒ³ã‚¬ãƒŸãƒ¼ãƒ¤ï¼‰ã€ â€œè‡ªå‹•ç€è‰²â€æ©Ÿèƒ½ã™ã’ã‡ï½—ï½—ï½—ï½—ï½—ï½—ï½—ï½—ï½—ã€ã®å†…æƒ…ã«è¿«ã‚‹
umjammer ã§ã™ã€‚ æ˜¨æ—¥ RSS ã‚’çœºã‚ã¦ã„ã‚‹ã¨è¡¨é¡Œã€Žã€å†…ã®è¨˜äº‹ãŒç›®ã«å…¥ã‚Šã¾ã—ãŸã€‚ã‚µã‚¤ãƒˆ(ã‚¨ãƒåºƒå‘Šæœ‰ã‚Šæ³¨æ„)ã‚’è¦—ã„ã¦ã¿ã‚‹ã¨ãŸã—ã‹ã«ã™ã”ã„ã§ã™ã€‚ä¹…ã€…ã«é¢ç™½ãã†ãªæŠ€è¡“ã ãªã¨æ€ã„ã€å†…æƒ…ã‚’èª¿ã¹ã¦è¦‹ã‚‹ã“ã¨ã«ã—ã¾ã—ãŸã€‚ MangaMeeya ã¯ Windows ã®ã‚³ãƒŸãƒƒã‚¯ãƒ“ãƒ¥ãƒ¼ã‚¢ã¨ã—ã¦ä»£è¡¨çš„ãªã‚½ãƒ•ãƒˆã®ä¸€ã¤ã§ã™(ç¾åœ¨ã¯å…¬é–‹ä¸æ¢ï¼Ÿ)ã€‚ãã—ã¦ MangaMeeya ã¯ Avisynth ã‚’ãƒ—ãƒ©ã‚°ã‚¤ãƒ³ã¨ã—ã¦ä½¿ç”¨ã§ãã‚‹ã¿ãŸã„ã§ã™ã€‚Avisynth ã¯æ§˜ã€…ãªå‹•ç”»å‡¦ç†ã‚’ãƒ—ãƒ©ã‚°ã‚¤ãƒ³ã‚’ç”¨ã„ã¦è¡Œãªã†ã€ã“ã‚Œã‚‚æœ‰åãªã‚½ãƒ•ãƒˆã§ã™ã€‚ç§ã¯ä»¥å‰ãŠä¸–è©±ã«ãªã£ãŸã“ã¨ãŒã‚ã‚Šã¾ã™ã€‚ãã® Avisynth ã®ãƒ—ãƒ©ã‚°ã‚¤ãƒ³ã®ä¸€ã¤ã« GiCoCu ã¨ã„ã†ã‚‚ã®ãŒã‚ã‚Šã€ã“ã‚ŒãŒå®Ÿéš›ã®è‡ªå‹•ç€è‰²ã‚’è¡Œãªã£ã¦ã„ã‚‹ã“ã¨ãŒã‚ã‹ã‚Šã¾ã—ãŸã€‚ ã¾ã¨ã‚ã‚‹ã¨ GiCoCu â€¦ è‡ªå‹•ç€è‰²ã®ãƒã‚¸ãƒƒã‚¯ Avisynth â€¦ GiCoCu ã®ãƒ•ãƒãƒ³ãƒˆã‚¨ãƒ³ãƒ‰ MangaMeeya
nilab 2012/02/22
ã€Žã€ŒMangaMeeyaï¼ˆãƒžãƒ³ã‚¬ãƒŸãƒ¼ãƒ¤ï¼‰ã€ â€œè‡ªå‹•ç€è‰²â€æ©Ÿèƒ½ã™ã’ã‡ï½—ï½—ï½—ï½—ï½—ï½—ï½—ï½—ï½—ã€ã®å†…æƒ…ã«è¿«ã‚‹ : GiCoCu â€¦ è‡ªå‹•ç€è‰²ã®ãƒã‚¸ãƒƒã‚¯, AviSynth â€¦ GiCoCu ã®ãƒ•ãƒãƒ³ãƒˆã‚¨ãƒ³ãƒ‰, MangaMeeya â€¦ Avisynth ã®ãƒ•ãƒãƒ³ãƒˆã‚¨ãƒ³ãƒ‰

