From 45bf844c0891098232b2a7ff5458cd2de32acbdf Mon Sep 17 00:00:00 2001 From: adamhrv Date: Sun, 31 Mar 2019 15:58:20 +0200 Subject: update about --- site/content/pages/about/credits.md | 48 ----------------------------- site/content/pages/about/faq.md | 28 +++++++++++++++++ site/content/pages/about/index.md | 60 +++++++++++++++++++++++-------------- 3 files changed, 65 insertions(+), 71 deletions(-) delete mode 100644 site/content/pages/about/credits.md create mode 100644 site/content/pages/about/faq.md (limited to 'site/content/pages') diff --git a/site/content/pages/about/credits.md b/site/content/pages/about/credits.md deleted file mode 100644 index bc2283fd..00000000 --- a/site/content/pages/about/credits.md +++ /dev/null @@ -1,48 +0,0 @@ ------------- - -status: published -title: MegaPixels Press and News -desc: MegaPixels Press and News -slug: press -cssclass: about -published: 2018-12-04 -updated: 2018-12-04 -authors: Adam Harvey - ------------- - -# Credits - -
- -
- - -#### Team - -- Research and image analysis: Adam Harvey -- Development and visualizations: Jules LaPlace -- Produced in Partnership with Mozilla -- Contributing researchers: Berit Gilma, Mathana Stender - -#### Code - -<<<<<<< HEAD -- This site uses D3.js, C3.js, and ThreeJS for visualizations. -- Data aggregation uses Pandas and PDFMiner.Six. -======= -- This site uses D3 and C2 for visuzations -- Add more here ->>>>>>> 26646e6adf3833f6282e9515c14ad61e485440c0 - -#### Data - -- link to github -- how it was gathered \ No newline at end of file diff --git a/site/content/pages/about/faq.md b/site/content/pages/about/faq.md new file mode 100644 index 00000000..cec53813 --- /dev/null +++ b/site/content/pages/about/faq.md @@ -0,0 +1,28 @@ +------------ + +status: published +title: MegaPixels Press and News +desc: MegaPixels Press and News +slug: press +cssclass: about +published: 2018-12-04 +updated: 2018-12-04 +authors: Adam Harvey + +------------ + +# FAQs + +
+ +
+ + +[ page under development ] diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index 4fec0777..c2d67f16 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -16,41 +16,55 @@ authors: Adam Harvey
-(PAGE UNDER DEVELOPMENT) +MegaPixels is an independent art and research project by Adam Harvey and Jules LaPlace investigating the ethics and individual privacy implications of publicly available face recognition datasets, and their role in industry and governmental expansion into biometric surveillance technologies. -

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to technological advancements. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance cameras on college campuses, search engine queries for celebrities, cafe livestreams, and personal videos posted on YouTube.

- -Collectively, facial recognition datasets are now gathered "in the wild". - -

MegaPixels is art and research by Adam Harvey about facial recognition datasets that unravels their histories, futures, geographies, and meanings. Throughout 2019 this site this site will publish research reports, visualizations, raw data, and interactive tools to explore how publicly available facial recognition datasets contribute to a global supply chain of biometric data that powers the global facial recognition industry.

- -During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is powering the global facial recognition industry. - -The MegaPixels website is produced in partnership with [Mozilla](https://mozilla.org). +The MegaPixels site is made possible with support from Mozilla
- -

Adam Harvey

-

is Berlin-based American artist and researcher. 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 grants, and is a researcher in residence at Karlsruhe HfG. -
- ahprojects.com +

Adam Harvey

+

is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for counter-surveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups) and is a currently researcher in residence at Karlsruhe HfG.

+

ahprojects.com

-

Jules LaPlace

-

is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians. -
- asdf.us +

is an American technologist and artist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision and data analysis software for human rights groups. Jules also builds experimental software for artists and musicians.

+

asdf.us

+ +MegaPixels.cc is an independent research project about publicly available face recognition datasets. This website is based, in part, on earlier installations and research project about facial recognition datasets in 2016-2018, in particular the MegaFace dataset. Since then it has evolved into a large-scale survey and analysis of publicly available face and person analysis dataset usage, geographies, and ethics. + +An academic report and presentation on the findings is forthcoming. This site is published to make the research more accessible to a wider audience and to include visualizations and interactive features not possible in PDF publications. Continued research on MegaPixles is supported by a 1 year Researcher-in-Residence grant from Karlsruhe HfG. + +When possible, and once thoroughly verified, data generated for MegaPixels will be made available for download on [github.com/adamhrv/megapixels](https://github.com/adamhrv/megapixels) + +#### Team + +- Adam Harvey: Concept, research, design, computer vision +- Jules LaPlace: Information and systems architecture, data retrieval, web applications + +#### Contributing Researchers + +- Berit Gilma: Dataset statistics and discovery +- Beth (aka Ms. Celeb): Dataset usage verification and research +- Mathana Stender: Commercial usage verification and research on LFW + +#### Code and Libraries + +- [Semantic Scholar](https://semanticscholar.org) for citation aggregation +- Leaflet.js for maps +- C3.js for charts +- D3.js and ThreeJS for 3D visualizations +- PDFMiner.Six and Pandas for research paper data analysis + +Please direct questions, comments, or feedback to [mastodon.social/@adamhrv](https://mastodon.social/@adamhrv) \ No newline at end of file -- cgit v1.2.3-70-g09d2 From 6366b90b7e124a0059e2ebebe0f813b2e35e2f66 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 31 Mar 2019 16:54:38 +0200 Subject: columns --- megapixels/app/site/parser.py | 22 ++++++++++++++++++++++ site/assets/css/css.css | 26 ++++++++++++++++++++------ site/content/pages/about/index.md | 16 ++++++++++++---- site/public/about/index.html | 16 ++++++++-------- 4 files changed, 62 insertions(+), 18 deletions(-) (limited to 'site/content/pages') diff --git a/megapixels/app/site/parser.py b/megapixels/app/site/parser.py index 00470e4b..06c45f41 100644 --- a/megapixels/app/site/parser.py +++ b/megapixels/app/site/parser.py @@ -27,6 +27,7 @@ def parse_markdown(metadata, sections, s3_path, skip_h1=False): current_group = [] footnotes = [] in_stats = False + in_columns = False in_footnotes = False ignoring = False @@ -50,6 +51,7 @@ def parse_markdown(metadata, sections, s3_path, skip_h1=False): footnotes.append(section) elif ignoring: continue + elif '### statistics' in section.lower() or '### sidebar' in section.lower(): if len(current_group): groups.append(format_section(current_group, s3_path)) @@ -64,6 +66,26 @@ def parse_markdown(metadata, sections, s3_path, skip_h1=False): if 'end sidebar' not in section.lower(): current_group.append(section) in_stats = False + + elif '=== columns' in section.lower(): + if len(current_group): + groups.append(format_section(current_group, s3_path)) + current_group = [] + in_columns = True + column_partz = section.split(' ') + if len(column_partz) == 3: + column_count = column_partz[2] + else: + column_count = "N" + groups.append("
".format(column_count)) + elif in_columns is True and '===' in section: + groups.append(format_section(current_group, s3_path, type='column', tag='div')) + current_group = [] + if 'end columns' in section: + groups.append("
") + in_columns = False + current_group = [] + elif section.strip().startswith('{% include'): groups.append(format_section(current_group, s3_path)) current_group = [] diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 0244b86b..b9e99efe 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -842,21 +842,20 @@ ul.map-legend li.source:before { color: #fff; } .content-about p { - font-size:16px; + font-size: 16px; } .content-about ul{ - font-size:14px; + font-size: 14px; font-weight: 300; } -.content-about section > p:first-of-type{ - font-size:23px; - line-height:39px; +.content-about section:first-of-type > p:first-of-type { + font-size: 23px; + line-height: 39px; } .content-about .about-menu ul li { display: inline-block; font-size: 14px; font-weight: 400; - margin-right: 8px; text-transform: uppercase; margin-right: 15px; font-family: 'Roboto'; @@ -870,6 +869,21 @@ ul.map-legend li.source:before { border-bottom: 1px solid #ddd; color: #ddd; } + +/* columns */ + +.columns { + display: flex; + flex-direction: row; + justify-content: flex-start; +} +.columns-3 .column { + width: 33%; + padding-right: 20px; + font-family: Roboto, sans-serif; + font-weight: 400; +} + /* about page */ diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index c2d67f16..5fc147c9 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -29,7 +29,7 @@ The MegaPixels site is made possible with support from
-

Adam Harvey

+

Adam Harvey

is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for counter-surveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups) and is a currently researcher in residence at Karlsruhe HfG.

ahprojects.com

@@ -42,29 +42,37 @@ The MegaPixels site is made possible with support from Mozilla

-

Adam Harvey

+

Adam Harvey

is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for counter-surveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups) and is a currently researcher in residence at Karlsruhe HfG.

ahprojects.com

@@ -50,29 +50,29 @@

asdf.us

-

MegaPixels.cc is an independent research project about publicly available face recognition datasets. This website is based, in part, on earlier installations and research project about facial recognition datasets in 2016-2018, in particular the MegaFace dataset. Since then it has evolved into a large-scale survey and analysis of publicly available face and person analysis dataset usage, geographies, and ethics.

-

An academic report and presentation on the findings is forthcoming. This site is published to make the research more accessible to a wider audience and to include visualizations and interactive features not possible in PDF publications. Continued research on MegaPixles is supported by a 1 year Researcher-in-Residence grant from Karlsruhe HfG.

+

MegaPixels.cc is an independent research project about publicly available face recognition datasets. This website is based, in part, on earlier installations and research projects about facial recognition datasets in 2016-2018, which focused particularly on the MegaFace dataset. Since then it has evolved into a large-scale survey of publicly-available face and person analysis datasets, covering their usage, geographies, and ethics.

+

An academic report and presentation on the findings is forthcoming. This site is published to make the research more accessible to a wider audience and to include visualizations and interactive features not possible in PDF publications. Continued research on MegaPixels is supported by a 1 year Researcher-in-Residence grant from Karlsruhe HfG.

When possible, and once thoroughly verified, data generated for MegaPixels will be made available for download on github.com/adamhrv/megapixels

-

Team

+

Team

  • Adam Harvey: Concept, research, design, computer vision
  • Jules LaPlace: Information and systems architecture, data retrieval, web applications
-

Contributing Researchers

+

Contributing Researchers

  • Berit Gilma: Dataset statistics and discovery
  • Beth (aka Ms. Celeb): Dataset usage verification and research
  • Mathana Stender: Commercial usage verification and research on LFW
-

Code and Libraries

+

Code and Libraries

  • Semantic Scholar for citation aggregation
  • Leaflet.js for maps
  • C3.js for charts
    • -
  • D3.js and ThreeJS for 3D visualizations
    • +
  • ThreeJS for 3D visualizations
  • PDFMiner.Six and Pandas for research paper data analysis
-

