Scheduled weekly dependency update for week 52 #572

pyup-bot · 2024-12-30T14:53:10Z

Update sphinx from 7.3.7 to 8.1.3.

Changelog

8.1.3

==============================

Bugs fixed
----------

* 13013: Restore support for :func:`!cut_lines` with no object type.
Patch by Adam Turner.

8.1.2

=====================================

Bugs fixed
----------

* 13012: Expose :exc:`sphinx.errors.ExtensionError` in ``sphinx.util``
for backwards compatibility.
This will be removed in Sphinx 9, as exposing the exception
in ``sphinx.util`` was never intentional.
:exc:`!ExtensionError` has been part of ``sphinx.errors`` since Sphinx 0.9.
Patch by Adam Turner.

8.1.1

=====================================

Bugs fixed
----------

* 13006: Use the preferred https://www.cve.org/ URL for
the :rst:role:`:cve: &lt;cve&gt;` role.
Patch by Hugo van Kemenade.
* 13007: LaTeX: Improve resiliency when the required
``fontawesome`` or ``fontawesome5`` packages are not installed.
Patch by Jean-François B.

8.1.0

=====================================

Dependencies
------------

* 12756: Add lower-bounds to the ``sphinxcontrib-*`` dependencies.
Patch by Adam Turner.
* 12833: Update the LaTeX ``parskip`` package from 2001 to 2018.
Patch by Jean-François B.

Incompatible changes
--------------------

* 12763: Remove unused internal class ``sphinx.util.Tee``.
Patch by Adam Turner.
* 12822: LaTeX: for Unicode engines, the :ref:`fvset` default is changed to
``&#x27;\\fvset{fontsize=auto}&#x27;`` from ``&#x27;\\fvset{fontsize=\\small}&#x27;``.
Code-blocks are unchanged as FreeMono is now loaded with ``Scale=0.9``.
An adjustment to existing projects is needed only if they used a custom
:ref:`fontpkg` configuration and did not set :ref:`fvset`.
Patch by Jean-François B.
* 12875: Disable smartquotes for languages: ``zh_CN`` and ``zh_TW`` by default.
Patch by A. Rafey Khan.

Deprecated
----------

* 12762: Deprecate ``sphinx.util.import_object``.
Use :py:func:`importlib.import_module` instead.
Patch by Adam Turner.
* 12766: Deprecate ``sphinx.util.FilenameUniqDict``
and ``sphinx.util.DownloadFiles``.
Patch by Adam Turner.

Features added
--------------

* 11328: Mention evaluation of templated content during production of static
output files.
Patch by James Addison.
* 12704: LaTeX: make :dudir:`contents &lt;table-of-contents&gt;`, :dudir:`topic`,
and :dudir:`sidebar` directives separately customizable for PDF output.
Patch by Jean-François B. and Bénédikt Tran.
* 12474: Support type-dependent search result highlighting via CSS.
Patch by Tim Hoffmann.
* 12652: LaTeX: Add :confval:`math_numsep` support to latex builder.
Patch by Thomas Fanning and Jean-François B.
* 12743: No longer exit on the first warning when
:option:`--fail-on-warning &lt;sphinx-build --fail-on-warning&gt;` is used.
Instead, exit with a non-zero status if any warnings were generated
during the build.
Patch by Adam Turner.
* 12743: Add :option:`sphinx-build --exception-on-warning`,
to raise an exception when warnings are emitted during the build.
Patch by Adam Turner and Jeremy Maitin-Shepard.
* 12907: Add :confval:`html_last_updated_use_utc` to allow using
universal time (GMT/UTC) instead of local time for the date-time
supplied to :confval:`html_last_updated_fmt`.
Patch by Adam Turner.
* 12910: Copyright entries now support the ``&#x27;%Y&#x27;`` placeholder
to substitute the current year.
This is helpful for reducing the reliance on Python modules
such as :py:mod:`time` or :py:mod:`datetime` in :file:`conf.py`.
See :ref:`the docs &lt;config-copyright&gt;` for further detail.
Patch by Adam Turner.
* 11781: Add roles for referencing CVEs (:rst:role:`:cve: &lt;cve&gt;`)
and CWEs (:rst:role:`:cwe: &lt;cwe&gt;`).
Patch by Hugo van Kemenade.
* 11809: Improve the formatting for RFC section anchors.
Patch by Jakub Stasiak and Adam Turner.
* 12852: Support a :attr:`.Builder.supported_linkcode` attribute
for builders to enable use of :mod:`sphinx.ext.linkcode`-generated
references.
Patch by James Knight.
* 12949: Print configuration options that differ from the pickled environment.
This can be helpful in diagnosing the cause of a full rebuild.
Patch by Adam Turner.