imageprocessing

graphics

color
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GraphicsMagick Image Processing System
Check http://www.GraphicsMagick.org/ or https://graphicsmagick.sourceforge.io/index.html for the latest version of this page. GraphicsMagick is the swiss army knife of image processing. Comprised of 286K physical lines (according to David A. Wheeler's SLOCCount) of source code in the base package, it provides a robust and efficient collection of tools and libraries which support reading, writing,
nilab 2011/08/19
GraphicsMagick Image Processing System

imageprocessing
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Imlib2: Imlib2 Library Documentation
Version:1.1.1 Author:Carsten Haitzler <[email protected]> Date:1999-2004 What is Imlib2 ? Imlib 2 is the successor to Imlib. It is NOT a newer version - it is a completely new library. Imlib 2 can be installed alongside Imlib 1.x without any probl ems since they are effectively different libraries - BUT they Have very similar functionality. Imlib 2 does the following: Load image files from disk
nilab 2011/08/19
Imlib2: Imlib2 Library Documentation

lib

graphics

imageprocessing
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How To Optimize PNG â€” Smashing Magazine
This post describes some techniques that may help you optimize your PNG-images. These techniques are derived from laborious hours spent on studying how exactly the PNG encoder saves data. Weâ€™ll start with some essentials about the PNG format and will then move to advanced optimization techniques. As a web designer you might be already familiar with the PNG image format which offers a full-featured
nilab 2010/08/18
Clever PNG Optimization Techniques - Smashing Magazine

graphics

imageprocessing

png
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Imlib2ã§ImageMagickã‚ˆã‚Š3å€é«˜é€Ÿã‹ã¤ç¾Žã—ã„ã‚µãƒ ãƒã‚¤ãƒ«ç”»åƒã®ç”Ÿæˆ - æ˜¼ãƒ¡ã‚·ç‰©èªž
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nilab 2010/07/24
RMagickã¨Imlib2-Rubyã®æ¯”è¼ƒã€‚qualityã€Œ90ã¨ãªã‚‹ã¨ã€å¤šå°‘ãƒ–ãƒãƒƒã‚¯ãƒŽã‚¤ã‚ºãŒå‡ºã¦ã„ã‚‹ãŒã€ã‚µãƒ ãƒã‚¤ãƒ«ã‚’è‚‰çœ¼ã§è¦‹ã¦ã‚‚ã‚ã¾ã‚Šå·®ãŒãªã„ã€Imlib2ã§ImageMagickã‚ˆã‚Š3å€é«˜é€Ÿã‹ã¤ç¾Žã—ã„ã‚µãƒ ãƒã‚¤ãƒ«ç”»åƒã®ç”Ÿæˆ

imageprocessing

thumbnail
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ãƒ‡ã‚³ãƒ¬ãƒžã‚¸ãƒƒã‚¯ - ã‚ãªãŸã®å†™çœŸã‚’ãƒ‡ã‚³ãƒ¡çµµæ–‡å—ã«â™ª
nilab 2010/06/30
ãƒ‡ã‚³ãƒ¬ãƒžã‚¸ãƒƒã‚¯ - ã‚ãªãŸã®å†™çœŸã‚’ãƒ‡ã‚³ãƒ¡çµµæ–‡å—ã«â™ª

