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diff --git a/site/public/about/credits/index.html b/site/public/about/credits/index.html index 6e4f06c1..7f3da564 100644 --- a/site/public/about/credits/index.html +++ b/site/public/about/credits/index.html @@ -36,14 +36,7 @@ <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</div><ul> -<li>MegaPixels by Adam Harvey</li> -<li>Made with support from Mozilla</li> -<li>Site developed by Jules Laplace</li> -<li>Design and graphics: Adam Harvey</li> -<li>Research assistants: Berit Gilma</li> -</ul> -</section> +</div></section> </div> <footer> diff --git a/site/public/about/disclaimer/index.html b/site/public/about/disclaimer/index.html index b93194fa..2f915c48 100644 --- a/site/public/about/disclaimer/index.html +++ b/site/public/about/disclaimer/index.html @@ -25,18 +25,17 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-about"> <section><h1>Disclaimer</h1> -</section><section><div class='right-sidebar'><ul> +<ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> -<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</div><p>Last updated: December 04, 2018</p> +</section><section><p>Last updated: December 04, 2018</p> <p>The information contained on MegaPixels.cc website (the "Service") is for academic and artistic purposes only.</p> <p>MegaPixels.cc assumes no responsibility for errors or omissions in the contents on the Service.</p> <p>In no event shall MegaPixels.cc be liable for any special, direct, indirect, consequential, or incidental damages or any damages whatsoever, whether in an action of contract, negligence or other tort, arising out of or in connection with the use of the Service or the contents of the Service. MegaPixels.cc reserves the right to make additions, deletions, or modification to the contents on the Service at any time without prior notice.</p> diff --git a/site/public/about/index.html b/site/public/about/index.html index 8583fd96..ed80691a 100644 --- a/site/public/about/index.html +++ b/site/public/about/index.html @@ -25,21 +25,16 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-about"> - <section><h1>About MegaPixels</h1> -</section><section><div class='right-sidebar'><ul> -<li><a href="/about/press/">Press</a></li> -<li><a href="/about/credits/">Credits</a></li> -<li><a href="/about/disclaimer/">Disclaimer</a></li> -<li><a href="/about/terms/">Terms and Conditions</a></li> -<li><a href="/about/privacy/">Privacy Policy</a></li> -</ul> -<div class='meta'><div><div class='gray'>Years</div><div>2002-2019</div></div><div><div class='gray'>Datasets Analyzed</div><div>325</div></div><div><div class='gray'>Author</div><div>Adam Harvey</div></div><div><div class='gray'>Development</div><div>Jules LaPlace</div></div><div><div class='gray'>Research Assistance</div><div>Berit Gilma</div></div></div></div><p>MegaPixels aims to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> -<p>MegaPixels aims to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> + <section><h1>About This Project</h1> +</section><section class="about-menu"><ul><li><a href="/about/">About</a></li><li><a href="/about/press/">Press</a></li><li><a href="/about/research/">Research Methodology</a></li><li><a href="/about/disclaimer/">Disclaimer</a></li><li><a href="/about/terms/">Terms and Conditions</a></li><li><a href="/about/privacy/">Privacy Policy</a></li></ul></section><section><p>MegaPixels is an art and research project by Adam Harvey about the origins and ethics of facial analysis datasets. Where do they come from? Who's included? Who created it and for what reason?</p> +<p>MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> +<p>MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> </section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/adam-harvey.jpg' alt='Adam Harvey'><div><p><strong>Adam Harvey</strong> is an American artist and researcher based in Berlin. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund awards, and is currently a researcher in residence at Karlsruhe HfG studying artifical intelligence and datasets.</p> </div></div></section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/jules-laplace.jpg' alt='Jules LaPlace'><div><p><strong>Jules LaPlace</strong> is an American artist and technologist also based in Berlin. He was previously the CTO of a NYC digital agency and currently works at VFRAME, developing computer vision for human rights groups, and building creative software for artists.</p> -</div></div></section><section><p><strong>Mozilla</strong> is a free software community founded in 1998 by members of Netscape. The Mozilla community uses, develops, spreads and supports Mozilla products, thereby promoting exclusively free software and open standards, with only minor exceptions. The community is supported institutionally by the not-for-profit Mozilla Foundation and its tax-paying subsidiary, the Mozilla Corporation.</p> +</div></div></section><section><h2>Partnership</h2> +<p>MegaPixels is produced in partnership with <strong>Mozilla</strong>, a free software community founded in 1998 by members of Netscape. The Mozilla community uses, develops, spreads and supports Mozilla products, thereby promoting exclusively free software and open standards, with only minor exceptions. The community is supported institutionally by the not-for-profit Mozilla Foundation and its tax-paying subsidiary, the Mozilla Corporation.