Please direct questions, comments, or feedback to mastodon.social/@adamhrv

+

Please direct questions, comments, or feedback to mastodon.social/@adamhrv

-- cgit v1.2.3-70-g09d2 From 103b816c4fb80ca010f39266bf8836b47907a91a Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 31 Mar 2019 17:00:35 +0200 Subject: columns --- site/content/pages/about/faq.md | 12 +++++------- site/content/pages/about/privacy.md | 7 +++---- site/content/pages/about/terms.md | 7 +++---- 3 files changed, 11 insertions(+), 15 deletions(-) (limited to 'site/content/pages') diff --git a/site/content/pages/about/faq.md b/site/content/pages/about/faq.md index cec53813..d5858103 100644 --- a/site/content/pages/about/faq.md +++ b/site/content/pages/about/faq.md @@ -15,14 +15,12 @@ authors: Adam Harvey
- [ page under development ] diff --git a/site/content/pages/about/privacy.md b/site/content/pages/about/privacy.md index e36daf2a..48598623 100644 --- a/site/content/pages/about/privacy.md +++ b/site/content/pages/about/privacy.md @@ -16,11 +16,10 @@ authors: Adam Harvey
diff --git a/site/content/pages/about/terms.md b/site/content/pages/about/terms.md index 7ae6dac7..e03bafaa 100644 --- a/site/content/pages/about/terms.md +++ b/site/content/pages/about/terms.md @@ -17,11 +17,10 @@ authors: Adam Harvey
-- cgit v1.2.3-70-g09d2 From 869701acaa7cd6a3f370121e183c3322f6973c58 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Sun, 31 Mar 2019 17:28:39 +0200 Subject: editing about pages --- site/content/pages/about/disclaimer.md | 41 ---------------------------------- site/content/pages/about/faq.md | 13 +++++------ site/content/pages/about/press.md | 7 +++--- site/content/pages/about/privacy.md | 7 +++--- site/content/pages/about/terms.md | 7 +++--- 5 files changed, 15 insertions(+), 60 deletions(-) delete mode 100644 site/content/pages/about/disclaimer.md (limited to 'site/content/pages') diff --git a/site/content/pages/about/disclaimer.md b/site/content/pages/about/disclaimer.md deleted file mode 100644 index f82a09a0..00000000 --- a/site/content/pages/about/disclaimer.md +++ /dev/null @@ -1,41 +0,0 @@ ------------- - -status: published -title: Disclaimer -desc: MegaPixels Disclaimer -slug: disclaimer -cssclass: about -published: 2018-12-04 -updated: 2018-12-04 -authors: Adam Harvey - ------------- - -# Disclaimer - -
- -
- -(TEMPORARY PAGE) - -Last updated: December 04, 2018 - -The information contained on MegaPixels.cc website (the "Service") is for academic and artistic purposes only. - -MegaPixels.cc assumes no responsibility for errors or omissions in the contents on the Service. - -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. - -## External links disclaimer - -MegaPixels.cc website may contain links to external websites that are not provided or maintained by or in any way affiliated with MegaPixels.cc - -Please note that the MegaPixels.cc does not guarantee the accuracy, relevance, timeliness, or completeness of any information on these external websites. diff --git a/site/content/pages/about/faq.md b/site/content/pages/about/faq.md index cec53813..a0422d10 100644 --- a/site/content/pages/about/faq.md +++ b/site/content/pages/about/faq.md @@ -3,7 +3,7 @@ status: published title: MegaPixels Press and News desc: MegaPixels Press and News -slug: press +slug: faqs cssclass: about published: 2018-12-04 updated: 2018-12-04 @@ -15,12 +15,11 @@ authors: Adam Harvey
diff --git a/site/content/pages/about/press.md b/site/content/pages/about/press.md index 47e1af52..a0780d64 100644 --- a/site/content/pages/about/press.md +++ b/site/content/pages/about/press.md @@ -16,11 +16,10 @@ authors: Adam Harvey
diff --git a/site/content/pages/about/privacy.md b/site/content/pages/about/privacy.md index e36daf2a..48598623 100644 --- a/site/content/pages/about/privacy.md +++ b/site/content/pages/about/privacy.md @@ -16,11 +16,10 @@ authors: Adam Harvey
diff --git a/site/content/pages/about/terms.md b/site/content/pages/about/terms.md index 7ae6dac7..e03bafaa 100644 --- a/site/content/pages/about/terms.md +++ b/site/content/pages/about/terms.md @@ -17,11 +17,10 @@ authors: Adam Harvey
-- cgit v1.2.3-70-g09d2 From 2e73ee5f56d02ee1dc3dbf384d71081c714a0491 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Sun, 31 Mar 2019 17:45:33 +0200 Subject: add tmp msceleb --- .../pages/datasets/msceleb/assets/background.jpg | Bin 0 -> 422970 bytes .../pages/datasets/msceleb/assets/index.jpg | Bin 0 -> 39839 bytes site/content/pages/datasets/msceleb/index.md | 56 +++++++++++++++++++++ 3 files changed, 56 insertions(+) create mode 100644 site/content/pages/datasets/msceleb/assets/background.jpg create mode 100644 site/content/pages/datasets/msceleb/assets/index.jpg create mode 100644 site/content/pages/datasets/msceleb/index.md (limited to 'site/content/pages') diff --git a/site/content/pages/datasets/msceleb/assets/background.jpg b/site/content/pages/datasets/msceleb/assets/background.jpg new file mode 100644 index 00000000..c1cd486e Binary files /dev/null and b/site/content/pages/datasets/msceleb/assets/background.jpg differ diff --git a/site/content/pages/datasets/msceleb/assets/index.jpg b/site/content/pages/datasets/msceleb/assets/index.jpg new file mode 100644 index 00000000..fb3a934a Binary files /dev/null and b/site/content/pages/datasets/msceleb/assets/index.jpg differ diff --git a/site/content/pages/datasets/msceleb/index.md b/site/content/pages/datasets/msceleb/index.md new file mode 100644 index 00000000..eb084eaa --- /dev/null +++ b/site/content/pages/datasets/msceleb/index.md @@ -0,0 +1,56 @@ +------------ + +status: published +title: MS Celeb +desc: MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms +subdesc: The MS Celeb dataset includes over 10,000,000 images and 93,000 identities of semi-public figures collected using the Bing search engine +slug: msceleb +cssclass: dataset +image: assets/background.jpg +year: 2015 +published: 2019-2-23 +updated: 2019-2-23 +authors: Adam Harvey + +------------ + +### sidebar + ++ Published: TBD ++ Images: TBD ++ Faces: TBD ++ Created by: TBD + + +## Microsoft Celeb Dataset (MS Celeb) + +(PAGE UNDER DEVELOPMENT) + +At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. + +Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat + +{% include 'chart.html' %} + +{% include 'piechart.html' %} + +{% include 'map.html' %} + +Add more analysis here + + +{% include 'supplementary_header.html' %} + +{% include 'citations.html' %} + + +### Additional Information + +- The dataset author spoke about his research at the CVPR conference in 2016 + + +### Footnotes + +[^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 -- cgit v1.2.3-70-g09d2 From 1369a597f2f564bf305e0918f91e2a96a4fded82 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 12:06:14 +0200 Subject: brainwash, example sidebar --- .../datasets/brainwash/assets/00818000_640x480.jpg | Bin 33112 -> 0 bytes .../datasets/brainwash/assets/background_540.jpg | Bin 83594 -> 0 bytes .../datasets/brainwash/assets/background_600.jpg | Bin 86425 -> 0 bytes .../brainwash/assets/brainwash_mean_overlay.jpg | Bin 0 -> 150399 bytes .../brainwash/assets/brainwash_mean_overlay_wm.jpg | Bin 0 -> 151713 bytes site/content/pages/datasets/brainwash/index.md | 41 ++++++++++++++++----- 6 files changed, 31 insertions(+), 10 deletions(-) delete mode 100644 site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg delete mode 100644 site/content/pages/datasets/brainwash/assets/background_540.jpg delete mode 100755 site/content/pages/datasets/brainwash/assets/background_600.jpg create mode 100755 site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg create mode 100755 site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg (limited to 'site/content/pages') diff --git a/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg b/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg deleted file mode 100644 index 30c0fcb1..00000000 Binary files a/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg and /dev/null differ diff --git a/site/content/pages/datasets/brainwash/assets/background_540.jpg b/site/content/pages/datasets/brainwash/assets/background_540.jpg deleted file mode 100644 index 5c8c0ad4..00000000 Binary files a/site/content/pages/datasets/brainwash/assets/background_540.jpg and /dev/null differ diff --git a/site/content/pages/datasets/brainwash/assets/background_600.jpg b/site/content/pages/datasets/brainwash/assets/background_600.jpg deleted file mode 100755 index 8f2de697..00000000 Binary files a/site/content/pages/datasets/brainwash/assets/background_600.jpg and /dev/null differ diff --git a/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg new file mode 100755 index 00000000..2f5917e3 Binary files /dev/null and b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg differ diff --git a/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg new file mode 100755 index 00000000..790dbb79 Binary files /dev/null and b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg differ diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 0bf67455..d9bffb39 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -19,28 +19,24 @@ authors: Adam Harvey + Published: 2015 + Images: 11,918 + Faces: 91,146 -+ Created by: Stanford Department of Computer Science ++ Created by: Stanford University (US)
Max Planck Institute for Informatics (DE) + Funded by: Max Planck Center for Visual Computing and Communication -+ Location: Brainwash Cafe, San Franscisco -+ Purpose: Training face detection ++ Purpose: Face detection + Website: stanford.edu -+ Paper: End-to-End People Detection in Crowded Scenes -+ Explicit Consent: No ## Brainwash Dataset (PAGE UNDER DEVELOPMENT) -*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. +*Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to train and validate algorithms for detecting people in crowded scenes. -Before closing in 2017, Brainwash Cafe was a "cafe and laundromat" located in San Francisco's SoMA district. The cafe published a publicy available livestream from the cafe with a view of the cash register, performance stage, and seating area. +Before closing in 2017, The Brainwash Cafe was a combination cafe, laundromat, and performance venue located in San Francisco's SoMA district. The images used for Brainwash dataset were captured on 3 days: October 27, November 13, and November 24 in 2014. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper]. -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]". +Brainwash is not a widely used dataset but since it's publication by Stanford in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on "people head detection in crowded scenes" [^localized_region_context] [^replacement_algorithm]. -![caption: An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)](assets/00425000_960.jpg) +![caption: The pixel-averaged image of all Brainwash dataset images is shown with 81,973 head annotations drawn from the Brainwash training partition. (c) Adam Harvey](assets/brainwash_mean_overlay.jpg) -![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) {% include 'chart.html' %} @@ -55,12 +51,37 @@ Add more analysis here {% include 'citations.html' %} +![caption: An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)](assets/00425000_960.jpg) + +![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) ### Additional Information - The dataset author spoke about his research at the CVPR conference in 2016 +To evaluate the performance of our approach, we collected a +large dataset of images from busy scenes using video footage available from public webcams. In +total, we collect 11917 images with 91146 labeled people. We extract images from video footage at +a fixed interval of 100 seconds to ensure a large variation in images. We allocate 1000 images for +testing and validation, and leave the remaining images for training, making sure that no temporal +overlaps exist between training and test splits. The resulting training set contains 82906 instances. +Test and validation sets contain 4922 and 3318 people instances respectively. Images were labeled +using Amazon Mechanical Turk by a handful of workers pre-selected through their performance on +an example task. We label each person’s head to avoid ambiguity in bounding box locations. The +annotator labels any person she is able to recognize, even if a substantial part of the person is not +visible. Images and annotations will be made available 1 . +Examples of collected images are shown in Fig. 6, and in the video included in the supplemental +material. Images in our dataset include challenges such as people at small scales, strong partial +occlusions, and a large variability in clothing and appearance. + +TODO + +- add bounding boxes to the header image +- remake montage with randomized images, with bboxes +- clean up intro text + + ### Footnotes [^readme]: "readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385. -- cgit v1.2.3-70-g09d2 From 1d261333895cb9305c73d02170e61c5100a39358 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 12:49:57 +0200 Subject: add dataset size --- site/content/pages/datasets/brainwash/index.md | 38 +++++++------------------- 1 file changed, 10 insertions(+), 28 deletions(-) (limited to 'site/content/pages') diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index d9bffb39..6d90e78f 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -2,8 +2,8 @@ status: published title: Brainwash -desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco -subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms +desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014 +subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms slug: brainwash cssclass: dataset image: assets/background.jpg @@ -21,19 +21,18 @@ authors: Adam Harvey + Faces: 91,146 + Created by: Stanford University (US)
