diff options
Diffstat (limited to 'site/content')
17 files changed, 91 insertions, 136 deletions
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diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index 17302118..ccb6ed0d 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -11,7 +11,7 @@ authors: Adam Harvey ------------ -# About This Project +# About MegaPixels {% include 'about_navigation.html' %} @@ -21,6 +21,15 @@ 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. +Notes + +- critical but informative +- not anti-dataset +- pro-sharing, pro-public dataset +- w/o data +- not generally anti-researcher, their parent organization should have checks in place to prevent dubious dataset collection methods +- +  **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/about/press.md b/site/content/pages/about/press.md index 1c80d020..abd4d823 100644 --- a/site/content/pages/about/press.md +++ b/site/content/pages/about/press.md @@ -13,15 +13,7 @@ authors: Adam Harvey # Press -- [About](/about/) -- [Press](/about/press/) -- [Disclaimer](/about/disclaimer/) -- [Terms and Conditions](/about/terms/) -- [Privacy Policy](/about/privacy/) - -### Sidebar - -## End Sidebar +{% include 'about_navigation.html' %} (list of press articles and images will go here) diff --git a/site/content/pages/about/privacy.md b/site/content/pages/about/privacy.md index 43db5032..a47b74cc 100644 --- a/site/content/pages/about/privacy.md +++ b/site/content/pages/about/privacy.md @@ -13,11 +13,7 @@ authors: Adam Harvey # Privacy Policy -- [About](/about/) -- [Press](/about/press/) -- [Disclaimer](/about/disclaimer/) -- [Terms and Conditions](/about/terms/) -- [Privacy Policy](/about/privacy/) +{% include 'about_navigation.html' %} A summary of our privacy policy is as follows: diff --git a/site/content/pages/about/research.md b/site/content/pages/about/research.md index 71dedcf0..8f001cc9 100644 --- a/site/content/pages/about/research.md +++ b/site/content/pages/about/research.md @@ -13,9 +13,4 @@ authors: Adam Harvey # Research Methodologies -- [About](/about/) -- [Press](/about/press/) -- [Research Methodology](/about/research/) -- [Disclaimer](/about/disclaimer/) -- [Terms and Conditions](/about/terms/) -- [Privacy Policy](/about/privacy/) +{% include 'about_navigation.html' %}
\ No newline at end of file diff --git a/site/content/pages/about/terms.md b/site/content/pages/about/terms.md index aa298421..38d43735 100644 --- a/site/content/pages/about/terms.md +++ b/site/content/pages/about/terms.md @@ -14,17 +14,7 @@ authors: Adam Harvey # Terms and Conditions ("Terms") -### Sidebar - -- [About](/about/) -- [Press](/about/press/) -- [Credits](/about/credits/) -- [Research Methodology](/about/research/) -- [Disclaimer](/about/disclaimer/) -- [Terms and Conditions](/about/terms/) -- [Privacy Policy](/about/privacy/) - -## End Sidebar +{% include 'about_navigation.html' %} (FPO: this is only example text) diff --git a/site/content/pages/datasets/brainwash/assets/00425000_960.jpg b/site/content/pages/datasets/brainwash/assets/00425000_960.jpg Binary files differnew file mode 100644 index 00000000..caa96fe2 --- /dev/null +++ b/site/content/pages/datasets/brainwash/assets/00425000_960.jpg diff --git a/site/content/pages/datasets/brainwash/assets/background.jpg b/site/content/pages/datasets/brainwash/assets/background.jpg Binary files differindex f6efb253..8f2de697 100644..100755 --- 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/brainwash_montage.jpg b/site/content/pages/datasets/brainwash/assets/brainwash_montage.jpg Binary files differnew file mode 100644 index 00000000..193fdd03 --- /dev/null +++ b/site/content/pages/datasets/brainwash/assets/brainwash_montage.jpg diff --git a/site/content/pages/datasets/brainwash/assets/index.jpg b/site/content/pages/datasets/brainwash/assets/index.jpg Binary files differindex e85f75c2..e5004ec0 100644..100755 --- 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 a99dce3a..6c8cad97 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -3,9 +3,9 @@ status: published title: Brainwash desc: <span style="color:#ffaa00">Brainwash</span> is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms -subdesc: Brainwash dataset includes 11,918 images of people getting coffee at the Brainwash cafe during 2014 -caption: An