</p> </section> </div> diff --git a/site/public/about/press/index.html b/site/public/about/press/index.html index d36b6bc6..0791d2a2 100644 --- a/site/public/about/press/index.html +++ b/site/public/about/press/index.html @@ -25,22 +25,19 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-about"> <section><h1>Press</h1> -</section><section><div class='right-sidebar'><ul> +<ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> -<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/test.jpg' alt='alt text'><div class='caption'>alt text</div></div></section><section><ul> +</section><section><p>(list of press articles and images will go here)</p> +<ul> <li>Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset</a></li> -<li>Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset</a></li> -<li>Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset</a> -lfw</li> </ul> </section> diff --git a/site/public/about/privacy/index.html b/site/public/about/privacy/index.html index 1b3b9d2f..1d9b2252 100644 --- a/site/public/about/privacy/index.html +++ b/site/public/about/privacy/index.html @@ -25,18 +25,17 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-about"> <section><h1>Privacy Policy</h1> -</section><section><div class='right-sidebar'><ul> +<ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> -<li><a href="/about/credits/">Credits</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</div><p>A summary of our privacy policy is as follows:</p> +<p>A summary of our privacy policy is as follows:</p> <p>The MegaPixels site does not use any analytics programs or collect any data besides the necessary IP address of your connection, which are deleted every 30 days and used only for security and to prevent misuse.</p> <p>The image processing sections of the site do not collect any data whatsoever. All processing takes place in temporary memory (RAM) and then is displayed back to the user over a SSL secured HTTPS connection. It is the sole responsibility of the user whether they discard, by closing the page, or share their analyzed information and any potential consequences that may arise from doing so.</p> <p>A more complete legal version is below:</p> diff --git a/site/public/test/search_face/index.html b/site/public/about/research/index.html index 86123c1c..94b4e2ee 100644 --- a/site/public/test/search_face/index.html +++ b/site/public/about/research/index.html @@ -3,13 +3,14 @@ <head> <title>MegaPixels</title> <meta charset="utf-8" /> - <meta name="author" content="Megapixels" /> - <meta name="description" content="Face Search Test" /> + <meta name="author" content="Adam Harvey" /> + <meta name="description" content="About MegaPixels Research Methodologies" /> <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> <link rel='stylesheet' href='/assets/css/tabulator.css' /> <link rel='stylesheet' href='/assets/css/css.css' /> + <link rel='stylesheet' href='/assets/css/leaflet.css' /> <link rel='stylesheet' href='/assets/css/applets.css' /> </head> <body> @@ -17,7 +18,6 @@ <a class='slogan' href="/"> <div class='logo'></div> <div class='site_name'>MegaPixels</div> - <span class='sub'>The Darkside of Datasets</span> </a> <div class='links'> <a href="/datasets/">Datasets</a> @@ -25,9 +25,17 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-about"> - <section><p><code></code></p> + <section><h1>Research Methodologies</h1> +<ul> +<li><a href="/about/">About</a></li> +<li><a href="/about/press/">Press</a></li> +<li><a href="/about/research/">Research Methodology</a></li> +<li><a href="/about/disclaimer/">Disclaimer</a></li> +<li><a href="/about/terms/">Terms and Conditions</a></li> +<li><a href="/about/privacy/">Privacy Policy</a></li> +</ul> </section> </div> diff --git a/site/public/about/terms/index.html b/site/public/about/terms/index.html index 8bd6e738..650366e0 100644 --- a/site/public/about/terms/index.html +++ b/site/public/about/terms/index.html @@ -25,18 +25,20 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-about"> <section><h1>Terms and Conditions ("Terms")</h1> -</section><section><div class='right-sidebar'><ul> +</section><section><div class='left-sidebar'><ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> <li><a href="/about/credits/">Credits</a></li> +<li><a href="/about/research/">Research Methodology</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</div><p>Last updated: December 04, 2018</p> +</div><p>(FPO: this is only example text)</p> +<p>Last updated: December 04, 2018</p> <p>Please read these Terms and Conditions ("Terms", "Terms and Conditions") carefully before using the MegaPixels website (the "Service") operated by megapixels.cc ("us", "we", or "our").</p> <p>Your access to and use of the Service is conditioned on your acceptance of and compliance with these Terms.</p> <p>By accessing or using the Service you agree to be bound by these Terms. If you disagree with any part of the terms then you may not access the Service.