Max Planck Institute for Informatics (DE) + Funded by: Max Planck Center for Visual Computing and Communication -+ Purpose: Face detection ++ Purpose: Head detection ++ Download Size: 4.1GB + Website: stanford.edu ## Brainwash Dataset -(PAGE UNDER DEVELOPMENT) +*Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe"[^readme] captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper]. -*Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to train and validate algorithms for detecting people in crowded scenes. +Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance [^localized_region_context] [^replacement_algorithm]. -Before closing in 2017, The Brainwash Cafe was a combination cafe, laundromat, and performance venue located in San Francisco's SoMA district. The images used for Brainwash dataset were captured on 3 days: October 27, November 13, and November 24 in 2014. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper]. - -Brainwash is not a widely used dataset but since it's publication by Stanford in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on "people head detection in crowded scenes" [^localized_region_context] [^replacement_algorithm]. +If you happen to have been at Brainwash cafe in San Franscisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset. ![caption: The pixel-averaged image of all Brainwash dataset images is shown with 81,973 head annotations drawn from the Brainwash training partition. (c) Adam Harvey](assets/brainwash_mean_overlay.jpg) @@ -44,42 +43,25 @@ Brainwash is not a widely used dataset but since it's publication by Stanford in {% include 'map.html' %} -Add more analysis here - +{% include 'citations.html' %} {% include 'supplementary_header.html' %} -{% include 'citations.html' %} - ![caption: An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)](assets/00425000_960.jpg) ![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) -### Additional Information +#### Additional Resources - The dataset author spoke about his research at the CVPR conference in 2016 -To evaluate the performance of our approach, we collected a -large dataset of images from busy scenes using video footage available from public webcams. In -total, we collect 11917 images with 91146 labeled people. We extract images from video footage at -a fixed interval of 100 seconds to ensure a large variation in images. We allocate 1000 images for -testing and validation, and leave the remaining images for training, making sure that no temporal -overlaps exist between training and test splits. The resulting training set contains 82906 instances. -Test and validation sets contain 4922 and 3318 people instances respectively. Images were labeled -using Amazon Mechanical Turk by a handful of workers pre-selected through their performance on -an example task. We label each person’s head to avoid ambiguity in bounding box locations. The -annotator labels any person she is able to recognize, even if a substantial part of the person is not -visible. Images and annotations will be made available 1 . -Examples of collected images are shown in Fig. 6, and in the video included in the supplemental -material. Images in our dataset include challenges such as people at small scales, strong partial -occlusions, and a large variability in clothing and appearance. - TODO - add bounding boxes to the header image - remake montage with randomized images, with bboxes - clean up intro text +- verify quote citations ### Footnotes -- cgit v1.2.3-70-g09d2 From 7aaa8b8cd68d3eb09c68da2b0a64cbe635fdb8d5 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 12:51:52 +0200 Subject: updating datasets --- .../assets/duke_mtmc_cam5_average_comp.jpg | Bin 0 -> 195172 bytes site/content/pages/datasets/duke_mtmc/index.md | 28 ++++++++++++------ .../datasets/uccs/assets/uccs_bboxes_clr_fill.jpg | Bin 146050 -> 0 bytes .../datasets/uccs/assets/uccs_bboxes_grayscale.jpg | Bin 299802 -> 0 bytes .../datasets/uccs/assets/uccs_mean_bboxes_comp.jpg | Bin 0 -> 253215 bytes site/content/pages/datasets/uccs/index.md | 32 +++++++++++++++------ 6 files changed, 43 insertions(+), 17 deletions(-) create mode 100755 site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg delete mode 100644 site/content/pages/datasets/uccs/assets/uccs_bboxes_clr_fill.jpg delete mode 100644 site/content/pages/datasets/uccs/assets/uccs_bboxes_grayscale.jpg create mode 100644 site/content/pages/datasets/uccs/assets/uccs_mean_bboxes_comp.jpg (limited to 'site/content/pages') diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg new file mode 100755 index 00000000..3cd64df1 Binary files /dev/null and b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg differ diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md index de1fa14c..c626ef4e 100644 --- a/site/content/pages/datasets/duke_mtmc/index.md +++ b/site/content/pages/datasets/duke_mtmc/index.md @@ -2,8 +2,8 @@ status: published title: Duke Multi-Target, Multi-Camera Tracking -desc: Duke MTMC is a dataset of CCTV footage of students at Duke University -subdesc: Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 cameras at Duke University campus in March 2014 +desc: Duke MTMC is a dataset of surveillance camera footage of students on Duke University campus +subdesc: Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 HD cameras at Duke University campus in March 2014 slug: duke_mtmc cssclass: dataset image: assets/background.jpg @@ -15,17 +15,27 @@ authors: Adam Harvey ### sidebar -+ Collected: March 19, 2014 -+ Cameras: 8 -+ Video Frames: 2,000,000 -+ Identities: Over 2,000 -+ Used for: Person re-identification,
face recognition -+ Sector: Academic ++ Created: 2014 ++ Identities: Over 2,700 ++ Used for: Face recognition, person re-identification ++ Created by: Computer Science Department, Duke University, Durham, US + Website: duke.edu ## Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC) -(PAGE UNDER DEVELOPMENT) +[ PAGE UNDER DEVELOPMENT ] + +Duke MTMC is a dataset of video recorded on Duke University campus during for the purpose of training, evaluating, and improving *multi-target multi-camera tracking*. The videos were recorded during February and March 2014 and cinclude + +Includes a total of 888.8 minutes of video (ind. verified) + +"We make available a new data set that has more than 2 million frames and more than 2,700 identities. It consists of 8×85 minutes of 1080p video recorded at 60 frames per second from 8 static cameras deployed on the Duke University campus during periods between lectures, when pedestrian traffic is heavy." + +The dataset includes approximately 2,000 annotated identities appearing in 85 hours of video from 8 cameras located throughout Duke University's campus. + +![caption: Duke MTMC pixel-averaged image of camera #5 is shown with the bounding boxes for each student drawn in white. (c) Adam Harvey](assets/duke_mtmc_cam5_average_comp.jpg) + +According to the dataset authors, {% include 'map.html' %} diff --git a/site/content/pages/datasets/uccs/assets/uccs_bboxes_clr_fill.jpg b/site/content/pages/datasets/uccs/assets/uccs_bboxes_clr_fill.jpg deleted file mode 100644 index c8002bb9..00000000 Binary files a/site/content/pages/datasets/uccs/assets/uccs_bboxes_clr_fill.jpg and /dev/null differ diff --git a/site/content/pages/datasets/uccs/assets/uccs_bboxes_grayscale.jpg b/site/content/pages/datasets/uccs/assets/uccs_bboxes_grayscale.jpg deleted file mode 100644 index 6e2833dd..00000000 Binary files a/site/content/pages/datasets/uccs/assets/uccs_bboxes_grayscale.jpg and /dev/null differ diff --git a/site/content/pages/datasets/uccs/assets/uccs_mean_bboxes_comp.jpg b/site/content/pages/datasets/uccs/assets/uccs_mean_bboxes_comp.jpg new file mode 100644 index 00000000..18f4c5ec Binary files /dev/null and b/site/content/pages/datasets/uccs/assets/uccs_mean_bboxes_comp.jpg differ diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index 092638c0..b3d16c2e 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -2,8 +2,8 @@ status: published title: Unconstrained College Students -desc: Unconstrained College Students (UCCS) is a dataset of images ... -subdesc: The UCCS dataset includes ... +desc: Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos of students taken without their knowledge +subdesc: The UCCS dataset includes 16,149 images and 1,732 identities, is used for face recognition and face detection, and funded was several US defense agences slug: uccs cssclass: dataset image: assets/background.jpg @@ -15,16 +15,22 @@ authors: Adam Harvey ### sidebar -+ Collected: TBD -+ Published: TBD -+ Images: TBD -+ Faces: TBD ++ Published: 2018 ++ Images: 16,149 ++ Identities: 1,732 ++ Used for: Face recognition, face detection ++ Created by: Unviversity of Colorado Colorado Springs (US) ++ Funded by: ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR ++ Website: vast.uccs.edu ## Unconstrained College Students ... (PAGE UNDER DEVELOPMENT) +![caption: The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey](assets/uccs_mean_bboxes_comp.jpg) + + {% include 'map.html' %} {% include 'chart.html' %} @@ -36,7 +42,6 @@ authors: Adam Harvey {% include 'citations.html' %} -![Bounding box visualization](assets/uccs_bboxes_grayscale.jpg) ### Research Notes @@ -55,4 +60,15 @@ The more recent UCCS version of the dataset received funding from [^funding_uccs [^funding_sb]: Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013. -[^funding_uccs]: Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3. \ No newline at end of file +[^funding_uccs]: Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3. + + +" In most face detection/recognition datasets, the majority of images are “posed”, i.e. the subjects know they are being photographed, and/or the images are selected for publication in public media. Hence, blurry, occluded and badly illuminated images are generally uncommon in these datasets. In addition, most of these challenges are close-set, i.e. the list of subjects in the gallery is the same as the one used for testing. + +This challenge explores more unconstrained data, by introducing the new UnConstrained College Students (UCCS) dataset, where subjects are photographed using a long-range high-resolution surveillance camera without their knowledge. Faces inside these images are of various poses, and varied levels of blurriness and occlusion. The challenge also creates an open set recognition problem, where unknown people will be seen during testing and must be rejected. + +With this challenge, we hope to foster face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet. + +UnConstrained College Students (UCCS) Dataset + +The UCCS dataset was collected over several months using Canon 7D camera fitted with Sigma 800mm F5.6 EX APO DG HSM lens, taking images at one frame per second, during times when many students were walking on the sidewalk. " \ No newline at end of file -- cgit v1.2.3-70-g09d2 From 4a11e59f991c8ca12ef4ca20a3b01741f311a0e4 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 13:10:52 +0200 Subject: updates, broke smth --- site/assets/css/css.css | 4 +- site/content/pages/datasets/index.md | 2 +- site/content/pages/datasets/uccs/index.md | 3 +- .../research/01_from_1_to_100_pixels/index.md | 52 ++++++++++++++++++++++ .../research/02_what_computers_can_see/index.md | 25 ++++++++++- site/includes/map.html | 2 +- 6 files changed, 81 insertions(+), 7 deletions(-) (limited to 'site/content/pages') diff --git a/site/assets/css/css.css b/site/assets/css/css.css index cd16409a..0ee8a4f3 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -884,7 +884,7 @@ ul.map-legend li.source:before { font-family: Roboto, sans-serif; font-weight: 400; background: #202020; - padding: 15px; + padding: 20px; margin: 10px; } .columns .column:first-of-type { @@ -937,7 +937,7 @@ ul.map-legend li.source:before { margin:0 0 0 40px; } .content-about .team-member p{ - font-size:14px; + font-size:16px; } .content-about .team-member img{ margin:0; diff --git a/site/content/pages/datasets/index.md b/site/content/pages/datasets/index.md index 2e943fbe..c0373d60 100644 --- a/site/content/pages/datasets/index.md +++ b/site/content/pages/datasets/index.md @@ -13,4 +13,4 @@ sync: false # Facial Recognition Datasets -### Survey +Explore publicly available facial recognition datasets. More datasets will be added throughout 2019. diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index b3d16c2e..e0925e07 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -3,8 +3,7 @@ status: published title: Unconstrained College Students desc: Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos of students taken without their knowledge -subdesc: The UCCS dataset includes 16,149 images and 1,732 identities, is used for face recognition and face detection, and funded was several US defense agences -slug: uccs +subdesc: The UCCS dataset includes 16,149 images and 1,732 identities of students at University of Colorado Colorado Springs campus and is used for face recognition and face detection cssclass: dataset image: assets/background.jpg published: 2019-2-23 diff --git a/site/content/pages/research/01_from_1_to_100_pixels/index.md b/site/content/pages/research/01_from_1_to_100_pixels/index.md index a7b863a9..b219dffb 100644 --- a/site/content/pages/research/01_from_1_to_100_pixels/index.md +++ b/site/content/pages/research/01_from_1_to_100_pixels/index.md @@ -56,3 +56,55 @@ Ideas: - "Note that we only keep the images with a minimal side length of 80 pixels." and "a face will be labeled as “Ignore” if it is very difficult to be detected due to blurring, severe deformation and unrecognizable eyes, or the side length of its bounding box is less than 32 pixels." Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf - IBM DiF: "Faces with region size less than 50x50 or inter-ocular distance of less than 30 pixels were discarded. Faces with non-frontal pose, or anything beyond being slightly tilted to the left or the right, were also discarded." + + + + +As the resolution +formatted as rectangular databases of 16 bit RGB-tuples or 8 bit grayscale values + + +To consider how visual privacy applies to real world surveillance situations, the first + +A single 8-bit grayscale pixel with 256 values is enough to represent the entire alphabet `a-Z0-9` with room to spare. + +A 2x2 pixels contains + +Using no more than a 42 pixel (6x7 image) face image researchers [cite] were able to correctly distinguish between a group of 50 people. Yet + +The likely outcome of face recognition research is that more data is needed to improve. Indeed, resolution is the determining factor for all biometric systems, both as training data to increase + +Pixels, typically considered the buiding blocks of images and vidoes, can also be plotted as a graph of sensor values corresponding to the intensity of RGB-calibrated sensors. + + +Wi-Fi and cameras presents elevated risks for transmitting videos and image documentation from conflict zones, high-risk situations, or even sharing on social media. How can new developments in computer vision also be used in reverse, as a counter-forensic tool, to minimize an individual's privacy risk? + +As the global Internet becomes increasingly effecient at turning the Internet into a giant dataset for machine learning, forensics, and data analysing, it would be prudent to also consider tools for decreasing the resolution. The Visual Defense module is just that. What are new ways to minimize the adverse effects of surveillance by dulling the blade. For example, a researcher paper showed that by decreasing a face size to 12x16 it was possible to do 98% accuracy with 50 people. This is clearly an example of + +This research module, tentatively called Visual Defense Tools, aims to explore the + + +### Prior Research + +- MPI visual privacy advisor +- NIST: super resolution +- YouTube blur tool +- WITNESS: blur tool +- Pixellated text +- CV Dazzle +- Bellingcat guide to geolocation +- Peng! magic passport + +### Notes + +- In China, out of the approximately 200 million surveillance cameras only about 15% have enough resolution for face recognition. +- In Apple's FaceID security guide, the probability of someone else's face unlocking your phone is 1 out of 1,000,000. +- In England, the Metropolitan Police reported a false-positive match rate of 98% when attempting to use face recognition to locate wanted criminals. +- In a face recognition trial at Berlin's Sudkreuz station, the false-match rate was 20%. + + +What all 3 examples illustrate is that face recognition is anything but absolute. In a 2017 talk, Jason Matheny the former directory of IARPA, admitted the face recognition is so brittle it can be subverted by using a magic marker and drawing "a few dots on your forehead". In fact face recognition is a misleading term. Face recognition is search engine for faces that can only ever show you the mos likely match. This presents real a real threat to privacy and lends + + +Globally, iPhone users unwittingly agree to 1/1,000,000 probably +relying on FaceID and TouchID to protect their information agree to a \ No newline at end of file diff --git a/site/content/pages/research/02_what_computers_can_see/index.md b/site/content/pages/research/02_what_computers_can_see/index.md index ab4c7884..51621f46 100644 --- a/site/content/pages/research/02_what_computers_can_see/index.md +++ b/site/content/pages/research/02_what_computers_can_see/index.md @@ -100,6 +100,7 @@ A list of 100 things computer vision can see, eg: - Wearing Necktie - Wearing Necklace +for i in {1..9};do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_0$i.MP4;done;for i in {10..20}; do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_$i.MP4;done ## From Market 1501 @@ -149,4 +150,26 @@ Visibility boolean for each keypoint Region annotations (upper clothes, lower clothes, dress, socks, shoes, hands, gloves, neck, face, hair, hat, sunglasses, bag, occluder) Body type (male, female or child) -source: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/h3d/ \ No newline at end of file +source: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/h3d/ + +## From Leeds Sports Pose + +=INDEX(A2:A9,MATCH(datasets!D1,B2:B9,0)) +=VLOOKUP(A2, datasets!A:J, 7, FALSE) + +Right ankle +Right knee +Right hip +Left hip +Left knee +Left ankle +Right wrist +Right elbow +Right shoulder +Left shoulder +Left elbow +Left wrist +Neck +Head top + +source: http://web.archive.org/web/20170915023005/sam.johnson.io/research/lsp.html \ No newline at end of file diff --git a/site/includes/map.html b/site/includes/map.html index 31d577cd..30c248a6 100644 --- a/site/includes/map.html +++ b/site/includes/map.html @@ -12,7 +12,7 @@ -->

