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Facial Recognition in Historical Photographs with Artificial Intelligence in Python #552

Closed giuliataurino closed 2 months ago

giuliataurino commented 1 year ago

The Programming Historian has received the following tutorial on 'Facial Recognition in Historical Photographs with Artificial Intelligence in Python' by @c-goldberg. This lesson is now under review and can be read at:

http://programminghistorian.github.io/ph-submissions/en/drafts/originals/facial-recognition-ai-python

Please feel free to use the line numbers provided on the preview if that helps with anchoring your comments, although you can structure your review as you see fit.

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charlottejmc commented 3 months ago

Hello @c-goldberg,

I thought I would provide some extra guidance on the alt-text, if you feel it is helpful.

We have found Amy Cesal's guide to Writing Alt Text for Data Visualization useful. This guide advises that alt-text for graphs and data visualisations should consist of the following:

alt="[Chart type] of [data type] where [reason for including chart]"

What Amy Cesal's guide achieves is prompting an author to reflect on their reasons for including the graph or visualisation. What idea does this support? What can a reader learn or understand from this visual?

The Graphs section of Diagram Center's guidance is also useful. Some key points (relevant to all graph types) we can take away from it are:

For general images, Harvard's guidance notes some helpful principles. A key point is to keep descriptions simple, and adapt them to the context and purpose for which the image is being included.

Would you feel comfortable making a first draft of the alt-text for each of the figures? This is certainly a bit time-consuming, but we believe it is very worthwhile in terms of making your lesson accessible to the broadest possible audience. We would be very grateful for your support with this.

Thank you!

anisa-hawes commented 3 months ago

Hello @hawc2,

This lesson's sustainability + accessibility checks are now complete. It is ready for your final read-through ahead of publication.

- name: Charles Goldberg
  team: false
  bio:
    en: |
      Charles Goldberg is an Associate Professor of History in the Department of History, Philosophy, and Political Science at Bethel University in Saint Paul, Minnesota, USA. 
- name: Zach Haala
  team: false
  bio:
    en: |
      Zach Haala graduated with a bachelor’s degree in Software Engineering and Digital Humanities from Bethel University in 2023. He is a Business Systems Analyst at Optum.

Promotion:

hawc2 commented 3 months ago

This looks great @anisa-hawes!

One minor thought for revision is to add a few more links for key technical terms and tools. For instance, there is a link for Deepface, but it doesn't get linked the first time the Python package is cited early in the lesson. Other complex terms like Convolutional Neural Networks (CNN) would also merit a wikipedia citation or another reference. Especially considering this is designed to be an introductory lesson, even things like Microsoft Visual Studio Code and Google Colab should receive external link citations, if not to their wikipedia pages, then to their product website pages.

Other than adding additional links during preparation for publication, I think this lesson is ready to go, and I'll draft the social media posts shortly.

Congrats @c-goldberg!

charlottejmc commented 3 months ago

Hi @hawc2, here are the links I've added now (perma.cc in the text):

I've chosen not to add a wikipedia link for terms that are defined by the authors within the lesson itself ('thresholding', 'semantic gap'...) but I can always add these in if you feel it is needed.

@c-goldberg and Zach, as well as linking to packages/products/software documentation, I have also added some Wikipedia links (as we do regularly in all our lessons) to provide readers with quick access to definitions of terms and concepts that are mentioned. We treat Wikipedia as an accessible dictionary rather than as sources/references, so we don't add these links to your bibliography. They are usually available in all of our languages too, which makes it a sustainable resource across our translations. However, if you'd like to suggest alternative links instead, please do let me know.

c-goldberg commented 3 months ago

This looks good to me.

On Fri, May 31, 2024 at 3:49 AM charlottejmc @.***> wrote:

Hi @hawc2 https://github.com/hawc2, here are the links I've added now (perma.cc in the text):

I've chosen not to add a wikipedia link for terms that are defined by the authors within the lesson itself ('thresholding', 'semantic gap'...) but I can always add these in if you feel it is needed.

@c-goldberg https://github.com/c-goldberg and Zach, as well as linking to packages/products/software documentation, I have also added some Wikipedia links (as we do regularly in all our lessons) to provide readers with quick access to definitions of terms and concepts that are mentioned. We treat Wikipedia as an accessible dictionary rather than as sources/references, so we don't add these links to your bibliography. They are usually available in all of our languages too, which makes it a sustainable resource across our translations. However, if you'd like to suggest alternative links instead, please do let me know.

— Reply to this email directly, view it on GitHub https://github.com/programminghistorian/ph-submissions/issues/552#issuecomment-2141524186, or unsubscribe https://github.com/notifications/unsubscribe-auth/AJQTHPSJBNCHBELWITCZTC3ZFA2QFAVCNFSM6AAAAAAVUEY2GWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCNBRGUZDIMJYGY . You are receiving this because you were mentioned.Message ID: @.***>

-- Charlie Goldberg Associate Professor of History Department of History, Philosophy, and Political Science Bethel University 3900 Bethel Drive Saint Paul, Minnesota 55112

anisa-hawes commented 3 months ago

Super! Many thanks to you all!

I'll stage this for publication next week 🎉

anisa-hawes commented 2 months ago

Facial Recognition in Historical Photographs with Artificial Intelligence in Python is published!

Congratulations @c-goldberg + Zach ! Thank you all for your contributions

Our suggested citation for this lesson is:

Charles Goldberg and Zach Haala, "Facial Recognition in Historical Photographs with Artificial Intelligence in Python," Programming Historian 13 (2024), https://doi.org/10.46430/phen0119.

We appreciate your help to circulate our social media announcements about this lesson among your networks: Twitter/X: https://x.com/ProgHist/status/1806008010658943055 Mastodon: https://hcommons.social/@proghist/112683859690952281

Sincere thanks.