Docs audit [April 2026]: update multi-animal guide#3335
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@C-Achard, maybe it is ready for a first round of review. Changes: In summary the docs now look like this:
I think the multi-animal tracking docs still need quite some (formatting and correction) work, but the merged user guide is getting there. Since all multi-animal-specific info is tagged in dedicated admonitions/dropdowns, we can easily go back to the old situation, in case we prefer to have two separate (largely duplicated) doc pages. |
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@deruyter92 I had a few issues in the user_guide file, the frontmatter metadata was a bit malformed, and the dropdowns did not render correctly. Is it okay if I push a fixed version? |
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Replace markdown-style links with Sphinx {ref} cross-reference roles in docs/UseOverviewGuide.md and docs/maDLC_UserGuide.md to ensure proper Sphinx rendering. Also fix a malformed bracket/URL in docs/pytorch/architectures.md for the Ye et al. citation link.
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@C-Achard thanks for the review!
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@deruyter92 This is suffering from the outdated squashed commits mismatch as well, happy to fix it if needed! |
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Cutoff should be ba8e985^ |
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I'm not working on it a the moment, so feel free to rebase as you wish! Thanks for taking care of it! |
…aders accordingly
* Update custom.css * Refine workflow dropdown styles and colors Update docs/_static/custom.css to adjust dark-theme variables and overhaul workflow dropdown styling. Changed single/multi-animal background variables, replaced old title-prefix approach with CSS-generated emoji titles, and hid sphinx-design's no-title icon. Apply consistent header/body color variables for sd-card dropdowns, keep text/chevron colors stable, and disable pydata's hover darken/lighten effect to prevent color shifts on focus/hover. These changes ensure consistent appearance and correct application of border/background styles overridden by pydata.
…ng details to separate doc.
Update documentation to use MyST's :class-container for dropdown directives (previous :class usages updated in docs/_static/custom.css and docs/main-workflows/user-guide.md). Also correct the YAML frontmatter formatting in user-guide.md (expand inline metadata into a proper YAML block). These changes align docs with current MyST/Sphinx directive syntax and fix frontmatter parsing.
Adjust multi-animal CSS variables in light and dark themes to be more distinct from hint/tip boxes. Updated --multi-animal-border to #57c4be, --multi-animal-bg to #e8f8f7, --multi-animal-title-bg to #21a197, and --multi-animal-title-text to #000000 in both themes.
Editorial and formatting updates to the main user guide and added an updated multi-animal figure. Changes include: clarified multi-animal workflow wording, strengthened guidance (emphasis on recommended options), reworked admonitions (hint/danger/tip), improved paragraph flow and bullet structure, clarified frame selection methods and recommendations, updated examples and GUI notes, refined training/evaluation/tracking explanations, and replaced the multi-animal figure reference with docs/images/box1-multi-rec.png (recolored for new CSS). Miscellaneous typography and markup fixes (code blocks, YAML/file references, and symbol styling) to improve readability.
Improve rendering and correctness in docs/main-workflows/user-guide.md: change admonition key to `class-container`, update dropdown/admonition syntax, fix code block languages (python -> yaml/text), correct example function parameter (`config` -> `config_path`), adjust heading capitalization and list formatting. These changes ensure examples render correctly and the docs reflect the actual API usage.
Add single- and multi-animal quick-start pages to the Main workflows overview in _toc.yml and substantially rewrite both quick-start docs. single_animal_quick_guide.md was reorganized into a clear step-by-step workflow (create project, configure, extract/label frames, create dataset, train/evaluate, analyze/filter/plot/create videos) with concrete Python examples, notes, and tips (use absolute paths, no spaces in body-part names). tutorial_maDLC.md was refactored into a multi-animal overview with GUI and Python workflows, clearer config guidance for multi-animal fields, extraction/annotation/checking steps, separate training engine examples (PyTorch/TensorFlow), and explicit tracking steps (analyze, convert detections, stitch tracklets, create labeled videos) plus helpful notes. Overall improvements focus on clarity, concrete examples, and actionable tips for users.
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Relocate the important guidance about selecting diverse training frames to the section near frame extraction/functionality, making it more contextually relevant. Clean up manual frame-selection wording, normalize the selection-method bullets, and adjust figure/code-fence markup (wrap figure in a comment) to prevent rendering issues. Minor formatting fixes for clarity.
Remove the parenthetical reference to www.deeplabcut.org and merge the broken sentence in the TensorFlow Engine augmentation section to improve readability and flow. No functional changes; content about available loaders remains the same.
…-audit-2026-update-ma-guide

in line with the main single animal guide, this PR updates the formatting of the multi-animal guide