- To help understand how {{ metadata.meta.dataset.name_display }} has been used around the world for commercial, military and academic research; publicly available research citations {{ metadata.meta.dataset.name_display }} are collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how {{ metadata.meta.dataset.name_display }} has been used around the world for commercial, military and academic research; publicly available research citing {{ metadata.meta.dataset.name_full} is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location.

-- cgit v1.2.3-70-g09d2 From 2d8b7dd6ea6ccb0293c8839898cf7a1246dc0eb4 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Mon, 1 Apr 2019 14:25:06 +0200 Subject: rebuild --- megapixels/app/site/builder.py | 2 +- megapixels/app/site/loader.py | 3 ++ site/content/pages/datasets/uccs/index.md | 1 + site/includes/map.html | 2 +- site/public/datasets/index.html | 2 +- .../research/01_from_1_to_100_pixels/index.html | 32 ++++++++++++++++++++++ .../research/02_what_computers_can_see/index.html | 19 +++++++++++++ site/public/research/index.html | 18 ++++++++++-- 8 files changed, 74 insertions(+), 5 deletions(-) (limited to 'site/content/pages') diff --git a/megapixels/app/site/builder.py b/megapixels/app/site/builder.py index 603d4788..55a85b0f 100644 --- a/megapixels/app/site/builder.py +++ b/megapixels/app/site/builder.py @@ -57,7 +57,7 @@ def build_page(fn, research_posts, datasets): s3.sync_directory(dirname, s3_dir, metadata) content = parser.parse_markdown(metadata, sections, s3_path, skip_h1=skip_h1) - + html = template.render( metadata=metadata, content=content, diff --git a/megapixels/app/site/loader.py b/megapixels/app/site/loader.py index a544333b..d150942c 100644 --- a/megapixels/app/site/loader.py +++ b/megapixels/app/site/loader.py @@ -85,6 +85,9 @@ def parse_metadata(fn, sections): metadata['meta'] = load_json(dataset_path) if not metadata['meta']: print("Bad metadata? {}".format(dataset_path)) + else: + print(metadata['slug']) + print("{} does not exist!".format(dataset_path)) if 'meta' not in metadata or not metadata['meta']: # dude metadata['meta'] = {} diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index e0925e07..1e3ec097 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -6,6 +6,7 @@ desc: Unconstrained College Students (UCCS) is subdesc: The UCCS dataset includes 16,149 images and 1,732 identities of students at University of Colorado Colorado Springs campus and is used for face recognition and face detection cssclass: dataset image: assets/background.jpg +slug: uccs published: 2019-2-23 updated: 2019-2-23 authors: Adam Harvey diff --git a/site/includes/map.html b/site/includes/map.html index 30c248a6..7511d4c7 100644 --- a/site/includes/map.html +++ b/site/includes/map.html @@ -12,7 +12,7 @@ -->

- To help understand how {{ metadata.meta.dataset.name_display }} has been used around the world for commercial, military and academic research; publicly available research citing {{ metadata.meta.dataset.name_full} is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how {{ metadata.meta.dataset.name_display }} has been used around the world for commercial, military and academic research; publicly available research citing {{ metadata.meta.dataset.name_full }} is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location.

diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index 03b38f8a..1d2630e1 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -28,7 +28,7 @@

Facial Recognition Datasets

-

Survey

+

Explore publicly available facial recognition datasets. More datasets will be added throughout 2019.

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 c91d17ad..37fc367f 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 @@ -80,6 +80,38 @@
  • "Note that we only keep the images with a minimal side length of 80 pixels." and "a face will be labeled as “Ignore” if it is very difficult to be detected due to blurring, severe deformation and unrecognizable eyes, or the side length of its bounding box is less than 32 pixels." Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf
  • IBM DiF: "Faces with region size less than 50x50 or inter-ocular distance of less than 30 pixels were discarded. Faces with non-frontal pose, or anything beyond being slightly tilted to the left or the right, were also discarded."
    • +

    As the resolution +formatted as rectangular databases of 16 bit RGB-tuples or 8 bit grayscale values

    +

    To consider how visual privacy applies to real world surveillance situations, the first

    +

    A single 8-bit grayscale pixel with 256 values is enough to represent the entire alphabet a-Z0-9 with room to spare.

    +

    A 2x2 pixels contains

    +

    Using no more than a 42 pixel (6x7 image) face image researchers [cite] were able to correctly distinguish between a group of 50 people. Yet

    +

    The likely outcome of face recognition research is that more data is needed to improve. Indeed, resolution is the determining factor for all biometric systems, both as training data to increase

    +

    Pixels, typically considered the buiding blocks of images and vidoes, can also be plotted as a graph of sensor values corresponding to the intensity of RGB-calibrated sensors.

    +

    Wi-Fi and cameras presents elevated risks for transmitting videos and image documentation from conflict zones, high-risk situations, or even sharing on social media. How can new developments in computer vision also be used in reverse, as a counter-forensic tool, to minimize an individual's privacy risk?

    +

    As the global Internet becomes increasingly effecient at turning the Internet into a giant dataset for machine learning, forensics, and data analysing, it would be prudent to also consider tools for decreasing the resolution. The Visual Defense module is just that. What are new ways to minimize the adverse effects of surveillance by dulling the blade. For example, a researcher paper showed that by decreasing a face size to 12x16 it was possible to do 98% accuracy with 50 people. This is clearly an example of

    +

    This research module, tentatively called Visual Defense Tools, aims to explore the

    +

    Prior Research

    +
      +
    • MPI visual privacy advisor
      • +
    • NIST: super resolution
      • +
    • YouTube blur tool
      • +
    • WITNESS: blur tool
      • +
    • Pixellated text
      • +
    • CV Dazzle
      • +
    • Bellingcat guide to geolocation
      • +
    • Peng! magic passport
      • +
    +

    Notes

    +
      +
    • In China, out of the approximately 200 million surveillance cameras only about 15% have enough resolution for face recognition.
      • +
    • In Apple's FaceID security guide, the probability of someone else's face unlocking your phone is 1 out of 1,000,000.
      • +
    • In England, the Metropolitan Police reported a false-positive match rate of 98% when attempting to use face recognition to locate wanted criminals.
      • +
    • In a face recognition trial at Berlin's Sudkreuz station, the false-match rate was 20%.
      • +
    +

    What all 3 examples illustrate is that face recognition is anything but absolute. In a 2017 talk, Jason Matheny the former directory of IARPA, admitted the face recognition is so brittle it can be subverted by using a magic marker and drawing "a few dots on your forehead". In fact face recognition is a misleading term. Face recognition is search engine for faces that can only ever show you the mos likely match. This presents real a real threat to privacy and lends

    +

    Globally, iPhone users unwittingly agree to 1/1,000,000 probably +relying on FaceID and TouchID to protect their information agree to a

    1. NIST 906932. Performance Assessment of Face Recognition Using Super-Resolution. Shuowen Hu, Robert Maschal, S. Susan Young, Tsai Hong Hong, Jonathon P. Phillips↩

      2. diff --git a/site/public/research/02_what_computers_can_see/index.html b/site/public/research/02_what_computers_can_see/index.html index 9389bf84..0fce1373 100644 --- a/site/public/research/02_what_computers_can_see/index.html +++ b/site/public/research/02_what_computers_can_see/index.html @@ -126,6 +126,7 @@
    2. Wearing Necktie
    3. Wearing Necklace
      4. +

      for i in {1..9};do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_0$i.MP4;done;for i in {10..20}; do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_$i.MP4;done

      From Market 1501

      The 27 attributes are:

      @@ -269,6 +270,24 @@ Visibility boolean for each keypoint Region annotations (upper clothes, lower clothes, dress, socks, shoes, hands, gloves, neck, face, hair, hat, sunglasses, bag, occluder) Body type (male, female or child)

      source: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/h3d/

      +

      From Leeds Sports Pose

      +

      =INDEX(A2:A9,MATCH(datasets!D1,B2:B9,0)) +=VLOOKUP(A2, datasets!A:J, 7, FALSE)

      +

      Right ankle +Right knee +Right hip +Left hip +Left knee +Left ankle +Right wrist +Right elbow +Right shoulder +Left shoulder +Left elbow +Left wrist +Neck +Head top

      +

      source: http://web.archive.org/web/20170915023005/sam.johnson.io/research/lsp.html

      diff --git a/site/public/research/index.html b/site/public/research/index.html index 303732f8..0ef57043 100644 --- a/site/public/research/index.html +++ b/site/public/research/index.html @@ -26,8 +26,22 @@
      -

      Research Blog

      -
      +
      +

      Research

      +
      +
      +
      Posted
      +
      2018-12-15
      +
      +
      +
      By
      +
      Adam Harvey
      +
      + +
      +
      + +
      -- cgit v1.2.3-70-g09d2 From 36cda707b6b03a7b2aa10e6b17ca780797916060 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Mon, 1 Apr 2019 19:45:15 +0200 Subject: test csv --- .gitignore | 3 +++ client/index.js | 8 +++++-- client/table/citations.table.js | 28 ++++++++++------------ client/table/file.table.js | 42 +++++++++++++++++++++++++-------- client/util/index.js | 9 +++++++ package-lock.json | 8 +++---- package.json | 2 +- site/content/pages/test/assets/test.csv | 8 +++++++ site/content/pages/test/csv.md | 4 ++-- site/public/datasets/index.html | 12 +++++----- site/public/test/csv/index.html | 2 +- 11 files changed, 84 insertions(+), 42 deletions(-) create mode 100644 site/content/pages/test/assets/test.csv (limited to 'site/content/pages') diff --git a/.gitignore b/.gitignore index 74a8a054..e41e7c36 100644 --- a/.gitignore +++ b/.gitignore @@ -170,3 +170,6 @@ site/public/user_content site/datasets/final/*.csv +flask.log +flask.log.* + diff --git a/client/index.js b/client/index.js index 668aebfb..5e36d341 100644 --- a/client/index.js +++ b/client/index.js @@ -65,14 +65,17 @@ function runApplets() { let opt = null payload.cmd = cmd payload.partz = cmdPartz + if (payload.cmd === 'load_file') { + payload.url = 'https://nyc3.digitaloceanspaces.com/megapixels/v1' + cmdPartz.shift() + return [el, payload] + } + if (payload.partz.length) { opt = payload.partz.shift().trim() if (opt.indexOf('http') === 0) { dataset = null url = opt } else if (opt.indexOf('assets') === 0) { - let pathname = window.location.pathname.replace('index.html', '') - url = 'https://nyc3.digitaloceanspaces.com/megapixels/v1' + pathname + opt dataset = null // console.log(url) } else { @@ -95,6 +98,7 @@ function runApplets() { } payload.dataset = dataset payload.url = url + console.log(payload) return [el, payload] }).filter(a => !!a) const withDataset = applets.map(a => a[1].dataset ? a[1] : null).filter(a => !!a) diff --git a/client/table/citations.table.js b/client/table/citations.table.js index f9599f5d..0092015f 100644 --- a/client/table/citations.table.js +++ b/client/table/citations.table.js @@ -2,10 +2,9 @@ import React, { Component } from 'react' import { bindActionCreators } from 'redux' import { connect } from 'react-redux' import { ReactTabulator } from 'react-tabulator' -import MultiValueFormatter from "react-tabulator/lib/formatters/MultiValueFormatter" import { Loader } from '../common' -import { toArray, toTuples } from '../util' +import { toArray, toTuples, domainFromUrl } from '../util' export const citationsColumns = [ { title: 'Title', field: 'title', sorter: 'string' }, @@ -42,13 +41,7 @@ class CitationsTable extends Component { : (citation.doi && citation.doi.length) ? citation.doi[0] : 'https://www.semanticscholar.org/paper/' + citation.id - let pdf_text - const pdf_partz = pdf_link.split('/')[2].split('.') - if (pdf_partz.length > 2 && pdf_partz[pdf_partz.length - 2].length == 2) { - pdf_text = pdf_partz.slice(-3).join('.') - } else { - pdf_text = pdf_partz.slice(-2).join('.') - } + let pdf_text = domainFromUrl(pdf_link) return { title: citation.title, institution: citation.addresses.map(a => a.name).sort().join('; '), @@ -83,13 +76,16 @@ class CitationsTable extends Component { if (!formattedCitations.length) return return (
      - this.updateFilter(e.target.value)} - className='q' - placeholder='Enter text to search citations...' - /> +
      + this.updateFilter(e.target.value)} + className='q' + placeholder='Enter text to search citations...' + /> + r.text()) .then(text => { try { + const keys = text.split('\n')[0].split(',').map(s => s.trim().replace(/\"/,'')) const data = csv.toJSON(text, { headers: { included: true } }) - this.setState({ data }) + // console.log(data) + const columns = this.getColumns(keys, data, payload.fields) + this.setState({ keys, data, columns }) } catch (e) { console.error("error making json:", payload.url) console.error(e) @@ -27,26 +34,41 @@ class FileTable extends Component { }) } - getColumns(payload) { - let { cmd, url, fields } = payload - return ((fields && fields.length) ? fields[0] : '').split(', ').map(field => { + getColumns(keys, data, fields) { + let titles = fields.length ? fields[0].split(', ') : keys + let numberFields = [] + let columns = keys.map((field, i) => { + const title = titles[i] || field + if (field.match('url')) { + let textField = field.replace('url', 'label') + data.forEach(el => el[textField] = domainFromUrl(el[field])) + return { + title, + field: textField, + formatter: 'link', + formatterParams: { target: "_blank", urlField: field, }, + sorter: 'string' + } + } switch (field) { + case 'images': + case 'year': + return { title, field: field.toLowerCase(), sorter: 'number' } default: - return { title: field, field: field.toLowerCase(), sorter: 'string' } + return { title, field: field.toLowerCase(), sorter: 'string' } } }) + return columns } render() { const { payload } = this.props - const { paper, citations } = payload.data - const columns = getColumns(payload) if (!this.state.data.length) { return } return ( (n * 100).toFixed(1) + '%' export const px = (n, w) => Math.round(n * w) + 'px' export const clamp = (n, a, b) => n < a ? a : n < b ? n : b +export const domainFromUrl = url => { + const partz = url.split('/')[2].split('.') + if (partz.length > 2 && partz[partz.length - 2].length == 2) { + return partz.slice(-3).join('.') + } else { + return partz.slice(-2).join('.') + } +} + /* URLs */ export const preloadImage = opt => { diff --git a/package-lock.json b/package-lock.json index 4e9d6fac..43ee0cbf 100644 --- a/package-lock.json +++ b/package-lock.json @@ -3673,9 +3673,9 @@ } }, "file-saver": { - "version": "2.0.0", - "resolved": "https://registry.npmjs.org/file-saver/-/file-saver-2.0.0.tgz", - "integrity": "sha512-cYM1ic5DAkg25pHKgi5f10ziAM7RJU37gaH1XQlyNDrtUnzhC/dfoV9zf2OmF0RMKi42jG5B0JWBnPQqyj/G6g==" + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/file-saver/-/file-saver-2.0.1.tgz", + "integrity": "sha512-dCB3K7/BvAcUmtmh1DzFdv0eXSVJ9IAFt1mw3XZfAexodNRoE29l3xB2EX4wH2q8m/UTzwzEPq/ArYk98kUkBQ==" }, "filename-regex": { "version": "2.0.1", @@ -8623,7 +8623,7 @@ }, "sprintf-js": { "version": "1.0.3", - "resolved": "https://registry.npmjs.org/sprintf-js/-/sprintf-js-1.0.3.tgz", + "resolved": "http://registry.npmjs.org/sprintf-js/-/sprintf-js-1.0.3.tgz", "integrity": "sha1-BOaSb2YolTVPPdAVIDYzuFcpfiw=", "dev": true }, diff --git a/package.json b/package.json index 6238e7e3..75fbebb7 100644 --- a/package.json +++ b/package.json @@ -38,7 +38,7 @@ "exif-reader": "^1.0.2", "exifreader": "^2.5.0", "fetch-jsonp": "^1.1.3", - "file-saver": "^2.0.0-rc.3", + "file-saver": "^2.0.1", "history": "^4.7.2", "leaflet": "^1.3.4", "leaflet-arc": "^1.0.2", diff --git a/site/content/pages/test/assets/test.csv b/site/content/pages/test/assets/test.csv new file mode 100644 index 00000000..7156a814 --- /dev/null +++ b/site/content/pages/test/assets/test.csv @@ -0,0 +1,8 @@ +name,images,year,gender,description,url +aardvark,100,2019,m,bim da,https://asdf.us/ +bobcat,10,2017,f,in a tree,https://asdf.us/ +cow,20,2012,f,moooo,https://asdf.us/ +doe,2,2016,f,doe a deer,https://asdf.us/ +earwig,1,2017,m,just a bug,https://i.asdf.us/ +frog,17,2018,f,ribbit ribbit,https://i.asdf.us/ +giraffe,23,2009,m,i get around,https://adsf.us/ diff --git a/site/content/pages/test/csv.md b/site/content/pages/test/csv.md index b5f37754..85f714b4 100644 --- a/site/content/pages/test/csv.md +++ b/site/content/pages/test/csv.md @@ -15,6 +15,6 @@ authors: Megapixels ### [← Back to test index](/test/) ``` -load_file /datasets/lfw/assets/lfw_names_gender_kg_min.csv -Name, Images, Gender, Description +load_file /site/test/assets/test.csv +Name, Images, Year, Gender, Description, URL ``` diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index 1d2630e1..3a2dbd52 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -42,8 +42,8 @@ Brainwash
      2015
      -
      Decoding image into set of people detections.
      -
      11,918 images
      +
      Head detection
      +
      11,917 images
      @@ -90,7 +90,7 @@ MS Celeb
      2016
      -
      face recognition
      +
      Large-scale face recognition
      1,000,000 images
      100,000
      @@ -114,9 +114,9 @@ Unconstrained College Students
      2018
      -
      Unconstrained face recognition
      +
      Face recognition, face detection
      16,149 images
      -
      4,362
      +
      1,732
      @@ -126,7 +126,7 @@ VIPeR
      2007
      -
      pedestrian re-identification
      +
      Person re-identification
      1,264 images
      632
      diff --git a/site/public/test/csv/index.html b/site/public/test/csv/index.html index 3257716f..70a7d257 100644 --- a/site/public/test/csv/index.html +++ b/site/public/test/csv/index.html @@ -28,7 +28,7 @@