sample image from the Brainwash dataset used for training face detection algorithms for surveillance. License: Open Data Commons Public Domain Dedication (PDDL) +subdesc: Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" slug: brainwash +cssclass: dataset image: assets/background.jpg published: 2019-2-23 updated: 2019-2-23 @@ -13,68 +13,49 @@ authors: Adam Harvey ------------ -### Statistics +### sidebar + Collected: 2014 + Published: 2015 -+ Location: 1122 Folsom Street San Franscisco -+ Images: 11,917 ++ Images: 11,918 + Faces: 91,146 + Created by: Stanford Department of Computer Science -+ Funding: Max Planck Center for Visual Computing and Communication ++ Funded by: Max Planck Center for Visual Computing and Communication + Resolution: 640x480px -+ Origin: Angelcam IP Cam ++ Size: 4.1GB ++ Origin: Brainwash Cafe, San Franscisco + Purpose: Training face detection ++ Website: <a href="https://exhibits.stanford.edu/data/catalog/sx925dc9385">stanford.edu</a> ++ Paper: <a href="http://arxiv.org/abs/1506.04878">End-to-End People Detection in Crowded Scenes</a> -- more info1 -- more info2 -- more info3 ## Brainwash Dataset -*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* is a face detection dataset created from the Brainwash Cafe's livecam footage including 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to develop face detection algorithms for the "challenging task of detecting people in crowded scenes" and tracking them. -The photos were collected on -- Oct 27, 2014 -- Nov 11, 2014 -- Nov 245, 2017 +Before closing in 2017, Brainwash Cafe was a "cafe and laundromat" located in San Francisco's Lower Haight district. The cafe published a publicy available livestream from the cafe with a view of the cash register, performance stage, and seating area. -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. +Since it's publication by Stanford in 2015, the Brainwash dataset has appeared in several notable research papers. In September 2016 four researchers from the National University of Defense Technology in Changsha, China used the Brainwash dataset for a research study on "people head detection in crowded scenes", concluding that their algorithm "achieves superior head detection performance on the crowded scenes dataset[^localized_region_context]". And again in 2017 three researchers at the National University of Defense Technology used Brainwash for a study on object detection noting "the data set used in our experiment is shown in Table 1, which includes one scene of the brainwash dataset[^replacement_algorithm]". - - - -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? + + {% include 'map.html' %} -<hr class="supp"> -## Supplementary Information for Brainwash Dataset +{% include 'supplementary_header.html' %} {% include 'citations.html' %} --------- - -RESEARCH below this line - ---- - -The file is 4.1GB -- add sha256 hash -- the images were taken from Dropcam which was runnign on https://www.angelcam.com/ "Angelcam’s Real-time Surveillance takes the weight of keeping your home or business secure off your shoulders." - +### Additional Information -> This package contains the "Brainwash" dataset. The dataset consists of images capturing the everyday life of a busy downtown cafe and is split into the following subsets: -> training set: 10769 with 81975 annotated people -> validation set: 500 images with 3318 annotated people -> test set: 500 images with 5007 annotated people +- The dataset author spoke about his research at the CVPR conference in 2016 <https://www.youtube.com/watch?v=Nl2fBKxwusQ> -> Bounding box annotations are provided in a simple text file format. Each line in the file contains -image name followed by the list of annotation rectangles in the \[xmin, ymin, max, ymax\] format. -> We refer to the following arXiv submission for details on the dataset and the evaluation procedure: +### Footnotes -http://arxiv.org/abs/1506.04878
\ No newline at end of file +[^readme]: "readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385. +[^localized_region_context]: Li, Y. and Dou, Y. and Liu, X. and Li, T. Localized Region Context and Object Feature Fusion for People Head Detection. ICIP16 Proceedings. 2016. Pages 594-598. +[^replacement_algorithm]: Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.