</p> diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index 7398da17..9cd50016 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -25,34 +25,19 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>Facial Recognition Datasets</h1> -</section><section><div class='meta'><div><div class='gray'>Found</div><div>275 datasets</div></div><div><div class='gray'>Created between</div><div>1993-2018</div></div><div><div class='gray'>Smallest dataset</div><div>20 images</div></div><div><div class='gray'>Largest dataset</div><div>10,000,000 images</div></div></div><section><section><div class='meta'><div><div class='gray'>Highest resolution faces</div><div>450x500 (Unconstrained College Students)</div></div><div><div class='gray'>Lowest resolution faces</div><div>16x20 pixels (QMUL SurvFace)</div></div></div><section> +</section> <section class='wide dataset-intro'> - <p> - We have prepared detailed case studies of some of the more noteworthy datasets, including tools to help you learn what is contained in these datasets, and even whether your own face has been used to train these algorithms. - </p> <div class="dataset-list"> - <a href="/datasets/afad/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/afad/assets/index.jpg)"> + <a href="/datasets/brainwash/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/index.jpg)"> <div class="dataset"> - <span>Asian Face Age Dataset</span> - </div> - </a> - - <a href="/datasets/aflw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/aflw/assets/index.jpg)"> - <div class="dataset"> - <span>Annotated Facial Landmarks in The Wild</span> - </div> - </a> - - <a href="/datasets/caltech_10k/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/caltech_10k/assets/index.jpg)"> - <div class="dataset"> - <span>Caltech 10K Faces Dataset</span> + <span>Brainwash</span> </div> </a> @@ -62,48 +47,12 @@ </div> </a> - <a href="/datasets/facebook/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/facebook/assets/index.jpg)"> - <div class="dataset"> - <span>Facebook</span> - </div> - </a> - - <a href="/datasets/feret/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/feret/assets/index.jpg)"> - <div class="dataset"> - <span>FERET: FacE REcognition </span> - </div> - </a> - - <a href="/datasets/lfpw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfpw/assets/index.jpg)"> - <div class="dataset"> - <span>Labeled Face Parts in The Wild</span> - </div> - </a> - <a href="/datasets/lfw/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/index.jpg)"> <div class="dataset"> <span>Labeled Faces in The Wild</span> </div> </a> - <a href="/datasets/uccs/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/index.jpg)"> - <div class="dataset"> - <span>Unconstrained College Students</span> - </div> - </a> - - <a href="/datasets/vgg_face2/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/vgg_face2/assets/index.jpg)"> - <div class="dataset"> - <span>VGG Face 2 Dataset</span> - </div> - </a> - - <a href="/datasets/youtube_celebrities/" style="background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/youtube_celebrities/assets/index.jpg)"> - <div class="dataset"> - <span>YouTube Celebrities</span> - </div> - </a> - </div> </section> diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 5b5e58f3..e90cdcc5 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -4,7 +4,7 @@ <title>MegaPixels</title> <meta charset="utf-8" /> <meta name="author" content="Adam Harvey" /> - <meta name="description" content="Labeled Faces in The Wild (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition." /> + <meta name="description" content="<span style="color:#ff0000">Labeled Faces in The Wild (LFW)</span> is a database of face photographs designed for studying the problem of unconstrained face recognition." /> <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> @@ -25,44 +25,36 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> - <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span><span style='color: #ff0000'>Labeled Faces in The Wild</span> (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition.</span></div><div class='hero_subdesc'><span>It includes 13,456 images of 4,432 people’s images copied from the Internet during 2002-2004. -</span></div></div></section><section><div class='image'><div class='caption'>A few of the 5,749 people in the Labeled Faces in the Wild Dataset. The most widely used face dataset for benchmarking commercial face recognition algorithms.</div></div></section><section><div class='right-sidebar'><h3>Statistics</h3> -<div class='meta'><div><div class='gray'>Years</div><div>2002-2004</div></div><div><div class='gray'>Images</div><div>13,233</div></div><div><div class='gray'>Identities</div><div>5,749</div></div><div><div class='gray'>Origin</div><div>Yahoo News Images</div></div><div><div class='gray'>Funding</div><div>(Possibly, partially CIA)</div></div></div><h3>INSIGHTS</h3> -<ul> -<li>There are about 3 men for every 1 woman (4,277 men and 1,472 women) in the LFW dataset<a class="footnote_shim" name="[^lfw_www]_1"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a></li> + <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span><span style="color:#ff0000">Labeled Faces in The Wild (LFW)</span> is a database of face photographs designed for studying the problem of unconstrained face recognition.</span></div><div class='hero_subdesc'><span>It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004. +</span></div></div></section><section><div class='image'><div class='intro-caption caption'>A few of the 5,749 people in the Labeled Faces in the Wild Dataset, thee most widely used face dataset for benchmarking face recognition algorithms.