      CSV Test

      ← Back to test index

      -
      +
      -- cgit v1.2.3-70-g09d2 From 79ca5c75243e4d94a7924d1bda8666123f398d9c Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 19:50:44 +0200 Subject: . --- site/content/pages/datasets/uccs/index.md | 70 ++++++++++++++++++++++++------- site/includes/map.html | 2 +- 2 files changed, 55 insertions(+), 17 deletions(-) (limited to 'site/content/pages') diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index e0925e07..80ce0836 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -2,6 +2,7 @@ status: published title: Unconstrained College Students +slug: uccs desc: Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos of students taken without their knowledge subdesc: The UCCS dataset includes 16,149 images and 1,732 identities of students at University of Colorado Colorado Springs campus and is used for face recognition and face detection cssclass: dataset @@ -27,6 +28,50 @@ authors: Adam Harvey (PAGE UNDER DEVELOPMENT) +Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, subjects were "photographed using a long-range high-resolution surveillance camera without their knowledge" [^funding_sb]. The images were captured using a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens pointed out the window of an office. + +The UCCS dataset was funded by ODNI (Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative, Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. + +The images in UCCS include students walking between classes on campus over 19 days in 2012 - 2013. The dates include: + +| Year | Month | Day | Date | Time Range | Photos | +| --- | --- | --- | --- | --- | --- | +| 2012 | Februay | --- | 23 | - | 132 | +| 2012 | March | --- | 6 | - | - | +| 2012 | March | --- | 8 | - | - | +| 2012 | March | --- | 13 | - | - | +| 2012 | Februay | --- | 23 | - | 132 | +| 2012 | March | --- | 6 | - | - | +| 2012 | March | --- | 8 | - | - | +| 2012 | March | --- | 13 | - | - | +| 2012 | Februay | --- | 23 | - | 132 | +| 2012 | March | --- | 6 | - | - | +| 2012 | March | --- | 8 | - | - | +| 2012 | March | --- | 13 | - | - | +| 2012 | Februay | --- | 23 | - | 132 | +| 2012 | March | --- | 6 | - | - | +| 2012 | March | --- | 8 | - | - | +| 2012 | March | --- | 13 | - | - | +| 2012 | Februay | --- | 23 | - | 132 | +| 2012 | March | --- | 6 | - | - | +| 2012 | March | --- | 8 | - | - | + + +2012-03-20 +2012-03-22 +2012-04-03 +2012-04-12 +2012-04-17 +2012-04-24 +2012-04-25 +2012-04-26 +2013-01-28 +2013-01-29 +2013-02-13 +2013-02-19 +2013-02-20 +2013-02-26 + ![caption: The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey](assets/uccs_mean_bboxes_comp.jpg) @@ -36,13 +81,9 @@ authors: Adam Harvey {% include 'piechart.html' %} -{% include 'supplementary_header.html' %} - {% include 'citations.html' %} - - -### Research Notes +{% include 'supplementary_header.html' %} The original Sapkota and Boult dataset, from which UCCS is derived, received funding from[^funding_sb]: @@ -57,17 +98,14 @@ The more recent UCCS version of the dataset received funding from [^funding_uccs - IARPA (Intelligence Advance Research Projects Activity) R&D contract 2014-14071600012 +### TODO -[^funding_sb]: Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013. -[^funding_uccs]: Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3. - - -" In most face detection/recognition datasets, the majority of images are “posed”, i.e. the subjects know they are being photographed, and/or the images are selected for publication in public media. Hence, blurry, occluded and badly illuminated images are generally uncommon in these datasets. In addition, most of these challenges are close-set, i.e. the list of subjects in the gallery is the same as the one used for testing. +- add tabulator module for dates +- parse dates into CSV using Python +- get google image showing line of sight? +- fix up quote/citations -This challenge explores more unconstrained data, by introducing the new UnConstrained College Students (UCCS) dataset, where subjects are photographed using a long-range high-resolution surveillance camera without their knowledge. Faces inside these images are of various poses, and varied levels of blurriness and occlusion. The challenge also creates an open set recognition problem, where unknown people will be seen during testing and must be rejected. +### footnotes -With this challenge, we hope to foster face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet. - -UnConstrained College Students (UCCS) Dataset - -The UCCS dataset was collected over several months using Canon 7D camera fitted with Sigma 800mm F5.6 EX APO DG HSM lens, taking images at one frame per second, during times when many students were walking on the sidewalk. " \ No newline at end of file +[^funding_sb]: Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013. +[^funding_uccs]: Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3. \ No newline at end of file diff --git a/site/includes/map.html b/site/includes/map.html index 30c248a6..7511d4c7 100644 --- a/site/includes/map.html +++ b/site/includes/map.html @@ -12,7 +12,7 @@ -->

      - To help understand how {{ metadata.meta.dataset.name_display }} has been used around the world for commercial, military and academic research; publicly available research citing {{ metadata.meta.dataset.name_full} is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how {{ metadata.meta.dataset.name_display }} has been used around the world for commercial, military and academic research; publicly available research citing {{ metadata.meta.dataset.name_full }} is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location.