Bugs fixed
----------

* 12514: intersphinx: fix the meaning of a negative value for
:confval:`intersphinx_cache_limit`.
Patch by Shengyu Zhang.
* 12722: LaTeX: avoid TeX reporting ``Overfull \hbox`` from too long
strings in a codeline when the problem has actually been solved thanks
to :ref:`latexsphinxsetupforcewraps`.
Patch by Jean-François B.
* 12730: The ``UnreferencedFootnotesDetector`` transform has been improved
to more consistently detect unreferenced footnotes.
Note, the priority of the transform has been changed from 200 to 622,
so that it now runs after the docutils ``Footnotes`` resolution transform.
Patch by Chris Sewell.
* 12778: LaTeX: let :ref:`&#x27;sphinxsetup&#x27; &lt;latexsphinxsetup&gt;`
``div.topic_box-shadow`` key if used with only one dimension set both
x-offset and y-offset as per documentation.
Patch by Jean-François B.
* 12587: Do not warn when potential ambiguity detected during Intersphinx
resolution occurs due to duplicate targets that differ case-insensitively.
Patch by James Addison.
* 12639: Fix singular and plural search results text.
Patch by Hugo van Kemenade.
* 12645: Correctly support custom gettext output templates.
Patch by Jeremy Bowman.
* 12717: LaTeX: let :option:`-q &lt;sphinx-build -q&gt;` (quiet) option for
:program:`sphinx-build -M latexpdf` or :program:`make latexpdf` (``O=-q``)
get passed to :program:`latexmk`.  Let :option:`-Q &lt;sphinx-build -Q&gt;`
(silent) apply as well to the PDF build phase.
Patch by Jean-François B.
* 12744: LaTeX: Classes injected by a custom interpreted text role now give
rise to nested ``\DUrole``&#x27;s, rather than a single one with comma separated
classes.
Patch by Jean-François B.
* 12831: LaTeX: avoid large voids sometimes occurring at page bottoms.
Patch by Jean-François B.
* 11970, 12551: singlehtml builder: make target URIs to be same-document
references in the sense of :rfc:`RFC 3986, §4.4 &lt;3986section-4.4&gt;`,
e.g., ``index.htmlfoo`` becomes ``foo``.
(note: continuation of a partial fix added in Sphinx 7.3.0)
Patch by James Addison (with reference to prior work by Eric Norige).
* 12735: Fix :pep:`695` generic classes LaTeX output formatting.
Patch by Jean-François B. and Bénédikt Tran.
* 12782: intersphinx: fix double forward slashes when generating the inventory
file URL (user-defined base URL of an intersphinx project are left untouched
even if they end with double forward slashes).
Patch by Bénédikt Tran.
* 12796: Enable parallel reading if requested,
even if there are fewer than 6 documents.
Patch by Matthias Geier.
* 12844: Restore support for ``:noindex:`` for the :rst:dir:`js:module`
and :rst:dir:`py:module` directives.
Patch by Stephen Finucane.
* 12916: Restore support for custom templates named with the legacy ``_t``
suffix during ``apidoc`` RST rendering (regression in 7.4.0).
Patch by James Addison.
* 12451: Only substitute copyright notice years with values from
``SOURCE_DATE_EPOCH`` for entries that match the current system clock year,
and disallow substitution of future years.
Patch by James Addison and Adam Turner.
* 12905: intersphinx: fix flipped use of :confval:`intersphinx_cache_limit`,
which always kept the cache for positive values, and always refreshed it for
negative ones.
Patch by Nico Madysa.
* 12888: Add a warning when document is included in multiple toctrees
and ensure deterministic resolution of global toctree in parallel builds
by choosing the lexicographically greatest parent document.
Patch by A. Rafey Khan
* 12995: Significantly improve performance when building the search index
for Chinese languages.
Patch by Adam Turner.
* 12767: :py:meth:`.Builder.write` is typed as ``final``, meaning that the
:event:`write-started` event may be relied upon by extensions.
A new :py:meth:`.Builder.write_documents` method has been added to
control how documents are written.
This is intended for builders that do not output a file for each document.
Patch by Adam Turner.


Testing
-------

* 12141: Migrate from the deprecated ``karma`` JavaScript test framework to
the actively-maintained ``jasmine`` framework.  Test coverage is unaffected.
Patch by James Addison.

Links

PyPI: https://pypi.org/project/sphinx
Changelog: https://data.safetycli.com/changelogs/sphinx/

Update furo from 2024.5.6 to 2024.8.6.

Changelog

2024.08.06

- ✨ Add support for Sphinx 8
- ✨ Add smoother transitions between breakpoints
- Increase specificity of table-wrapper selector
- Avoid page breaks inside paragraphs

2024.07.18

- Improve how icons are handled and aligned.
- Improve scroll event handler.
- Hide the copybutton by default.
- Fix `source_view_link` configuration handling.
- Fix close tag on pencil icon.