</div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Created</div><div>2002-2004</div></div><div><div class='gray'>Images</div><div>13,233</div></div><div><div class='gray'>Identities</div><div>5,749</div></div><div><div class='gray'>Origin</div><div>Yahoo! News Images</div></div><div><div class='gray'>Used by</div><div>Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA</div></div><div><div class='gray'>Website</div><div><a href="http://vis-www.cs.umass.edu/lfw">vis-www.cs.umass.edu/lfw</a></div></div></div><ul> +<li>There are about 3 men for every 1 woman in the LFW dataset<a class="footnote_shim" name="[^lfw_www]_1"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a></li> <li>The person with the most images is <a href="http://vis-www.cs.umass.edu/lfw/person/George_W_Bush_comp.html">George W. Bush</a> with 530</li> <li>There are about 3 George W. Bush's for every 1 <a href="http://vis-www.cs.umass.edu/lfw/person/Tony_Blair.html">Tony Blair</a></li> <li>The LFW dataset includes over 500 actors, 30 models, 10 presidents, 124 basketball players, 24 football players, 11 kings, 7 queens, and 1 <a href="http://vis-www.cs.umass.edu/lfw/person/Moby.html">Moby</a></li> <li>In all 3 of the LFW publications [^lfw_original_paper], [^lfw_survey], [^lfw_tech_report] the words "ethics", "consent", and "privacy" appear 0 times</li> <li>The word "future" appears 71 times</li> +<li>* denotes partial funding for related research</li> </ul> </div><h2>Labeled Faces in the Wild</h2> <p><em>Labeled Faces in The Wild</em> (LFW) is "a database of face photographs designed for studying the problem of unconstrained face recognition<a class="footnote_shim" name="[^lfw_www]_2"> </a><a href="#[^lfw_www]" class="footnote" title="Footnote 1">1</a>. It is used to evaluate and improve the performance of facial recognition algorithms in academic, commercial, and government research. According to BiometricUpdate.com<a class="footnote_shim" name="[^lfw_pingan]_1"> </a><a href="#[^lfw_pingan]" class="footnote" title="Footnote 3">3</a>, LFW is "the most widely used evaluation set in the field of facial recognition, LFW attracts a few dozen teams from around the globe including Google, Facebook, Microsoft Research Asia, Baidu, Tencent, SenseTime, Face++ and Chinese University of Hong Kong."</p> <p>The LFW dataset includes 13,233 images of 5,749 people that were collected between 2002-2004. LFW is a subset of <em>Names of Faces</em> and is part of the first facial recognition training dataset created entirely from images appearing on the Internet. The people appearing in LFW are...</p> <p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> -<h3>Biometric Trade Routes</h3> -<p>To understand how this dataset has been used, its citations have been geocoded to show an approximate geographic digital trade route of the biometric data. Lines indicate an organization (education, commercial, or governmental) that has cited the LFW dataset in their research. Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a>.</p> -</section><section class='applet_container'><div class='applet' data-payload='{"command": "map"}'></div></section><section><h3>Synthetic Faces</h3> -<p>To visualize the types of photos in the dataset without explicitly publishing individual's identities a generative adversarial network (GAN) was trained on the entire dataset. The images in this video show a neural network learning the visual latent space and then interpolating between archetypical identities within the LFW dataset.</p> -</section><section class='fullwidth'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_synthetic.jpg' alt=''></div></section><section><h3>Citations</h3> -<p>Browse or download the geocoded citation data collected for the LFW dataset.</p> -</section><section class='applet_container'><div class='applet' data-payload='{"command": "citations"}'></div></section><section><h3>Additional Information</h3> -<p>(tweet-sized snippets go here)</p> -<ul> -<li>The LFW dataset is considered the "most popular benchmark for face recognition" <a class="footnote_shim" name="[^lfw_baidu]_1"> </a><a href="#[^lfw_baidu]" class="footnote" title="Footnote 2">2</a></li> -<li>The LFW dataset is "the most widely used evaluation set in the field of facial recognition" <a class="footnote_shim" name="[^lfw_pingan]_2"> </a><a href="#[^lfw_pingan]" class="footnote" title="Footnote 3">3</a></li> -<li>All images in LFW dataset were obtained "in the wild" meaning without any consent from the subject or from the photographer</li> -<li>The faces in the LFW dataset were detected using the Viola-Jones haarcascade face detector [^lfw_website] [^lfw-survey]</li> -<li>The LFW dataset is used by several of the largest tech companies in the world including "Google, Facebook, Microsoft Research Asia, Baidu, Tencent, SenseTime, Face++ and Chinese University of Hong Kong." <a class="footnote_shim" name="[^lfw_pingan]_3"> </a><a href="#[^lfw_pingan]" class="footnote" title="Footnote 3">3</a></li> -<li>All images in the LFW dataset were copied from Yahoo News between 2002 - 2004</li> -<li>In 2014, two of the four original authors of the LFW dataset received funding from IARPA and ODNI for their followup paper <a href="https://www.semanticscholar.org/paper/Labeled-Faces-in-the-Wild-%3A-Updates-and-New-Huang-Learned-Miller/2d3482dcff69c7417c7b933f22de606a0e8e42d4">Labeled Faces in the Wild: Updates and New Reporting Procedures</a> via IARPA contract number 2014-14071600010</li> -<li>The dataset includes 2 images of <a href="http://vis-www.cs.umass.edu/lfw/person/George_Tenet.html">George Tenet</a>, the former Director of Central Intelligence (DCI) for the Central Intelligence Agency whose facial biometrics were eventually used to help train facial recognition software in China and Russia</li> -</ul> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_montage_top1_640.jpg' alt=' former President George W. Bush'><div class='caption'> former President George W. Bush</div></div> -<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_montage_top2_4_640.jpg' alt=' Colin Powell (236), Tony Blair (144), and Donald Rumsfeld (121)'><div class='caption'> Colin Powell (236), Tony Blair (144), and Donald Rumsfeld (121)</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_montage_all_crop.jpg' alt='All 5,379 faces in the Labeled Faces in The Wild Dataset'><div class='caption'>All 5,379 faces in the Labeled Faces in The Wild Dataset</div></div></section><section><h2>Code</h2> -<p>The LFW dataset is so widely used that a popular code library called Sci-Kit Learn includes a function called <code>fetch_lfw_people</code> to download the faces in the LFW dataset.