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diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html
index e90cdcc5..3c7fd45f 100644
--- a/site/public/datasets/lfw/index.html
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@@ -27,8 +27,8 @@
</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 (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>
+ <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 class='bgpad'><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 class='bgpad'>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='left-sidebar'><div class='meta'><div><div class='gray'>Created</div><div>2002 &ndash; 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">umass.edu</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>
@@ -44,47 +44,10 @@
<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>
-<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>
+</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.</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> Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a></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>
+</section><section> <div class="hr-wave-holder"> <div class="hr-wave-line hr-wave-line1"></div> <div class="hr-wave-line hr-wave-line2"></div> </div> <h2>Supplementary Information</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>Commercial Use</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
-from sklearn.datasets import fetch_lfw_people
-import imageio
-import imutils
-
-# download LFW dataset (first run takes a while)
-lfw_people = fetch_lfw_people(min_faces_per_person=1, resize=1, color=True, funneled=False)
-
-# introspect dataset
-n_samples, h, w, c = lfw_people.images.shape
-print(f&#39;{n_samples:,} images at {w}x{h} pixels&#39;)
-cols, rows = (176, 76)
-n_ims = cols * rows
-
-# build montages
-im_scale = 0.5
-ims = lfw_people.images[:n_ims]
-montages = imutils.build_montages(ims, (int(w * im_scale, int(h * im_scale)), (cols, rows))
-montage = montages[0]
-
-# save full montage image
-imageio.imwrite(&#39;lfw_montage_full.png&#39;, montage)
-
-# make a smaller version
-montage = imutils.resize(montage, width=960)
-imageio.imwrite(&#39;lfw_montage_960.jpg&#39;, montage)
-</code></pre>
-</section><section><p>Research, text, and graphics ©Adam Harvey / megapixels.cc</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><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"></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>
diff --git a/site/public/datasets/lfw/right-to-removal/index.html b/site/public/datasets/lfw/right-to-removal/index.html
new file mode 100644
index 00000000..5dc269b2
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+++ b/site/public/datasets/lfw/right-to-removal/index.html
@@ -0,0 +1,62 @@
+<!doctype html>
+<html>
+<head>
+ <title>MegaPixels</title>
+ <meta charset="utf-8" />
+ <meta name="author" content="Adam Harvey" />
+ <meta name="description" content="LFW: Labeled Faces in The Wild" />
+ <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' />
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+ </div>
+ </header>
+ <div class="content">
+
+ <section><h1>Labeled Faces in the Wild</h1>
+<h2>Right to Removal</h2>
+<p>If you are affected by disclosure of your identity in this dataset please do contact the authors. Many have stated that they are willing to remove images upon request. The authors of the LFW dataset provide the following email for inquiries:</p>
+<p>You can use the following message to request removal from the dataset:</p>
+<p>To: Gary Huang <a href="mailto:mailto:gbhuang@cs.umass.edu">mailto:gbhuang@cs.umass.edu</a></p>
+<p>Subject: Request for Removal from LFW Face Dataset</p>
+<p>Dear [researcher name],</p>
+<p>I am writing to you about the "Labeled Faces in The Wild Dataset". Recently I discovered that your dataset includes my identity and I no longer wish to be included in your dataset.</p>
+<p>The dataset is being used thousands of companies around the world to improve facial recognition software including usage by governments for the purpose of law enforcement, national security, tracking consumers in retail environments, and tracking individuals through public spaces.</p>
+<p>My name as it appears in your dataset is [your name]. Please remove all images from your dataset and inform your newsletter subscribers to likewise update their copies.</p>
+<p>- [your name]</p>
+<hr>
+</section>
+
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diff --git a/site/public/datasets/lfw/tables/index.html b/site/public/datasets/lfw/tables/index.html
new file mode 100644
index 00000000..dd460843
--- /dev/null
+++ b/site/public/datasets/lfw/tables/index.html
@@ -0,0 +1,52 @@
+<!doctype html>
+<html>
+<head>
+ <title>MegaPixels</title>
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+ <meta name="description" content="LFW: Labeled Faces in The Wild" />
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+ <div class="content">
+
+ <section><h1>Labeled Faces in the Wild</h1>
+<h2>Tables</h2>
+</section><section class='applet_container'><div class='applet' data-payload='{"command": "load_file assets/lfw_names_gender_kg_min.csv", "fields": ["Name, Images, Gender, Description"]}'></div></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></section>
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