      -- cgit v1.2.3-70-g09d2 From c78730887ed63b4c1cb83cf0f2cd7451a964c523 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 23:27:52 +0200 Subject: update about section --- site/content/pages/about/legal.md | 88 +++++++++++++++++++ site/content/pages/about/privacy.md | 164 ------------------------------------ site/content/pages/about/terms.md | 73 ---------------- 3 files changed, 88 insertions(+), 237 deletions(-) create mode 100644 site/content/pages/about/legal.md delete mode 100644 site/content/pages/about/privacy.md delete mode 100644 site/content/pages/about/terms.md (limited to 'site/content/pages') diff --git a/site/content/pages/about/legal.md b/site/content/pages/about/legal.md new file mode 100644 index 00000000..089f32d7 --- /dev/null +++ b/site/content/pages/about/legal.md @@ -0,0 +1,88 @@ +------------ + +status: published +title: Privacy Policy +desc: MegaPixels Privacy Policy +slug: privacy-policy +cssclass: about +published: 2018-12-04 +updated: 2018-12-04 +authors: Adam Harvey + +------------ + +# Legal + +
      + +
      + +MegaPixels.cc Terms and Privacy + +MegaPixels is an independent art and research project about the origins and ethics of publicly available face analysis image datasets. By accessing MegaPixels (the *Service* or *Services*) you agree to the terms and conditions set forth below. + +### Changes + +We reserve the right, at our sole discretion, to modify or replace these Terms at any time. If a revision is material we will try to provide at least 30 days notice prior to any new terms taking effect. What constitutes a material change will be determined at our sole discretion. + +By continuing to access or use our Service after those revisions become effective, you agree to be bound by the revised terms. If you do not agree to the new terms, please stop using the Service. + + +## Privacy + +The MegaPixels site has been designed to minimize the amount of network requests to 3rd party services and therefore prioritize the privacy of the viewer by only loading local dependencies. Additionaly, this site does not use any anaytics programs to monitor site viewers. In fact, the only data collected are the necessary server logs that used only for preventing misuse, which are deleteted at regular short-term intervals. + +## 3rd Party Services + +In order to provide certain features of the site, some 3rd party services are needed. Currently, the MegaPixels.cc site uses two 3rd party services: (1) Leaflet.js for the interactive map and (2 Digital Ocean Spaces as a condent delivery network. Both services encrypt your requests to their server using HTTPS and neither service requires storing any cookies or authentication. However, both services will store files in your web browser's local cache (local storage) to improve loading performance. None of these local storage files are using for analytics, cookie-like technologies, tracking, or any similar purpose. + +### Links To Other Web Sites + +The MegaPixels.cc contains many links to 3rd party websites, especically in the list of citations that are provided for each dataset. This website has no control over and assumes no responsibility for, the content, privacy policies, or practices of any third party web sites or services. You further acknowledge and agree that megapixels.cc shall not be responsible or liable, directly or indirectly, for any damage or loss caused or alleged to be caused by or in connection with use of or reliance on any such content, goods or services available on or through any such web sites or services. + +We advise you to read the terms and conditions and privacy policies of any third-party web sites or services that you visit. + + +### The Information We Provide + +While every intention is made to verify and publish only verifiablenformation, at times amendments to accuracy may be required. In no event will the operators of this site be liable for your use or misuse of the information provided. + +We may terminate or suspend access to our Service immediately, without prior notice or liability, for any reason whatsoever, including without limitation if you breach the Terms. + +All provisions of the Terms which by their nature should survive termination shall survive termination, including, without limitation, ownership provisions, warranty disclaimers, indemnity and limitations of liability. + +### Prohibited Uses + +You may not access or use, or attempt to access or use, the Services to take any action that could harm us or a third party. You may not use the Services in violation of applicable laws or in violation of our or any third party’s intellectual property or other proprietary or legal rights. You further agree that you shall not attempt (or encourage or support anyone else's attempt) to circumvent, reverse engineer, decrypt, or otherwise alter or interfere with the Services, or any content thereof, or make any unauthorized use thereof. + +Without prior written consent, you shall not: + +(i) access any part of the Services, Content, data or information you do not have permission or authorization to access; + +(ii) use robots, spiders, scripts, service, software or any manual or automatic device, tool, or process designed to data mine or scrape the Content, data or information from the Services, or otherwise access or collect the Content, data or information from the Services using automated means; + +(iii) use services, software or any manual or automatic device, tool, or process designed to circumvent any restriction, condition, or technological measure that controls access to the Services in any way, including overriding any security feature or bypassing or circumventing any access controls or use limits of the Services; + +(iv) cache or archive the Content (except for a public search engine’s use of spiders for creating search indices); + +(v) take action that imposes an unreasonable or disproportionately large load on our network or infrastructure; and + +(vi) do anything that could disable, damage or change the functioning or appearance of the Services, including the presentation of advertising. + +Engaging in a prohibited use of the Services may result in civil, criminal, and/or administrative penalties, fines, or sanctions against the user and those assisting the user. + +### Governing Law + +These Terms shall be governed and construed in accordance with the laws of Berlin, Germany, without regard to its conflict of law provisions. + +Our failure to enforce any right or provision of these Terms will not be considered a waiver of those rights. If any provision of these Terms is held to be invalid or unenforceable by a court, the remaining provisions of these Terms will remain in effect. These Terms constitute the entire agreement between us regarding our Service, and supersede and replace any prior agreements we might have between us regarding the Service. + +### Indemnity + +You hereby indemnify, defend and hold harmless MegaPixels (and its creators) and all officers, directors, owners, agents, information providers, affiliates, licensors and licensees (collectively, the "Indemnified Parties") from and against any and all liability and costs, including, without limitation, reasonable attorneys' fees, incurred by the Indemnified Parties in connection with any claim arising out of any breach by you or any user of your account of these Terms of Service or the foregoing representations, warranties and covenants. You shall cooperate as fully as reasonably required in the defense of any such claim. We reserves the right, at its own expense, to assume the exclusive defense and control of any matter subject to indemnification by you. \ No newline at end of file diff --git a/site/content/pages/about/privacy.md b/site/content/pages/about/privacy.md deleted file mode 100644 index 48598623..00000000 --- a/site/content/pages/about/privacy.md +++ /dev/null @@ -1,164 +0,0 @@ ------------- - -status: published -title: Privacy Policy -desc: MegaPixels Privacy Policy -slug: privacy-policy -cssclass: about -published: 2018-12-04 -updated: 2018-12-04 -authors: Adam Harvey - ------------- - -# Privacy Policy - -
      - -
      - -(TEMPORARY PAGE) - -A summary of our privacy policy is as follows: - -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. - -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. - ----- - -A more complete legal version is below: - -**This is a boilerplate Privacy policy from ** - -**Needs to be reviewed** - -Effective date: December 04, 2018 - -megapixels.cc ("us", "we", or "our") operates the WebsiteName website (hereinafter referred to as the "Service"). - -This page informs you of our policies regarding the collection, use, and disclosure of personal data when you use our Service and the choices you have associated with that data. - -We use your data to provide and improve the Service. By using the Service, you agree to the collection and use of information in accordance with this policy. Unless otherwise defined in this Privacy Policy, the terms used in this Privacy Policy have the same meanings as in our Terms and Conditions, accessible from WebsiteName - -## Definitions - -**Service** - -Service is the MegaPixels website operated by megapixels.cc - -**Personal Data** - -Personal Data means data about a living individual who can be identified from those data (or from those and other information either in our possession or likely to come into our possession). - -**Usage Data** - -Usage Data is data collected automatically either generated by the use of the Service or from the Service infrastructure itself - -## Information Collection and Use - -We collect several different types of information for various purposes to provide and improve our Service to you. - -## Types of Data Collected - -### Personal Data - -While using our Service, we may ask you to provide us with certain personally identifiable information that can be used to contact or identify you ("Personal Data"). Personally identifiable information may include, but is not limited to: - -- Cookies and Usage Data - -### Usage Data - -We may also collect information how the Service is accessed and used ("Usage Data"). This Usage Data may include information such as your computer's Internet Protocol address (e.g. IP address), browser type, browser version, the pages of our Service that you visit, the time and date of your visit, the time spent on those pages, unique device identifiers and other diagnostic data. - -### Tracking & Cookies Data - -We use cookies and similar tracking technologies to track the activity on our Service and we hold certain information. -Cookies are files with a small amount of data which may include an anonymous unique identifier. Cookies are sent to your browser from a website and stored on your device. Other tracking technologies are also used such as beacons, tags and scripts to collect and track information and to improve and analyse our Service. - -You can instruct your browser to refuse all cookies or to indicate when a cookie is being sent. However, if you do not accept cookies, you may not be able to use some portions of our Service. -Examples of Cookies we use: - -- Session Cookies. We use Session Cookies to operate our Service. -- Preference Cookies. We use Preference Cookies to remember your preferences and various settings. -- Security Cookies. We use Security Cookies for security purposes. - - -## Use of Data - -megapixels.cc uses the collected data for various purposes: - -- To provide and maintain the Service -- To notify you about changes to our Service -- To allow you to participate in interactive features of our Service when you choose to do so -- To provide customer care and support -- To provide analysis or valuable information so that we can improve the Service -- To monitor the usage of the Service -- To detect, prevent and address technical issues - -## Transfer Of Data - -Your information, including Personal Data, may be transferred to — and maintained on — computers located outside of your state, province, country or other governmental jurisdiction where the data protection laws may differ than those from your jurisdiction. - -If you are located outside Germany and choose to provide information to us, please note that we transfer the data, including Personal Data, to Germany and process it there. -Your consent to this Privacy Policy followed by your submission of such information represents your agreement to that transfer. -megapixels.cc will take all steps reasonably necessary to ensure that your data is treated securely and in accordance with this Privacy Policy and no transfer of your Personal Data will take place to an organization or a country unless there are adequate controls in place including the security of your data and other personal information. - -## Disclosure Of Data - -### Legal Requirements - -megapixels.cc may disclose your Personal Data in the good faith belief that such action is necessary to: - -- To comply with a legal obligation -- To protect and defend the rights or property of megapixels.cc -- To prevent or investigate possible wrongdoing in connection with the Service -- To protect the personal safety of users of the Service or the public -- To protect against legal liability - - - -## Security of Data - -The security of your data is important to us but remember that no method of transmission over the Internet or method of electronic storage is 100% secure. While we strive to use commercially acceptable means to protect your Personal Data, we cannot guarantee its absolute security. - -## Service Providers - -We may employ third party companies and individuals to facilitate our Service ("Service Providers"), to provide the Service on our behalf, to perform Service-related services or to assist us in analyzing how our Service is used. - -These third parties have access to your Personal Data only to perform these tasks on our behalf and are obligated not to disclose or use it for any other purpose. - - - - -## Links to Other Sites - -Our Service may contain links to other sites that are not operated by us. If you click a third party link, you will be directed to that third party's site. We strongly advise you to review the Privacy Policy of every site you visit. -We have no control over and assume no responsibility for the content, privacy policies or practices of any third party sites or services. - - -## Children's Privacy - -Our Service does not address anyone under the age of 18 ("Children"). - -We do not knowingly collect personally identifiable information from anyone under the age of 18. If you are a parent or guardian and you are aware that your Child has provided us with Personal Data, please contact us. If we become aware that we have collected Personal Data from children without verification of parental consent, we take steps to remove that information from our servers. - - -## Changes to This Privacy Policy - -We may update our Privacy Policy from time to time. We will notify you of any changes by posting the new Privacy Policy on this page. -We will let you know via email and/or a prominent notice on our Service, prior to the change becoming effective and update the "effective date" at the top of this Privacy Policy. -You are advised to review this Privacy Policy periodically for any changes. Changes to this Privacy Policy are effective when they are posted on this page. - - -## Contact Us - -If you have any questions about this Privacy Policy, please contact us: - -- By visiting this page on our website: \ No newline at end of file diff --git a/site/content/pages/about/terms.md b/site/content/pages/about/terms.md deleted file mode 100644 index e03bafaa..00000000 --- a/site/content/pages/about/terms.md +++ /dev/null @@ -1,73 +0,0 @@ ------------- - -status: published -title: Terms of Use -desc: MegaPixels Terms of Use and Privacy Policy -slug: terms -cssclass: about -published: 2018-12-04 -updated: 2018-12-04 -authors: Adam Harvey - ------------- - - -# Terms and Conditions ("Terms") - -
      - -
      - -(TEMPORARY PAGE) - -(FPO: this is only example text) - -Last updated: December 04, 2018 - -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"). - -Your access to and use of the Service is conditioned on your acceptance of and compliance with these Terms. - -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. - - -### Links To Other Web Sites - -Our Service may contain links to third-party web sites or services that are not owned or controlled by megapixels.cc. - -megapixels.cc has no control over, and assumes no responsibility for, the content, privacy policies, or practices of any third party web sites or services. You further acknowledge and agree that megapixels.cc shall not be responsible or liable, directly or indirectly, for any damage or loss caused or alleged to be caused by or in connection with use of or reliance on any such content, goods or services available on or through any such web sites or services. - -We strongly advise you to read the terms and conditions and privacy policies of any third-party web sites or services that you visit. - - -### Termination - -We may terminate or suspend access to our Service immediately, without prior notice or liability, for any reason whatsoever, including without limitation if you breach the Terms. - -All provisions of the Terms which by their nature should survive termination shall survive termination, including, without limitation, ownership provisions, warranty disclaimers, indemnity and limitations of liability. - - - -### Governing Law - -These Terms shall be governed and construed in accordance with the laws of Berlin, Germany, without regard to its conflict of law provisions. - -Our failure to enforce any right or provision of these Terms will not be considered a waiver of those rights. If any provision of these Terms is held to be invalid or unenforceable by a court, the remaining provisions of these Terms will remain in effect. These Terms constitute the entire agreement between us regarding our Service, and supersede and replace any prior agreements we might have between us regarding the Service. - - -### Changes - -We reserve the right, at our sole discretion, to modify or replace these Terms at any time. If a revision is material we will try to provide at least 30 days notice prior to any new terms taking effect. What constitutes a material change will be determined at our sole discretion. - -By continuing to access or use our Service after those revisions become effective, you agree to be bound by the revised terms. If you do not agree to the new terms, please stop using the Service. - - -### Contact Us - -If you have any questions about these Terms, please contact us. \ No newline at end of file -- cgit v1.2.3-70-g09d2 From b8f5c87e823d0b68d5e30f8de453ba90dcadc241 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 2 Apr 2019 14:38:27 +0200 Subject: sidebar from spreadsheet --- megapixels/app/site/loader.py | 38 ++++++++++++++++++++++ megapixels/app/site/parser.py | 11 +------ site/assets/css/css.css | 11 +------ site/content/pages/datasets/brainwash/index.md | 11 +------ site/includes/sidebar.html | 6 ++++ .../datasets/50_people_one_question/index.html | 4 +-- site/public/datasets/brainwash/index.html | 24 ++++++++++++-- site/public/datasets/celeba/index.html | 4 +-- site/public/datasets/cofw/index.html | 4 +-- site/public/datasets/duke_mtmc/index.html | 4 +-- site/public/datasets/facebook/index.html | 3 +- site/public/datasets/hrt_transgender/index.html | 4 +-- site/public/datasets/lfw/index.html | 4 +-- site/public/datasets/market_1501/index.html | 4 +-- site/public/datasets/msceleb/index.html | 4 +-- site/public/datasets/pipa/index.html | 4 +-- site/public/datasets/uccs/index.html | 4 +-- site/public/datasets/viper/index.html | 4 +-- site/public/research/index.html | 18 ++++++++-- 19 files changed, 109 insertions(+), 57 deletions(-) create mode 100644 site/includes/sidebar.html (limited to 'site/content/pages') diff --git a/megapixels/app/site/loader.py b/megapixels/app/site/loader.py index 779f68ba..701c78b2 100644 --- a/megapixels/app/site/loader.py +++ b/megapixels/app/site/loader.py @@ -5,6 +5,9 @@ import glob import app.settings.app_cfg as cfg from app.utils.file_utils import load_json +import app.utils.sheet_utils as sheet + +sidebar = sheet.fetch_google_lookup("sidebar", item_key="key") def read_metadata(fn): """ @@ -20,6 +23,12 @@ def read_metadata(fn): sections = data.split("\n\n") return parse_metadata(fn, sections) +def domainFromUrl(url): + domain = url.split('/')[2].split('.') + if len(domain) > 2 and len(domain[-2]) == 2: + return ".".join(domain[-3:]) + return ".".join(domain[-2:]) + default_metadata = { 'status': 'published', @@ -33,6 +42,18 @@ default_metadata = { 'tagline': '', } +sidebar_order = [ + { 'key': 'published', 'title': 'Published' }, + { 'key': 'images', 'title': 'Images' }, + { 'key': 'videos', 'title': 'Videos' }, + { 'key': 'identities', 'title': 'Identities' }, + { 'key': 'purpose', 'title': 'Purpose' }, + { 'key': 'created_by', 'title': 'Created by' }, + { 'key': 'funded_by_short', 'title': 'Funded by' }, + { 'key': 'size_gb', 'title': 'Download Size' }, + { 'key': 'website', 'title': 'Website' }, +] + def parse_metadata(fn, sections): """ parse the metadata headers in a markdown file @@ -87,8 +108,25 @@ def parse_metadata(fn, sections): print("Bad metadata? {}".format(dataset_path)) elif 'datasets' in fn: print("/!\\ {} does not exist!".format(dataset_path)) + + if metadata['slug'] in sidebar: + sidebar_row = sidebar[metadata['slug']] + if sidebar_row: + metadata['sidebar'] = [] + for item in sidebar_order: + key = item['key'] + value = sidebar_row[key] + if value: + value = value.replace(' - ', ' – ') + if key == 'size_gb': + value += ' GB' + if key == 'website': + value = "" + domainFromUrl(value) + "" + metadata['sidebar'].append({ 'value': value, 'title': item['title'], }) + if 'meta' not in metadata or not metadata['meta']: # dude metadata['meta'] = {} + metadata['sidebar'] = [] return metadata, valid_sections diff --git a/megapixels/app/site/parser.py b/megapixels/app/site/parser.py index 06c45f41..dc2a09f2 100644 --- a/megapixels/app/site/parser.py +++ b/megapixels/app/site/parser.py @@ -55,7 +55,7 @@ def parse_markdown(metadata, sections, s3_path, skip_h1=False): elif '### statistics' in section.lower() or '### sidebar' in section.lower(): if len(current_group): groups.append(format_section(current_group, s3_path)) - current_group = [] + current_group = [format_include("{% include 'sidebar.html' %}", metadata)] if 'sidebar' not in section.lower(): current_group.append(section) in_stats = True @@ -267,15 +267,6 @@ def format_include(section, metadata): include_fn = section.strip().strip('\n').strip().strip('{%').strip().strip('%}').strip() include_fn = include_fn.strip('include').strip().strip('"').strip().strip("'").strip() return includes_env.get_template(include_fn).render(metadata=metadata) - # include_dir = cfg.DIR_SITE_INCLUDES - # try: - # includes_env.get_template(fp_html) - # with open(join(include_dir, fp_html), 'r') as fp: - # html = fp.read().replace('\n', '') - # return html - # except Exception as e: - # print(f'Error parsing include: {e}') - # return '' def format_applet(section, s3_path): """ diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 0ee8a4f3..30663ef7 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -1,4 +1,4 @@ -da* { box-sizing: border-box; outline: 0; } +* { box-sizing: border-box; outline: 0; } html, body { margin: 0; padding: 0; @@ -278,11 +278,8 @@ p.subp{ color: #ccc; margin-bottom: 20px; font-family: 'Roboto', sans-serif; -} -.meta > div { margin-right: 20px; line-height: 17px - /*font-size:11px;*/ } .meta .gray { font-size: 9pt; @@ -316,12 +313,6 @@ p.subp{ .left-sidebar .meta, .right-sidebar .meta { flex-direction: column; } -.right-sidebar .meta > div { - margin-bottom: 10px; -} -.left-sidebar .meta > div { - margin-bottom: 15px; -} .right-sidebar ul { margin-bottom: 10px; color: #aaa; diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 6d90e78f..db88d949 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -15,16 +15,7 @@ authors: Adam Harvey ------------ ### sidebar - -+ Published: 2015 -+ Images: 11,918 -+ Faces: 91,146 -+ Created by: Stanford University (US)
      Max Planck Institute for Informatics (DE) -+ Funded by: Max Planck Center for Visual Computing and Communication -+ Purpose: Head detection -+ Download Size: 4.1GB -+ Website: stanford.edu - +### end sidebar ## Brainwash Dataset diff --git a/site/includes/sidebar.html b/site/includes/sidebar.html new file mode 100644 index 00000000..0f7d2dad --- /dev/null +++ b/site/includes/sidebar.html @@ -0,0 +1,6 @@ +{% for item in metadata.sidebar %} +
      +
      {{ item.title }}
      +
      {{ item.value }}
      +
      +{% endfor %} \ No newline at end of file diff --git a/site/public/datasets/50_people_one_question/index.html b/site/public/datasets/50_people_one_question/index.html index 540e2d0d..1b03fc7e 100644 --- a/site/public/datasets/50_people_one_question/index.html +++ b/site/public/datasets/50_people_one_question/index.html @@ -27,7 +27,8 @@
      People One Question is a dataset of people from an online video series on YouTube and Vimeo used for building facial recogntion algorithms
      People One Question dataset includes ... -
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      50 People 1 Question