</p> +<p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> +</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/lfw_montage_all_crop.jpg' alt='All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person'><div class='caption'>All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person</div></div></section><section><p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> +<p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> +</section><section> <h3>Biometric Trade Routes</h3><!-- <div class="map-sidebar right-sidebar"> <h3>Legend</h3> <ul> <li><span style="color: #f2f293">■</span> Industry</li> <li><span style="color: #f30000">■</span> Academic</li> <li><span style="color: #3264f6">■</span> Government</li> </ul> </div> --> <p> To understand how this dataset has been used, its citations have been geocoded to show an approximate geographic digital trade route of the biometric data. Lines indicate an organization (education, commercial, or governmental) that has cited the LFW dataset in their research. Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a>. </p> </section><section class="applet_container"> <div class="applet" data-payload="{"command": "map"}"></div></section><div class="caption"> <div class="map-legend-item"><span class="edu">■</span> Academic</div> <div class="map-legend-item"><span class="com">■</span> Industry</div> <div class="map-legend-item"><span class="gov">■</span> Government</div></div><section><p>Sed ut perspiciatis, unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam eaque ipsa, quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt, explicabo. Nemo enim ipsam voluptatem, quia voluptas sit, aspernatur aut odit aut fugit, sed quia.</p> +<hr class="supp"> + +<h2>Supplementary Information for Labeled Faces in The Wild</h2> +</section><section class="applet_container"> <h3>Citations</h3> <p>Add graph showing distribution by country. Add information about how the citations were generated. Add button/link to download CSV</p> <div class="applet" data-payload="{"command": "citations"}"></div></section><section> <h3>Synthetic Faces</h3> <p>To visualize the types of photos in the dataset without explicitly publishing individual's identities a generative adversarial network (GAN) was trained on the entire dataset. The images in this video show a neural network learning the visual latent space and then interpolating between archetypical identities within the LFW dataset.</p></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/synthetic_01.jpg' alt='Synthetically generated face from the visual space of LFW dataset'><div class='caption'>Synthetically generated face from the visual space of LFW dataset</div></div> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/synthetic_02.jpg' alt='Synthetically generated face from the visual space of LFW dataset'><div class='caption'>Synthetically generated face from the visual space of LFW dataset</div></div> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/synthetic_03.jpg' alt='Synthetically generated face from the visual space of LFW dataset'><div class='caption'>Synthetically generated face from the visual space of LFW dataset</div></div> +<div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/synthetic_01.jpg' alt='Synthetically generated face from the visual space of LFW dataset'><div class='caption'>Synthetically generated face from the visual space of LFW dataset</div></div></section><section><h3>Commercial Use of Labeled Faces in The Wild</h3> +<p>Add a paragraph about how usage extends far beyond academia into research centers for largest companies in the world. And even funnels into CIA funded research in the US and defense industry usage in China.</p> +</section><section class='applet_container'><div class='applet' data-payload='{"command": "load_file assets/lfw_commercial_use.csv", "fields": ["name_display, company_url, example_url, country, description"]}'></div></section><section><h3>Code</h3> +<p>The LFW dataset is so widely used that access to the facial data has built directly into a popular code library called Sci-Kit Learn. It includes a function called <code>fetch_lfw_people</code> to download the faces in the LFW dataset.</p> </section><section><pre><code class="lang-python">#!