cosmetics

16 files changed, 76 insertions, 98 deletions

diff --git a/site/assets/css/css.css b/site/assets/css/css.css
index c22d4002..91d75599 100644
--- a/site/assets/css/css.css
+++ b/site/assets/css/css.css
@@ -400,7 +400,7 @@ section.images {
 }
 .image:first-child {
   margin-left: 0;
-  margin-top:10px;
+  /*margin-top:10px;*/
 }
 .image:nth-child(2),
 .image:nth-child(3) {
@@ -432,6 +432,12 @@ section.fullwidth {
 section.fullwidth .image {
   max-width: 100%;
 }
+.image .caption{
+  text-align: center;
+}
+.image .caption.intro-caption{
+  text-align: left;
+}
 .caption {
   text-align: left;
   font-size: 9pt;
@@ -621,7 +627,7 @@ section.intro_section {
   background-size: cover;
   background-position: bottom left;
   padding: 50px 0;
-  min-height: 60vh;
+  min-height: 45vh;
   display: flex;
   justify-content: center;
   align-items: center;
@@ -641,7 +647,7 @@ section.intro_section {
 .intro_section .hero_subdesc {
   font-size: 17px;
   line-height: 36px;
-  max-width: 640px;
+  max-width: 680px;
   font-weight: 400;
   color: #ddd;
 }
@@ -684,14 +690,15 @@ page-specific formatting
 .content-about{
   font-color:#ff0;
 }
-.content-about > section > ul li{
+.content-about .about-menu ul li{
   display:inline-block;
   font-size: 12px;
   font-weight: 400;
   margin-right: 5px;
   text-transform: uppercase;
+  margin-right: 10px
 }
-.content-about > section > ul li a{
+.content-about .about-menu ul li a{
   border-bottom: 0;
 }
 
diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md
index 7f034d57..17302118 100644
--- a/site/content/pages/about/index.md
+++ b/site/content/pages/about/index.md
@@ -13,22 +13,7 @@ authors: Adam Harvey
 
 # About This Project
 
-- [About](/about/)
-- [Press](/about/press/)
-- [Research Methodology](/about/research/)
-- [Disclaimer](/about/disclaimer/)
-- [Terms and Conditions](/about/terms/)
-- [Privacy Policy](/about/privacy/)
-
-### Sidebar
-
-### Recent Press
-
-- [TheVerge: Transgender YouTubers had their videos grabbed to train facial recognition software](https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset) by James Vincent 
-- [TheVerge: Transgender YouTubers had their videos grabbed to train facial recognition software](https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset) by James Vincent 
-- [change to small button]Read more [press](/about/press)
- 
-## End Sidebar
+{% include 'about_navigation.html' %}
 
 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?
 
@@ -36,7 +21,6 @@ MegaPixels sets out to answer to these questions and reveal the stories behind t
 
 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.
 
-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.
 
 ![sideimage:Adam Harvey](assets/adam-harvey.jpg) **Adam Harvey** 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.
 
diff --git a/site/content/pages/datasets/brainwash/assets/00425000_640x480.jpg b/site/content/pages/datasets/brainwash/assets/00425000_640x480.jpg
new file mode 100644
index 00000000..de62175a
--- /dev/null
+++ b/site/content/pages/datasets/brainwash/assets/00425000_640x480.jpg
diff --git a/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg b/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg
new file mode 100644
index 00000000..30c0fcb1
--- /dev/null
+++ b/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg
diff --git a/site/content/pages/datasets/brainwash/assets/background.jpg b/site/content/pages/datasets/brainwash/assets/background.jpg
index d971a331..f6efb253 100755..100644
--- a/site/content/pages/datasets/brainwash/assets/background.jpg
+++ b/site/content/pages/datasets/brainwash/assets/background.jpg
diff --git a/site/content/pages/datasets/brainwash/assets/background_02.jpg b/site/content/pages/datasets/brainwash/assets/background_02.jpg
deleted file mode 100644
index eada1779..00000000
--- a/site/content/pages/datasets/brainwash/assets/background_02.jpg
+++ /dev/null
diff --git a/site/content/pages/datasets/brainwash/assets/index.jpg b/site/content/pages/datasets/brainwash/assets/index.jpg
index c903baea..e85f75c2 100644
--- a/site/content/pages/datasets/brainwash/assets/index.jpg
+++ b/site/content/pages/datasets/brainwash/assets/index.jpg
diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md
index b12f4bd5..a99dce3a 100644
--- a/site/content/pages/datasets/brainwash/index.md
+++ b/site/content/pages/datasets/brainwash/index.md
@@ -15,9 +15,9 @@ authors: Adam Harvey
 