      +

      {% include 'sidebar.html' %}

      +
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      50 People 1 Question

      (PAGE UNDER DEVELOPMENT)

      At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

      Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

      @@ -71,7 +72,6 @@
      -->
      -
      diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index 5e8f3a4c..c0830a96 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -27,7 +27,28 @@
      Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014
      The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms -
      Published
      2015
      Images
      11,918
      Faces
      91,146
      Created by
      Stanford University (US)
      Max Planck Institute for Informatics (DE)
      Funded by
      Max Planck Center for Visual Computing and Communication
      Purpose
      Head detection
      Download Size
      4.1GB

      Brainwash Dataset

      +
      +
      Published
      +
      2015
      +
      +
      Images
      +
      11,917
      +
      +
      Purpose
      +
      Head detection
      +
      +
      Created by
      +
      Stanford University (US), Max Planck Institute for Informatics (DE)
      +
      +
      Funded by
      +
      Max Planck Center for Visual Computing and Communication
      +
      +
      Download Size
      +
      4.1 GB
      +
      +
      Website
      + +

      Brainwash Dataset

      Brainwash is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe" 1 captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper].

      Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance 2 3.

      If you happen to have been at Brainwash cafe in San Franscisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset.

      @@ -94,7 +115,6 @@
      -
      diff --git a/site/public/datasets/celeba/index.html b/site/public/datasets/celeba/index.html index f1ee0c22..ef7a3b27 100644 --- a/site/public/datasets/celeba/index.html +++ b/site/public/datasets/celeba/index.html @@ -27,7 +27,8 @@
      CelebA is a dataset of people...
      CelebA includes... -
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      CelebA

      +

      {% include 'sidebar.html' %}

      +
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      CelebA

      (PAGE UNDER DEVELOPMENT)

      At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

      Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

      @@ -71,7 +72,6 @@
      -->
      -
      diff --git a/site/public/datasets/cofw/index.html b/site/public/datasets/cofw/index.html index 1f5aa315..3520aaa2 100644 --- a/site/public/datasets/cofw/index.html +++ b/site/public/datasets/cofw/index.html @@ -26,7 +26,8 @@
      -
      Years
      1993-1996
      Images
      14,126
      Identities
      1,199
      Origin
      Web Searches
      Funded by
      ODNI, IARPA, Microsoft

      Caltech Occluded Faces in the Wild

      +

      {% include 'sidebar.html' %}

      +
      Years
      1993-1996
      Images
      14,126
      Identities
      1,199
      Origin
      Web Searches
      Funded by
      ODNI, IARPA, Microsoft

      Caltech Occluded Faces in the Wild

      (PAGE UNDER DEVELOPMENT)

      COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion].

      RESEARCH below this line

      @@ -81,7 +82,6 @@ To increase the number of training images, and since COFW has the exact same la
      -->
      -
      diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index 83050506..c3e84053 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -27,7 +27,8 @@
      Duke MTMC is a dataset of surveillance camera footage of students on Duke University campus
      Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 HD cameras at Duke University campus in March 2014 -
      Created
      2014
      Identities
      Over 2,700
      Used for
      Face recognition, person re-identification
      Created by
      Computer Science Department, Duke University, Durham, US
      Website

      Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)

      +

      {% include 'sidebar.html' %}

      +
      Created
      2014
      Identities
      Over 2,700
      Used for
      Face recognition, person re-identification
      Created by
      Computer Science Department, Duke University, Durham, US
      Website

      Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)

      [ PAGE UNDER DEVELOPMENT ]

      Duke MTMC is a dataset of video recorded on Duke University campus during for the purpose of training, evaluating, and improving multi-target multi-camera tracking. The videos were recorded during February and March 2014 and cinclude

      Includes a total of 888.8 minutes of video (ind. verified)

      @@ -89,7 +90,6 @@
      -
      diff --git a/site/public/datasets/facebook/index.html b/site/public/datasets/facebook/index.html index 7fb1901a..e9adb3f2 100644 --- a/site/public/datasets/facebook/index.html +++ b/site/public/datasets/facebook/index.html @@ -27,7 +27,8 @@
      TBD
      TBD -
      TBD

      Statistics

      +
      TBD

      {% include 'sidebar.html' %}

      +

      Statistics

      Years
      2002-2004
      Images
      13,233
      Identities
      5,749
      Origin
      Yahoo News Images
      Funding
      (Possibly, partially CIA)

      Ignore content below these lines

      • Tool to create face datasets from Facebook https://github.com/ankitaggarwal011/FaceGrab
        • diff --git a/site/public/datasets/hrt_transgender/index.html b/site/public/datasets/hrt_transgender/index.html index 528d1c3d..3215fb5d 100644 --- a/site/public/datasets/hrt_transgender/index.html +++ b/site/public/datasets/hrt_transgender/index.html @@ -27,7 +27,8 @@
        TBD
        TBD -
        Published
        TBD
        Images
        TBD

        HRT Transgender Dataset

        +

      {% include 'sidebar.html' %}

      +
      Published
      TBD
      Images
      TBD

      HRT Transgender Dataset

      Who used HRT Transgender?

      @@ -83,7 +84,6 @@
      -->
      -
      diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 5f076fc7..562169e4 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -27,7 +27,8 @@
      Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos
      It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004 and is the most frequently used dataset in the world for benchmarking face recognition algorithms. -
      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
        +

      {% include 'sidebar.html' %}

      +
      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
      • There are about 3 men for every 1 woman in the LFW dataset 1
      • The person with the most images is George W. Bush with 530
      • There are about 3 George W. Bush's for every 1 Tony Blair
        • @@ -99,7 +100,6 @@
      -
      diff --git a/site/public/datasets/market_1501/index.html b/site/public/datasets/market_1501/index.html index 951646e3..7d9f87f6 100644 --- a/site/public/datasets/market_1501/index.html +++ b/site/public/datasets/market_1501/index.html @@ -27,7 +27,8 @@
      Market-1501 is a dataset is collection of CCTV footage from ...
      The Market-1501 dataset includes ... -
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      Market-1501 ...

      +

      {% include 'sidebar.html' %}

      +
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      Market-1501 ...

      (PAGE UNDER DEVELOPMENT)

      @@ -69,7 +70,6 @@
      -->
      -
      diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html index 9a671c8e..ecab4c3a 100644 --- a/site/public/datasets/msceleb/index.html +++ b/site/public/datasets/msceleb/index.html @@ -27,7 +27,8 @@
      MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms
      The MS Celeb dataset includes over 10,000,000 images and 93,000 identities of semi-public figures collected using the Bing search engine -
      Published
      TBD
      Images
      TBD
      Faces
      TBD
      Created by
      TBD

      Microsoft Celeb Dataset (MS Celeb)

      +

      {% include 'sidebar.html' %}

      +
      Published
      TBD
      Images
      TBD
      Faces
      TBD
      Created by
      TBD

      Microsoft Celeb Dataset (MS Celeb)

      (PAGE UNDER DEVELOPMENT)

      At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

      Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

      @@ -87,7 +88,6 @@ -->

      Add more analysis here

      -
      diff --git a/site/public/datasets/pipa/index.html b/site/public/datasets/pipa/index.html index fe6a4742..ff4302eb 100644 --- a/site/public/datasets/pipa/index.html +++ b/site/public/datasets/pipa/index.html @@ -27,7 +27,8 @@
      is a dataset...
      PIPA subdescription -
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      Dataset Title TBD

      +

      {% include 'sidebar.html' %}

      +
      Collected
      TBD
      Published
      TBD
      Images
      TBD
      Faces
      TBD

      Dataset Title TBD

      (PAGE UNDER DEVELOPMENT)

      @@ -69,7 +70,6 @@
      -->
      -
      diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 10b7603e..0925763b 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -27,7 +27,8 @@
      Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos of students taken without their knowledge
      The UCCS dataset includes 16,149 images and 1,732 identities of students at University of Colorado Colorado Springs campus and is used for face recognition and face detection -
      Published
      2018
      Images
      16,149
      Identities
      1,732
      Used for
      Face recognition, face detection
      Created by
      Unviversity of Colorado Colorado Springs (US)
      Funded by
      ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR

      Unconstrained College Students ...

      +

      {% include 'sidebar.html' %}

      +
      Published
      2018
      Images
      16,149
      Identities
      1,732
      Used for
      Face recognition, face detection
      Created by
      Unviversity of Colorado Colorado Springs (US)
      Funded by
      ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR

      Unconstrained College Students ...

      (PAGE UNDER DEVELOPMENT)

      The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey
      The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey
      @@ -84,7 +85,6 @@
      -
      diff --git a/site/public/datasets/viper/index.html b/site/public/datasets/viper/index.html index cc4272c8..b838c2b9 100644 --- a/site/public/datasets/viper/index.html +++ b/site/public/datasets/viper/index.html @@ -27,7 +27,8 @@
      VIPeR is a person re-identification dataset of images captured at UC Santa Cruz in 2007
      VIPeR contains 1,264 images and 632 persons on the UC Santa Cruz campus and is used to train person re-identification algorithms for surveillance -
      Published
      2007
      Images
      1,264
      Persons
      632
      Created by
      UC Santa Cruz

      VIPeR Dataset

      +

      {% include 'sidebar.html' %}

      +
      Published
      2007
      Images
      1,264
      Persons
      632
      Created by
      UC Santa Cruz

      VIPeR Dataset

      (PAGE UNDER DEVELOPMENT)

      VIPeR (Viewpoint Invariant Pedestrian Recognition) is a dataset of pedestrian images captured at University of California Santa Cruz in 2007. Accoriding to the reserachers 2 "cameras were placed in different locations in an academic setting and subjects were notified of the presence of cameras, but were not coached or instructed in any way."

      VIPeR is amongst the most widely used publicly available person re-identification datasets. In 2017 the VIPeR dataset was combined into a larger person re-identification created by the Chinese University of Hong Kong called PETA (PEdesTrian Attribute).

      @@ -86,7 +87,6 @@
      -->
      -
      diff --git a/site/public/research/index.html b/site/public/research/index.html index 303732f8..0ef57043 100644 --- a/site/public/research/index.html +++ b/site/public/research/index.html @@ -26,8 +26,22 @@
      -

      Research Blog

      -
      +
      +

      Research

      +
      +
      +
      Posted
      +
      2018-12-15
      +
      +
      +
      By
      +
      Adam Harvey
      +
      + +
      +
      + +
      -- cgit v1.2.3-70-g09d2