\ No newline at end of file diff --git a/site/content/pages/datasets/index.md b/site/content/pages/datasets/index.md index 47d0bce2..30fca496 100644 --- a/site/content/pages/datasets/index.md +++ b/site/content/pages/datasets/index.md @@ -13,3 +13,4 @@ sync: false # Facial Recognition Datasets +[add text, make sortable] This is a list of all the facial recognition datasets
\ No newline at end of file diff --git a/site/content/pages/datasets/lfw/assets/background.jpg b/site/content/pages/datasets/lfw/assets/background.jpg Binary files differindex 3ab1607d..2c517060 100644 --- a/site/content/pages/datasets/lfw/assets/background.jpg +++ b/site/content/pages/datasets/lfw/assets/background.jpg diff --git a/site/content/pages/datasets/lfw/assets/background_lg.jpg b/site/content/pages/datasets/lfw/assets/background_lg.jpg Binary files differnew file mode 100644 index 00000000..3ab1607d --- /dev/null +++ b/site/content/pages/datasets/lfw/assets/background_lg.jpg diff --git a/site/content/pages/datasets/lfw/assets/fetch_lfw_people.py b/site/content/pages/datasets/lfw/assets/fetch_lfw_people.py new file mode 100644 index 00000000..639883a6 --- /dev/null +++ b/site/content/pages/datasets/lfw/assets/fetch_lfw_people.py @@ -0,0 +1,34 @@ +#!/usr/bin/python + +# ------------------------------------------------------------ +# +# Script to generate montage of LFW faces used in scikit-learn +# +# ------------------------------------------------------------ + +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'{n_samples:,} images at {w}x{h} pixels') +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('lfw_montage_full.png', montage) + +# make a smaller version +montage = imutils.resize(montage, width=960) +imageio.imwrite('lfw_montage_960.jpg', montage)
\ No newline at end of file diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md index 1af263dc..80e30ab3 100644 --- a/site/content/pages/datasets/lfw/index.md +++ b/site/content/pages/datasets/lfw/index.md @@ -5,7 +5,6 @@ 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. 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 published: 2019-2-23 updated: 2019-2-23 @@ -15,12 +14,12 @@ authors: Adam Harvey ### sidebar -+ Created: 2002-2004 ++ Created: 2002 – 2004 + Images: 13,233 + Identities: 5,749 + Origin: Yahoo! News Images + 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> ++ Website: <a href="http://vis-www.cs.umass.edu/lfw">umass.edu</a> - There are about 3 men for every 1 woman in the LFW dataset[^lfw_www] - The person with the most images is [George W. Bush](http://vis-www.cs.umass.edu/lfw/person/George_W_Bush_comp.html) with 530 @@ -48,23 +47,11 @@ The *Names and Faces* dataset was the first face recognition dataset created ent {% include 'map.html' %} - 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. - -<hr class="supp"> - -## Supplementary Information for Labeled Faces in The Wild +{% include 'supplementary_header.html' %} {% include 'citations.html' %} -{% include 'synthetic_faces_intro.html' %} - - - - - - - -### Commercial Use of Labeled Faces in The Wild +### Commercial Use 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. @@ -73,46 +60,6 @@ load_file assets/lfw_commercial_use.csv name_display, company_url, example_url, country, description ``` -### 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. - -```python -#!/usr/bin/python - -# ------------------------------------------------------------ -# -# Script to generate montage of LFW faces used in scikit-learn -# -# ------------------------------------------------------------ - -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'{n_samples:,} images at {w}x{h} pixels') -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('lfw_montage_full.png', montage) - -# make a smaller version -montage = imutils.resize(montage, width=960) -imageio.imwrite('lfw_montage_960.jpg', montage) -``` Research, text, and graphics ©Adam Harvey / megapixels.cc |