imageprocessing

animation_gif
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Ring
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nilab 2010/06/30
ImageMagickã§ãƒ‡ã‚³ãƒ¡çµµæ–‡å—ã‚’ã¤ãã‚‹æ–¹æ³• : Media Technology Labs (MTL) : ãƒ¡ãƒ‡ã‚£ã‚¢ãƒ†ã‚¯ãƒŽãƒã‚¸ãƒ¼ãƒ©ãƒœã€€ãƒ–ãƒã‚°:ã‚¢ãƒƒãƒ—ãƒãƒ¼ãƒ‰å†™çœŸã‚’50pxÃ—50pxã«ç¸®å°ã—ã¦ã‚¹ã‚±ãƒƒãƒèª¿ã«å¤‰æ›->ç¸¦åè»¢ã—ãŸç”»åƒã‚’ä¿å˜->åè»¢ã—ãŸç”»åƒ2ç‚¹ã‚’ã‚¢ãƒ‹ãƒ¡ãƒ¼ã‚·ãƒ§ãƒ³GIFã«å¤‰æ›

ImageMagick

imageprocessing
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[ãƒ…ãƒ©ãƒ‰] Java ã®ãƒ•ã‚£ãƒ«ã‚¿è¡Œåˆ—APIã‚’ä½¿ã£ã¦ã„ã‚ã„ã‚ãªç”»åƒå‡¦ç†ã‚’ã—ã¦ã¿ãŸ
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nilab 2010/01/13
_[ãƒ…ãƒ©ãƒ‰] Java ã®ãƒ•ã‚£ãƒ«ã‚¿è¡Œåˆ—APIã‚’ä½¿ã£ã¦ã„ã‚ã„ã‚ãªç”»åƒå‡¦ç†ã‚’ã—ã¦ã¿ãŸ : ã‚ã‚Œã‚¬ã‚¦ã‚·ã‚¢ãƒ³ãƒ•ã‚£ãƒ«ã‚¿ã£ã¦ã„ã†ã®ã‹ã€‚ã€‚ã€‚

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nilab 2010/01/13
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imageprocessing

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Jerry's Java Image Processing Pages
Java Image Filters I have a large number of Java Image filters which are freely available for download from this site. The filters are all standard Java BufferedImageOps and can be plugged directly into existing programs. All the filters are available in the Java Image Editor and most have dialogs to allow you to play with their settings. If you want to try out any of these filters, I recommend do
nilab 2010/01/08
Jerry's Java Image Processing Pages : Java Image Filters : ç”»åƒåŠ å·¥ãƒ•ã‚£ãƒ«ã‚¿ãƒ¼ã‚ã‚Œã“ã‚Œã€‚åŠ å·¥å‰ã¨åŠ å·¥å¾Œã®ç”»åƒã‚ã‚Šã€‚ã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰ã¯ç„¡ã—ï¼Ÿ

java

imageprocessing
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pixels: Home
nilab 2010/01/08
pixels: ãƒ›ãƒ¼ãƒ ã€ŒImage Processing classes for Java2Dã€ ç”»åƒåŠ å·¥ãƒ•ã‚£ãƒ«ã‚¿ãƒ¼ã®ãƒ©ã‚¤ãƒ–ãƒ©ãƒª

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UrlImg.com is for sale | HugeDomains
Acquiring OakvilleM aids.com through HugeDomains was a good experience. Weâ€™ve operated our business on OakvilleM aids.ca for years, but securing the .com version was important to eliminate any customer confusion and strengthen our brand credibility. HugeDomains made the entire process easy! It was fast, clear, and hassle-free. We highly recommend them to any business looking to upgrade or protect th
nilab 2010/01/01
urlimg.com - The URL-based image processing service : ãŸã¨ãˆã° http://example.com/myimage.jpg ã‚’ http://urlimg.com/resize/300x400/example.com/myimage.jpg ãªURLã§ç”»åƒå‡¦ç†

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imageprocessing
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æ±šã‚Œãªãã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰ - ã‚¹ã‚¿ãƒƒãƒ•BLOG
nilab 2009/12/04
æ±šã‚Œãªãã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰: æ—¥å ±ã‚ãã›ãã‚¸ã‚§ï½žãƒ ã‚º : ã€Œãƒ¡ãƒ‡ã‚£ã‚¢ãƒ³ã‚«ãƒƒãƒˆæ³•ã®å®Ÿè£…ç·¨ã§ã™ã€ã€Œï¼£ï¼‹ï¼‹ã§ä½œã‚‹ãƒ¡ãƒ‡ã‚£ã‚¢ãƒ³ã‚«ãƒƒãƒˆæ³•ã€