 ### Statistics
 
-+ Published: 2015
 + Collected: 2014
-+ Location: San Franscisco
++ Published: 2015
++ Location: 1122 Folsom Street​ San Franscisco
 + Images: 11,917
 + Faces: 91,146
 + Created by: Stanford Department of Computer Science
@@ -26,35 +26,36 @@ authors: Adam Harvey
 + Origin: Angelcam IP Cam
 + Purpose: Training face detection
 
-### Insights
+- more info1
+- more info2
+- more info3
 
-- more insights here
+## Brainwash Dataset
 
-- facts about Brainwash 2
+*Brainwash* is a face detection dataset created from the Brainwash Cafe's livecam footage. The stream is It was published in 2015 by researchers at the Stanford University and has been used 1122 Folsom Street​ | USA
 
-## Brainwash Dataset
+The photos were collected on
+- Oct 27, 2014
+- Nov 11, 2014
+- Nov 245, 2017
 
-*Brainwash* is a face detection dataset created from the Brainwash Cafe's livecam footage. The stream is It was published in 2015 by researchers at the Stanford University and has been used
- 1122 Folsom Street​ | USA
+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 consequuntur magni dolores eos, qui ratione voluptatem sequi nesciunt, neque porro quisquam est, qui dolorem ipsum, quia dolor sit amet consectetur adipisci[ng] velit, sed quia non-numquam [do] eius modi tempora inci[di]dunt, ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam.
 
-# Map
+![Example images from the Brainwash dataset](assets/00425000_640x480.jpg)
+![Example images from the Brainwash dataset](assets/00818000_640x480.jpg)
 
-{% include 'map.html' %}
+porro quisquam est, qui dolorem ipsum, quia dolor sit amet consectetur adipisci[ng] velit, sed quia non-numquam [do] eius modi tempora inci[di]dunt, ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum[d] exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur? Quis autem vel eum iure reprehenderit, qui in ea voluptate velit esse, quam nihil molestiae consequatur, vel illum, qui dolorem eum fugiat, quo voluptas nulla pariatur?
 
-### Synthetic Faces
 
-```
-synthetic_faces_intro
-```
+{% include 'map.html' %}
 
-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.
+<hr class="supp">
 
-![Synthetically generated face from the visual space of LFW dataset](assets/synthetic_01.jpg)
-![Synthetically generated face from the visual space of LFW dataset](assets/synthetic_02.jpg)
-![Synthetically generated face from the visual space of LFW dataset](assets/synthetic_03.jpg)
+## Supplementary Information for Brainwash Dataset
 
 {% include 'citations.html' %}
 
+
 --------
 
 RESEARCH below this line
diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md
index 04fe775c..1af263dc 100644
--- a/site/content/pages/datasets/lfw/index.md
+++ b/site/content/pages/datasets/lfw/index.md
@@ -3,7 +3,7 @@
 status: published
 title: Labeled Faces in The Wild
 desc: <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.
-subdesc: It includes 13,456 images of 4,432 people’s images copied from the Internet during 2002-2004.
+subdesc: It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004.
 image: assets/background.jpg
 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.
 slug: lfw
@@ -19,7 +19,7 @@ authors: Adam Harvey
 + Images: 13,233
 + Identities: 5,749
 + Origin: Yahoo! News Images
-+ Funding: IARPA*, CIA*
++ Used by: Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA
 + Website: <a href="http://vis-www.cs.umass.edu/lfw">vis-www.cs.umass.edu/lfw</a>
 
 - There are about 3 men for every 1 woman in the LFW dataset[^lfw_www]
@@ -56,9 +56,7 @@ The *Names and Faces* dataset was the first face recognition dataset created ent
 
 {% include 'citations.html' %}
 
-### Synthetic Faces
-
-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.
+{% include 'synthetic_faces_intro.html' %}
 