/usr/bin/python import numpy as np @@ -92,11 +84,10 @@ imageio.imwrite('lfw_montage_full.png', montage) montage = imutils.resize(montage, width=960) imageio.imwrite('lfw_montage_960.jpg', montage) </code></pre> -</section><section><h3>Supplementary Material</h3> -</section><section class='applet_container'><div class='applet' data-payload='{"command": "load_file assets/lfw_commercial_use.csv", "fields": ["name_display, company_url, example_url, country, description"]}'></div></section><section><p>Text and graphics ©Adam Harvey / megapixels.cc</p> +</section><section><p>Research, text, and graphics ©Adam Harvey / megapixels.cc</p> </section><section><ul class="footnotes"><li><a name="[^lfw_www]" class="footnote_shim"></a><span class="backlinks"><a href="#[^lfw_www]_1">a</a><a href="#[^lfw_www]_2">b</a></span><p><a href="http://vis-www.cs.umass.edu/lfw/results.html">http://vis-www.cs.umass.edu/lfw/results.html</a></p> -</li><li><a name="[^lfw_baidu]" class="footnote_shim"></a><span class="backlinks"><a href="#[^lfw_baidu]_1">a</a></span><p>Jingtuo Liu, Yafeng Deng, Tao Bai, Zhengping Wei, Chang Huang. Targeting Ultimate Accuracy: Face Recognition via Deep Embedding. <a href="https://arxiv.org/abs/1506.07310">https://arxiv.org/abs/1506.07310</a></p> -</li><li><a name="[^lfw_pingan]" class="footnote_shim"></a><span class="backlinks"><a href="#[^lfw_pingan]_1">a</a><a href="#[^lfw_pingan]_2">b</a><a href="#[^lfw_pingan]_3">c</a></span><p>Lee, Justin. "PING AN Tech facial recognition receives high score in latest LFW test results". BiometricUpdate.com. Feb 13, 2017. <a href="https://www.biometricupdate.com/201702/ping-an-tech-facial-recognition-receives-high-score-in-latest-lfw-test-results">https://www.biometricupdate.com/201702/ping-an-tech-facial-recognition-receives-high-score-in-latest-lfw-test-results</a></p> +</li><li><a name="[^lfw_baidu]" class="footnote_shim"></a><span class="backlinks"></span><p>Jingtuo Liu, Yafeng Deng, Tao Bai, Zhengping Wei, Chang Huang. Targeting Ultimate Accuracy: Face Recognition via Deep Embedding. <a href="https://arxiv.org/abs/1506.07310">https://arxiv.org/abs/1506.07310</a></p> +</li><li><a name="[^lfw_pingan]" class="footnote_shim"></a><span class="backlinks"><a href="#[^lfw_pingan]_1">a</a></span><p>Lee, Justin. "PING AN Tech facial recognition receives high score in latest LFW test results". BiometricUpdate.com. Feb 13, 2017. <a href="https://www.biometricupdate.com/201702/ping-an-tech-facial-recognition-receives-high-score-in-latest-lfw-test-results">https://www.biometricupdate.com/201702/ping-an-tech-facial-recognition-receives-high-score-in-latest-lfw-test-results</a></p> </li></ul></section> </div> diff --git a/site/public/datasets/vgg_face2/index.html b/site/public/datasets/vgg_face2/index.html index efe6cb84..d0a161cb 100644 --- a/site/public/datasets/vgg_face2/index.html +++ b/site/public/datasets/vgg_face2/index.html @@ -25,13 +25,32 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>VGG Face 2</h1> </section><section><div class='meta'><div><div class='gray'>Years</div><div>TBD</div></div><div><div class='gray'>Images</div><div>TBD</div></div><div><div class='gray'>Identities</div><div>TBD</div></div><div><div class='gray'>Origin</div><div>TBD</div></div><div><div class='gray'>Funding</div><div>IARPA</div></div></div><section><section class='fullwidth'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/vgg_face2/assets/vgg_face2_index.gif' alt='...'><div class='caption'>...</div></div></section><section><h3>Analysis</h3> <ul> <li>The VGG Face 2 dataset includes approximately 1,331 actresses, 139 presidents, 16 wives, 3 husbands, 2 snooker player, and 1 guru</li> </ul> +<h3>Names and descriptions</h3> +<ul> +<li>The original VGGF2 name list has been updated with the results returned from Google Knowledge</li> +<li>Names with a similarity score greater than 0.75 where automatically updated. Scores computed using <code>import difflib; seq = difflib.SequenceMatcher(a=a.lower(), b=b.lower()); score = seq.ratio()</code></li> +<li>The 97 names with a score of 0.75 or lower were manually reviewed and includes name changes validating using Wikipedia.org results for names such as "Bruce Jenner" to "Caitlyn Jenner", spousal last-name changes, and discretionary changes to improve search results such as combining nicknames with full name when appropriate, for example changing "Aleksandar Petrović" to "Aleksandar 'Aco' Petrović" and minor changes such as "Mohammad Ali" to "Muhammad Ali"</li> +<li>The 'Description' text was automatically added when the Knowledge Graph score was greater than 250</li> +</ul> +<h2>TODO</h2> +<ul> +<li>create name list, and populate with Knowledge graph information like LFW</li> +<li>make list of interesting number stats, by the numbers</li> +<li>make list of interesting important facts</li> +<li>write intro abstract</li> +<li>write analysis of usage</li> +<li>find examples, citations, and screenshots of useage</li> +<li>find list of companies using it for table</li> +<li>create montages of the dataset, like LFW</li> +<li>create right to removal information</li> +</ul> </section> </div> diff --git a/site/public/datasets_v0/index.html b/site/public/datasets_v0/index.html index c2e6617b..19e8fda1 100644 --- a/site/public/datasets_v0/index.html +++ b/site/public/datasets_v0/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>Facial Recognition Datasets</h1> <p>Regular Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> diff --git a/site/public/datasets_v0/lfw/index.html b/site/public/datasets_v0/lfw/index.html index 4ee4799f..aefe393b 100644 --- a/site/public/datasets_v0/lfw/index.html +++ b/site/public/datasets_v0/lfw/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>Labeled Faces in the Wild</h1> </section><section><div class='meta'><div><div class='gray'>Created</div><div>2007</div></div><div><div class='gray'>Images</div><div>13,233</div></div><div><div class='gray'>People</div><div>5,749</div></div><div><div class='gray'>Created From</div><div>Yahoo News images</div></div><div><div class='gray'>Search available</div><div>Searchable</div></div></div><section><section class='applet_container'><div class='applet' data-payload='{"command": "face_search"}'></div></section><section class='applet_container'><div class='applet' data-payload='{"command": "name_search"}'></div></section><section class='fullwidth'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/datasets_v0/lfw/assets/lfw_feature.jpg' alt='Eighteen of the 5,749 people in the Labeled Faces in the Wild Dataset. The most widely used face dataset for benchmarking commercial face recognition algorithms.'