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C++ç‰ˆã®OpenCVã‚’ä½¿ã£ã¦ã‚«ãƒ©ãƒ¼ãƒ’ã‚¹ãƒˆã‚°ãƒ©ãƒ ã‚’ç”¨ã„ãŸé¡žä¼¼ç”»åƒæ¤œç´¢ã‚’å®Ÿé¨“ã—ã¦ã¿ã¾ã—ãŸã€‚ãƒãƒƒãƒå‡¦ç†ãªã©ã®ã‚¹ã‚¯ãƒªãƒ—ãƒˆã¯Pythonã‚’ä½¿ã£ã¦ã¾ã™ãŒã€Perlã§ã‚‚Rubyã§ã‚‚ä¼¼ãŸã‚ˆã†ãªæ„Ÿã˜ã§ã§ãã¾ã™ã€‚ æŒ‡å®šã—ãŸç”»åƒã¨é¡žä¼¼ã—ãŸç”»åƒã‚’æ¤œç´¢ã™ã‚‹ã‚·ã‚¹ãƒ†ãƒ ã¯é¡žä¼¼ç”»åƒæ¤œç´¢ã‚·ã‚¹ãƒ†ãƒ ã¨è¨€ã„ã¾ã™ã€‚Googleã‚„Yahoo!ã®ã‚¤ãƒ¡ãƒ¼ã‚¸æ¤œç´¢ã¯ã€ã‚¯ã‚¨ãƒªã«ã‚ãƒ¼ãƒ¯ãƒ¼ãƒ‰ã‚’å…¥ã‚Œã¦ã‚ãƒ¼ãƒ¯ãƒ¼ãƒ‰ã«é–¢é€£ã—ãŸç”»åƒã‚’æ¤œç´¢ã—ã¾ã™ãŒã€é¡žä¼¼ç”»åƒæ¤œç´¢ã§ã¯ã‚¯ã‚¨ãƒªã«ç”»åƒã‚’ä¸Žãˆã‚‹ã®ãŒç‰¹å¾´çš„ã§ã™ã€‚ã“ã®åˆ†é‡Žã¯ã€Content-Based Image Retrieval (CBIR)ã¨å‘¼ã°ã‚Œã¦ãŠã‚Šã€æœ€æ–°ã®ã‚µãƒ¼ãƒ™ã‚¤è«–æ–‡ï¼ˆDatta,2008ï¼‰ã‚’èªã‚€ã¨1990å¹´ä»£å‰åŠã¨ã‘ã£ã“ã†æ˜”ã‹ã‚‰ç ”ç©¶ã•ã‚Œã¦ã¾ã™ã€‚ æœ€æ–°ã®æ‰‹æ³•ã§ã¯ã€è‰²ã€å½¢çŠ¶ã€ãƒ†ã‚¯ã‚¹ãƒãƒ£ã€ç‰¹å¾´ç‚¹ãªã©ã•ã¾ã–ã¾ãªç‰¹å¾´é‡ã‚’ç”¨ã„ã¦é¡žä¼¼åº¦ã‚’åˆ¤å®šã™ã‚‹ãã†ã§ã™ãŒã€ä»Šå›žã¯ã€ã‚‚ã£ã¨ã‚‚ç°¡å˜ãªã€Œè‰²ã€ã‚’ç”¨ã„ãŸé¡žä¼¼ç”»åƒæ¤œç´¢ã‚’å®Ÿé¨“ã—ã¦ã¿ã¾ã™
nilab 2009/10/13
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imageprocessing
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osakana.factory - ã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ«ã®ã²ã¿ã¤
Adobe PhotoShop ã§ RGB ãƒ¢ãƒ¼ãƒ‰ã®ç”»åƒã‚’ 256 éšŽèª¿ã®ã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ«ã¸å¤‰æ›ã™ã‚‹æ–¹æ³•ã¯ã€1 é€šã‚Šã§ã¯ã‚ã‚Šã¾ã›ã‚“ã€‚ã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ«ã¸ã®å¤‰æ›ã‚³ãƒžãƒ³ãƒ‰ã¯ã€ã‚¬ãƒ³ãƒžã‚„è‰²ç©ºé–“ãªã©ã®æ¦‚å¿µãŒçµ¡ã¿åˆã£ã¦ã„ã¦ã€çµæ§‹è¤‡é›‘ã§ã™ã€‚ä»•çµ„ã¿ã‚’ç†è§£ã—ã¦ã„ãªã‹ã£ãŸãŸã‚ã«ã€ãƒ¢ãƒ¼ãƒ‰ ãƒ¡ãƒ‹ãƒ¥ãƒ¼ã‹ã‚‰ ã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ« ã‚’é¸ã‚“ã§ã‚‚æœ›ã‚“ã ã‚ˆã†ãªçµæžœãŒå¾—ã‚‰ã‚Œãªã‹ã£ãŸã‚Šã€ä¸é©åˆ‡ã«å½©åº¦ã‚’å–ã‚Šé™¤ã„ã¦ç”»åƒã®éšŽèª¿ã‚’æ½°ã—ã¦ã—ã¾ã†ã¨ã„ã†ã‚ˆã†ãªã“ã¨ã‚‚è€ƒãˆã‚‰ã‚Œã¾ã™ã€‚ã“ã“ã§ã¯ã€ä½•é€šã‚Šã‹ã®ã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ«åŒ–æ–¹æ³•ã‚’ã€è¨ˆç®—å¼ã‹ã‚‰è€ƒãˆã¦ã„ããŸã„ã¨æ€ã„ã¾ã™ã€‚è¨ˆç®—å¼ã¯ã€PhotoShop ä»¥å¤–ã®ä¸€èˆ¬çš„ãªç”»åƒå‡¦ç†ã§ã‚‚åˆ©ç”¨ã§ãã‚‹æ±Žç”¨çš„ãªã‚‚ã®ã§ã™ã€‚
nilab 2009/09/07
osakana.factory - ã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ«ã®ã²ã¿ã¤ : ã„ã‚ã„ã‚ãªã‚°ãƒ¬ãƒ¼ã‚¹ã‚±ãƒ¼ãƒ«å¤‰æ›æ–¹æ³•

