OpenFace
Free and open source face recognition with deep neural networks. News 2016-09-15: We presented OpenFace in the Data (after)Lives art exhibit at the University of Pittsburgh and have released the code as Demo 4: Real-time Face Embedding Visualization. 2016-08-09: New blog post: (Face) Image Completion with Deep Learning in TensorFlow. (OpenFace group discussion on it) 2016-06-01: OpenFace tech repo
Colorful Image Colorization
Example input grayscale photos and output colorizations from our algorithm. These examples are cases where our model works especially well. For randomly selected examples, see the Performance comparisons section below. Welcome! Computer vision algorithms often work well on some images, but fail on others. Ours is like this too. We believe our work is a significant step forward in solving the color
GitHub - kjw0612/awesome-deep-vision: A curated list of deep learning resources for computer vision
(from Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton, ImageNet Classification with Deep Convolutional Neural Networks, NIPS, 2012.) Microsoft (Deep Residual Learning) [Paper][Slide] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Deep Residual Learning for Image Recognition, arXiv:1512.03385. Microsoft (PReLu/Weight Initialization) [Paper] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun,
Using convolutional neural nets to detect facial keypoints tutorial — Daniel Nouri's Blog
This is a hands-on tutorial on deep learning. Step by step, we'll go about building a solution for the Facial Keypoint Detection Kaggle challenge. The tutorial introduces Lasagne, a new library for building neural networks with Python and Theano. We'll use Lasagne to implement a couple of network architectures, talk about data augmentation, dropout, the importance of momentum, and pre-training. So
Perceptual Hash - stMind
Perceptual Hashã¯ã€ç”»åƒãªã©ã®ãƒ¡ãƒ‡ã‚£ã‚¢ãƒ‡ãƒ¼ã‚¿ã®ãƒãƒƒã‚·ãƒ¥ã‚’計算ã™ã‚‹ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ 群ã§ã™ã€‚ SHA-1ã‚„MD5ã¨ã¯ç•°ãªã‚Šã€ç”»åƒã‚µã‚¤ã‚ºã®é•ã„や回転ãªã©ã®å¤‰æ›ã§ç”»åƒãŒå…¨ãåŒä¸€ã§ãªã„å ´åˆã§ã‚‚ã€å…ƒç”»åƒã¨åŒã˜ãƒãƒƒã‚·ãƒ¥å€¤ã‚’計算ã—ã¦ãã‚Œã¾ã™ã€‚ ã©ã‚“ãªã“ã¨ã«ä½¿ã‚ã‚Œã¦ã„ã‚‹ã®ã‹ï¼Ÿ アプリケーションã¨ã—ã¦ã¯æ¬¡ã®ã‚ˆã†ãªã‚‚ã®ãŒã‚ã‚Šã¾ã™ã€‚ コンテンツã®é‡è¤‡æ¤œå‡º Iconfinderã§ã¯ã€ã‚¢ã‚¤ã‚³ãƒ³ç”»åƒã®ã‚¢ãƒƒãƒ—ãƒãƒ¼ãƒ‰æ™‚ã«dHashを用ã„ã¦ç™»éŒ²æ¸ˆã¿ã‚¢ã‚¤ã‚³ãƒ³ã¨ã®é‡è¤‡ã‚’検出ã™ã‚‹æ©Ÿèƒ½ã‚’é–‹ç™ºä¸ Youtubeã§ã¯ãƒ¦ãƒ¼ã‚¶ã®ã‚¢ãƒƒãƒ—ãƒãƒ¼ãƒ‰ã—ãŸå‹•ç”»ã¨ã€ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã«ã‚る著作権ã‚り動画を比較ã—ã€é•æ³•ã‚¢ãƒƒãƒ—ãƒãƒ¼ãƒ‰ã‚’検出 Dropboxã®Carouselã§ã¯ã€ãƒãƒ¼ã‚«ãƒ«ã®ãƒ•ã‚¡ã‚¤ãƒ«ã‹ã‚‰ãƒãƒƒã‚·ãƒ¥å€¤ã‚’計算ã—ã€ã‚µãƒ¼ãƒå´ã«ãƒãƒƒã‚¯ã‚¢ãƒƒãƒ—ã—ã¦ã„ãªã„ファイルを判定ã—ã¦ã„るよㆠ類似画åƒæ¤œç´¢ TinEye.com Google Image Search ã‚¢