><div class='caption'>Eighteen of the 5,749 people in the Labeled Faces in the Wild Dataset. The most widely used face dataset for benchmarking commercial face recognition algorithms.</div></div></section><section><h3>Intro</h3> diff --git a/site/public/datasets_v0/lfw/right-to-removal/index.html b/site/public/datasets_v0/lfw/right-to-removal/index.html index 97ce4d05..338245bf 100644 --- a/site/public/datasets_v0/lfw/right-to-removal/index.html +++ b/site/public/datasets_v0/lfw/right-to-removal/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>Labeled Faces in the Wild</h1> <h2>Right to Removal</h2> diff --git a/site/public/datasets_v0/lfw/tables/index.html b/site/public/datasets_v0/lfw/tables/index.html index dd460843..348a0759 100644 --- a/site/public/datasets_v0/lfw/tables/index.html +++ b/site/public/datasets_v0/lfw/tables/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>Labeled Faces in the Wild</h1> <h2>Tables</h2> diff --git a/site/public/datasets_v0/vgg_face2/index.html b/site/public/datasets_v0/vgg_face2/index.html index 6a67e7e4..4f8cb550 100644 --- a/site/public/datasets_v0/vgg_face2/index.html +++ b/site/public/datasets_v0/vgg_face2/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>VGG Faces2</h1> </section><section><div class='meta'><div><div class='gray'>Created</div><div>2018</div></div><div><div class='gray'>Images</div><div>3.3M</div></div><div><div class='gray'>People</div><div>9,000</div></div><div><div class='gray'>Created From</div><div>Scraping search engines</div></div><div><div class='gray'>Search available</div><div>[Searchable](#)</div></div></div><section><section><p>VGG Face2 is the updated version of the VGG Face dataset and now includes over 3.3M face images from over 9K people. The identities were selected by taking the top 500K identities in Google's Knowledge Graph of celebrities and then selecting only the names that yielded enough training images. The dataset was created in the UK but funded by Office of Director of National Intelligence in the United States.</p> diff --git a/site/public/info/index.html b/site/public/info/index.html index 0b59e647..371a6520 100644 --- a/site/public/info/index.html +++ b/site/public/info/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h2>Face Analysis</h2> </section><section class='applet_container'><div class='applet' data-payload='{"command": "face_analysis"}'></div></section><section><p>Results are only stored for the duration of the analysis and are deleted when you leave this page.</p> diff --git a/site/public/research/00_introduction/index.html b/site/public/research/00_introduction/index.html index 395bd268..b661b939 100644 --- a/site/public/research/00_introduction/index.html +++ b/site/public/research/00_introduction/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section> <h1>00: Introduction</h1> diff --git a/site/public/research/01_from_1_to_100_pixels/index.html b/site/public/research/01_from_1_to_100_pixels/index.html index c11e966e..87a08886 100644 --- a/site/public/research/01_from_1_to_100_pixels/index.html +++ b/site/public/research/01_from_1_to_100_pixels/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section> <h1>From 1 to 100 Pixels</h1> @@ -47,22 +47,31 @@ <p>What can you know from a very small amount of information?</p> <ul> <li>1 pixel grayscale</li> -<li>2x2 pixels grayscale, font example</li> -<li>4x4 pixels</li> -<li>8x8 yotta yotta</li> -<li>5x7 face recognition</li> +<li>2x2 pixels grayscale, font example, can encode letters</li> +<li>3x3 pixels: can create a font</li> +<li>4x4 pixels: how many variations</li> +<li>8x8 yotta yotta, many more variations</li> +<li>5x7 face recognition </li> <li>12x16 activity recognition</li> <li>6/5 (up to 124/106) pixels in height/width, and the average is 24/20 for QMUL SurvFace</li> +<li>(prepare a Progan render of the QMUL dataset and TinyFaces)</li> <li>20x16 tiny faces paper</li> <li>20x20 MNIST handwritten images <a href="http://yann.lecun.com/exdb/mnist/">http://yann.lecun.com/exdb/mnist/</a></li> <li>24x24 haarcascade detector idealized images</li> <li>32x32 CIFAR image dataset</li> <li>40x40 can do emotion detection, face recognition at scale, 3d modeling of the face. include datasets with faces at this resolution including pedestrian.</li> +<li>NIST standards begin to appear from 40x40, distinguish occular pixels</li> <li>need more material from 60-100</li> <li>60x60 show how texture emerges and pupils, eye color, higher resolution of features and compare to lower resolution faces</li> +<li>100x100 all you need for medical diagnosis</li> <li>100x100 0.5% of one Instagram photo</li> </ul> -<p>Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage</p> +<p>Ideas:</p> +<ul> +<li>Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage</li> +<li>resolution of boston bomber face</li> +<li>resolution of the state of the union image</li> +</ul> <h3>Research</h3> <ul> <li>NIST report on sres states several resolutions</li> diff --git a/site/public/research/02_what_computers_can_see/index.html b/site/public/research/02_what_computers_can_see/index.html new file mode 100644 index 00000000..6826955f --- /dev/null +++ b/site/public/research/02_what_computers_can_see/index.html @@ -0,0 +1,150 @@ +<!doctype