imageprocessing

graphics
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nilab 2009/07/27
ãŠæŽƒé™¤ãƒãƒœãƒƒãƒˆãƒ«ãƒ³ãƒã®æŽƒé™¤çµŒè·¯ã‚’æ’®å½±ã™ã‚‹ãƒ—ãƒã‚°ãƒ©ãƒ ã‚’ã¤ãã£ã¦ã¿ãŸ:ã€Œãƒ•ã‚©ãƒ«ãƒ€ä»¥ä¸‹ã®å…¨ã¦ã®ãƒ•ã‚¡ã‚¤ãƒ«åŒå£«ã‚’ãƒ”ã‚¯ã‚»ãƒ«å˜ä½ã§æ¯”è¼ƒã—ã€ç›¸é•ãŒã‚ã‚Œã°åˆæˆã—ã¦å‡ºåŠ›ã—ã¦ã€æœ€çµ‚çš„ã«ä¸€æžšã®ç”»åƒãƒ•ã‚¡ã‚¤ãƒ«ã‚’ç”Ÿæˆã€

imageprocessing
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Scene Completion Using Millions of Photographs
People James Hays Alexei Efros Abstract What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images
nilab 2009/06/30
Scene Completion Using Millions of Photographs:James Hays, Alexei A. Efros. Scene Completion Using Millions of Photographs. ACM Transactions on Graphics (SIGGRAPH 2007). August 2007, vol. 26, No. 3.

imageprocessing

photo
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