 ![Synthetically generated face from the visual space of LFW dataset](assets/synthetic_01.jpg)
 ![Synthetically generated face from the visual space of LFW dataset](assets/synthetic_02.jpg)
@@ -70,14 +68,12 @@ To visualize the types of photos in the dataset without explicitly publishing in
 
 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.
 
-
 ```
 load_file assets/lfw_commercial_use.csv
 name_display, company_url, example_url, country, description
 ```
 
-
-## Code
+### Code
 
 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 `fetch_lfw_people` to download the faces in the LFW dataset.
 
diff --git a/site/includes/about_navigation.html b/site/includes/about_navigation.html
new file mode 100644
index 00000000..f82b77b7
--- /dev/null
+++ b/site/includes/about_navigation.html
@@ -0,0 +1,10 @@
+<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>
\ No newline at end of file
diff --git a/site/includes/citations.html b/site/includes/citations.html
index b542ef3c..ed54b9b1 100644
--- a/site/includes/citations.html
+++ b/site/includes/citations.html
@@ -1,5 +1,6 @@
 <section class="applet_container">
   <h3>Citations</h3>
-  <p>Add information about how the citations were generated</p>
+  <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="{&quot;command&quot;: &quot;citations&quot;}"></div>
 </section>
\ No newline at end of file
diff --git a/site/includes/map.html b/site/includes/map.html
index 77956f52..730e30d0 100644
--- a/site/includes/map.html
+++ b/site/includes/map.html
@@ -20,6 +20,7 @@
 <section class="applet_container">
  <div class="applet" data-payload="{&quot;command&quot;: &quot;map&quot;}"></div>
 </section>
+
 <div class="caption">
 	<div class="map-legend-item"><span class="edu">&#9632;</span> Academic</div>
 	<div class="map-legend-item"><span class="com">&#9632;</span> Industry</div>
diff --git a/site/includes/synthetic_faces_intro.html b/site/includes/synthetic_faces_intro.html
new file mode 100644
index 00000000..13f6db0e
--- /dev/null
+++ b/site/includes/synthetic_faces_intro.html
@@ -0,0 +1,4 @@
+<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>
\ No newline at end of file
diff --git a/site/public/about/index.html b/site/public/about/index.html
index e2ce409d..ed80691a 100644
--- a/site/public/about/index.html
+++ b/site/public/about/index.html
@@ -28,22 +28,7 @@
   <div class="content content-about">
     
   <section><h1>About This Project</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><section><div class='right-sidebar'><h3>Recent Press</h3>
-<ul>
-<li><a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">TheVerge: Transgender YouTubers had their videos grabbed to train facial recognition software</a> by James Vincent </li>
-<li><a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">TheVerge: Transgender YouTubers had their videos grabbed to train facial recognition software</a> by James Vincent </li>
-<li>[change to small button]Read more <a href="/about/press">press</a></li>
-</ul>
-</div><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>
+</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>
diff --git a/site/public/about/terms/index.html b/site/public/about/terms/index.html
index c90f1c9d..650366e0 100644
--- a/site/public/about/terms/index.html
+++ b/site/public/about/terms/index.html
@@ -28,7 +28,7 @@
   <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>
diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html
index 9657b866..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' />
@@ -27,44 +27,34 @@
   </header>
   <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>[convert to template] 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='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>
+<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">&#9632;</span> Industry</li>	    <li><span style="color: #f30000">&#9632;</span> Academic</li>	    <li><span style="color: #3264f6">&#9632;</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="{&quot;command&quot;: &quot;map&quot;}"></div></section><div class="caption">	<div class="map-legend-item"><span class="edu">&#9632;</span> Academic</div>	<div class="map-legend-item"><span class="com">&#9632;</span> Industry</div>	<div class="map-legend-item"><span class="gov">&#9632;</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="{&quot;command&quot;: &quot;citations&quot;}"></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></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>
+<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
@@ -94,11 +84,10 @@ imageio.imwrite(&#39;lfw_montage_full.png&#39;, montage)
 montage = imutils.resize(montage, width=960)
 imageio.imwrite(&#39;lfw_montage_960.jpg&#39;, 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>