html> +<html> +<head> + <title>MegaPixels</title> + <meta charset="utf-8" /> + <meta name="author" content="Adam Harvey" /> + <meta name="description" content="What Computers Can See" /> + <meta name="referrer" content="no-referrer" /> + <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> + <link rel='stylesheet' href='/assets/css/fonts.css' /> + <link rel='stylesheet' href='/assets/css/tabulator.css' /> + <link rel='stylesheet' href='/assets/css/css.css' /> + <link rel='stylesheet' href='/assets/css/leaflet.css' /> + <link rel='stylesheet' href='/assets/css/applets.css' /> +</head> +<body> + <header> + <a class='slogan' href="/"> + <div class='logo'></div> + <div class='site_name'>MegaPixels</div> + </a> + <div class='links'> + <a href="/datasets/">Datasets</a> + <a href="/research/">Research</a> + <a href="/about/">About</a> + </div> + </header> + <div class="content content-"> + + <section> + <h1>What Computers Can See</h1> + <div class='meta'> + <div> + <div class='gray'>Posted</div> + <div>2018-12-15</div> + </div> + <div> + <div class='gray'>By</div> + <div>Adam Harvey</div> + </div> + + </div> + </section> + + <section><p>A list of 100 things computer vision can see, eg:</p> +<ul> +<li>age, race, gender, ancestral origin, body mass index</li> +<li>eye color, hair color, facial hair, glasses</li> +<li>beauty score, </li> +<li>intelligence</li> +<li>what you're looking at</li> +<li>medical conditions</li> +<li>tired, drowsiness in car</li> +<li>affectiva: interest in product, intent to buy</li> +</ul> +<h2>From PubFig Dataset</h2> +<ul> +<li>Male</li> +<li>Asian</li> +<li>White</li> +<li>Black</li> +<li>Baby</li> +<li>Child</li> +<li>Youth</li> +<li>Middle Aged</li> +<li>Senior</li> +<li>Black Hair</li> +<li>Blond Hair</li> +<li>Brown Hair</li> +<li>Bald</li> +<li>No Eyewear</li> +<li>Eyeglasses</li> +<li>Sunglasses</li> +<li>Mustache</li> +<li>Smiling Frowning</li> +<li>Chubby</li> +<li>Blurry</li> +<li>Harsh Lighting</li> +<li>Flash</li> +<li>Soft Lighting</li> +<li>Outdoor Curly Hair</li> +<li>Wavy Hair</li> +<li>Straight Hair</li> +<li>Receding Hairline</li> +<li>Bangs</li> +<li>Sideburns</li> +<li>Fully Visible Forehead </li> +<li>Partially Visible Forehead </li> +<li>Obstructed Forehead</li> +<li>Bushy Eyebrows </li> +<li>Arched Eyebrows</li> +<li>Narrow Eyes</li> +<li>Eyes Open</li> +<li>Big Nose</li> +<li>Pointy Nose</li> +<li>Big Lips</li> +<li>Mouth Closed</li> +<li>Mouth Slightly Open</li> +<li>Mouth Wide Open</li> +<li>Teeth Not Visible</li> +<li>No Beard</li> +<li>Goatee </li> +<li>Round Jaw</li> +<li>Double Chin</li> +<li>Wearing Hat</li> +<li>Oval Face</li> +<li>Square Face</li> +<li>Round Face </li> +<li>Color Photo</li> +<li>Posed Photo</li> +<li>Attractive Man</li> +<li>Attractive Woman</li> +<li>Indian</li> +<li>Gray Hair</li> +<li>Bags Under Eyes</li> +<li>Heavy Makeup</li> +<li>Rosy Cheeks</li> +<li>Shiny Skin</li> +<li>Pale Skin</li> +<li>5 o' Clock Shadow</li> +<li>Strong Nose-Mouth Lines</li> +<li>Wearing Lipstick</li> +<li>Flushed Face</li> +<li>High Cheekbones</li> +<li>Brown Eyes</li> +<li>Wearing Earrings</li> +<li>Wearing Necktie</li> +<li>Wearing Necklace</li> +</ul> +</section> + + </div> + <footer> + <div> + <a href="/">MegaPixels.cc</a> + <a href="/about/disclaimer/">Disclaimer</a> + <a href="/about/terms/">Terms of Use</a> + <a href="/about/privacy/">Privacy</a> + <a href="/about/">About</a> + <a href="/about/team/">Team</a> + </div> + <div> + MegaPixels ©2017-19 Adam R. 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\ No newline at end of file diff --git a/site/public/research/index.html b/site/public/research/index.html index 56348040..e78e34c6 100644 --- a/site/public/research/index.html +++ b/site/public/research/index.html @@ -25,11 +25,10 @@ <a href="/about/">About</a> </div> </header> - <div class="content"> + <div class="content content-"> <section><h1>Research Blog</h1> -<h3>The darkside of datasets and the future of computer vision</h3> -</section><div class='research_index'><a href='/research/00_introduction/'><section class='wide'><img src='data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==' alt='Research post' /><section><h1>00: Introduction</h1><h2></h2></section></section></a><a href='/research/01_from_1_to_100_pixels/'><section class='wide'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/research/01_from_1_to_100_pixels/assets/intro.jpg' alt='Research post' /><section><h1>From 1 to 100 Pixels</h1><h2>Photographs are for romantics. For the rest of us, it's all about data. And a photo contains a massive amount of information about who you are.</h2></section></section></a></div> +</section><div class='research_index'><a href='/research/00_introduction/'><section class='wide'><img src='data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==' alt='Research post' /><section><h1>00: Introduction</h1><h2></h2></section></section></a><a href='/research/01_from_1_to_100_pixels/'><section class='wide'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/research/01_from_1_to_100_pixels/assets/intro.jpg' alt='Research post' /><section><h1>From 1 to 100 Pixels</h1><h2>A breif description of this post, appears in the index page overview</h2></section></section></a></div> </div> <footer> diff --git a/site/public/test/citations/index.html b/site/public/test/citations/index.html index 3567c92a..7c21c3d6 100644 --- a/site/public/test/citations/index.html +++ b/site/public/test/citations/index.html @@ -25,7 +25,7 @@ <a href="/about/">About</a> </div> </header> - 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