Finding Matching Images in Python using Corner Detection - Gary Sieling
I’m working through Programming Computer Vision with Python: Tools and algorithms for analyzing images, which covers various mechanisms for determining corresponding methods to match points of interest between two interest. In the book, this eventually builds up to an instruction on how to reconstruct a panorama. The first technique for finding corresponding points of interest looks for corners in
ccv - a modern computer vision library
A Modern Computer Vision Library View the Project on GitHub liuliu/ccv Download ZIP File Download TAR Ball Fork On GitHub with a sub-10% image classifier, a decent face detector, here comes ccv 0.7 › Backstory I set to build ccv with a minimalism inspiration. That was back in 2010, out of the frustration with the computer vision library then I was using, ccv was meant to be a much easier to deploy
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SimpleCV
What is it? SimpleCV is an open source framework for building computer vision applications. With it, you get access to several high-powered computer vision libraries such as OpenCV – without having to first learn about bit depths, file formats, color spaces, buffer management, eigenvalues, or matrix versus bitmap storage. This is computer vision made easy. from SimpleCV import Camera # Initialize
実践 コンピュータビジョン
コンピュータビジョンã®ç†è«–ã¨ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ を基礎ã‹ã‚‰å¦ã¹ã‚‹å®Ÿè·µçš„ãªå…¥é–€æ›¸ã€‚ç†è«–ã®èª¬æ˜Žã«ã¨ã©ã¾ã‚‰ãšã€ãƒ™ã‚¯ãƒˆãƒ«æ¼”算や行列演算を駆使ã—ãŸã‚µãƒ³ãƒ—ルを示ã—ãªãŒã‚‰ç‰©ä½“èªè˜ã€3次元復元ã€ã‚¹ãƒ†ãƒ¬ã‚ªç”»åƒã€æ‹¡å¼µç¾å®Ÿæ„Ÿã€ãã®ä»–ã®å¿œç”¨ã«ã¤ã„ã¦è§£èª¬ã—ã¾ã™ã€‚サンプルプãƒã‚°ãƒ©ãƒ ã¯Python 2.7ã§æ›¸ã‹ã‚Œã¦ã„ã¾ã™ã€‚OpenCVを使ã†ã ã‘ã§ã¯ã‚³ãƒ³ãƒ”ュータビジョンã®æœ¬è³ªã‚’ç†è§£ã§ãã¾ã›ã‚“。forループã§ãƒ”クセルをæ“作ã—行列を計算ã™ã‚‹æ™‚代ã§ã‚‚ã‚ã‚Šã¾ã›ã‚“。Pythonã®æ•°å€¤æ¼”算ライブラリを使ãˆã°ã€ã»ã©ã‚ˆã„粒度ã§ã‚³ãƒ³ãƒ”ュータビジョンã®åŸºç¤Žã‚’å¦ã¹ã¾ã™ã€‚å„ç« æœ«ã«ã¯æ¼”ç¿’å•é¡ŒãŒç”¨æ„ã—ã¦ã‚ã‚Šã¾ã™ã€‚演習å•é¡Œã‚’解ãã“ã¨ã§è‡ªåˆ†ãŒãã®ç« ã§ä½•ã‚’å¦ã‚“ã ã®ã‹ã€ã¾ãŸè‡ªåˆ†ã®ç†è§£åº¦ã‚’確èªã§ãã¾ã™ã€‚ â—本書ã§æ‰±ã†ã‚µãƒ³ãƒ—ルプãƒã‚°ãƒ©ãƒ ã®èª¬æ˜Žï¼ˆã‚µãƒ³ãƒ—ルコードã¯ã€Œé–¢é€£ãƒ•ã‚¡ã‚¤ãƒ«ã€ã‚¿ãƒ–ページã‹ã‚‰ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰å¯ï¼‰ã€‚ 翻訳者ã®ç›¸å·æ°ã®ãƒ–ãƒã‚°ã«ã¯ã€æœ¬æ›¸ã®è¿½åŠ æƒ…å ±ã‚„é–¢é€£ã™ã‚‹æŠ€è¡“æƒ…å ±
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GitHub - jesolem/PCV: Open source Python module for computer vision
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