Links

PyPI: https://pypi.org/project/furo
Changelog: https://data.safetycli.com/changelogs/furo/

Update sphinx-autobuild from 2024.4.16 to 2024.10.3.

Changelog

2024.10.03

-----------------------

* Improve error handling for failures in pre-build commands.

2024.10.02

-----------------------

* Show the changed paths that triggered the rebuild.

2024.09.19

-----------------------

* Fix path filtering on Windows by normalising path separators.
* Filter various directories by default (``.git``, ``venv``, etc).
* Serve the correct directory when using make mode (``-M``).

2024.09.18

-----------------------

* Run Sphinx through the Python entry point rather than the binary on PATH.

2024.09.17

-----------------------

* Relax checks for paths that aren&#x27;t required to exist.

2024.09.03

-----------------------

* Fix support for Python 3.9.
* Fix running ``sphinx-autobuild`` via entry point scripts.
* Run ``sphinx-build`` in a subprocess to mitigate autdoc issues.
* Support the ``-M`` &#x27;make mode&#x27; option for ``sphinx-build``.

Links

PyPI: https://pypi.org/project/sphinx-autobuild
Changelog: https://data.safetycli.com/changelogs/sphinx-autobuild/

Update sphinx-click from 5.0.1 to 6.0.0.

The bot wasn't able to find a changelog for this release. Got an idea?

Links

PyPI: https://pypi.org/project/sphinx-click
Changelog: https://data.safetycli.com/changelogs/sphinx-click/
Repo: https://github.com/click-contrib/sphinx-click

Update setuptools from 70.0.0 to 75.6.0.

The bot wasn't able to find a changelog for this release. Got an idea?

Links

PyPI: https://pypi.org/project/setuptools

Update pytest from 8.2.1 to 8.3.4.

The bot wasn't able to find a changelog for this release. Got an idea?

Links

PyPI: https://pypi.org/project/pytest

Update respx from 0.21.1 to 0.22.0.

Changelog

0.22.0

Fixed

- Support HTTPX 0.28.0, thanks ndhansen (278)

Removed

- Drop support for Python 3.7, to align with HTTPX 0.25.0 (280)

CI

- Update CI test to not fail fast and cancel workflows, thanks flaeppe (269)
- Add dependabot to check GitHub actions packages, thanks flaeppe (268)
- Add Python 3.13 to test suite, thanks jairhenrique (283)

Links

PyPI: https://pypi.org/project/respx
Changelog: https://data.safetycli.com/changelogs/respx/
Repo: https://lundberg.github.io/respx/

Update pytest-env from 1.1.3 to 1.1.5.

Changelog

1.1.5

&lt;!-- Release notes generated using configuration in .github/release.yml at main --&gt;

What&#x27;s Changed
* Improve the CI by gaborbernat in https://github.com/pytest-dev/pytest-env/pull/101


**Full Changelog**: https://github.com/pytest-dev/pytest-env/compare/1.1.4...1.1.5

1.1.4

&lt;!-- Release notes generated using configuration in .github/release.yml at main --&gt;



**Full Changelog**: https://github.com/pytest-dev/pytest-env/compare/1.1.3...1.1.4

Links

PyPI: https://pypi.org/project/pytest-env
Changelog: https://data.safetycli.com/changelogs/pytest-env/

Update fiftyone from 0.23.8 to 1.2.0.

Changelog

1.1.0

Please see the official Voxel51 [Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-1-1-0) for details!

1.0.2

Please see the official [Voxel51 Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-1-0-2) for details!

1.0.1

Please see the official [Voxel51 Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-1-0-1) for details!

1.0.0

Please see the official Voxel51 [Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-1-0-0)

0.25.2

Please see the official Voxel51 [Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-0-25-2)

0.25.1

Please see the official Voxel51 [Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-0-25-1)

0.25.0

Please see the official Voxel51 [Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-0-25-0)

0.24.1

Please see the official [Voxel51 Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-0-24-1) for details.

0.24.0

Please see the official [Voxel51 Release Notes](https://docs.voxel51.com/release-notes.html#fiftyone-0-24-0) for details.

Links

PyPI: https://pypi.org/project/fiftyone
Changelog: https://data.safetycli.com/changelogs/fiftyone/
Repo: https://github.com/voxel51/fiftyone

Update datasets from 2.19.1 to 3.2.0.

Changelog

3.2.0

Added

-   [API] `tfds.ImageFolder` and `tfds.TranslateFolder` to easily create custom
 datasets with your custom data.
-   [API] `tfds.ReadConfig(input_context=)` to shard dataset, for better
 multi-worker compatibility (1426).
-   [API] The default `data_dir` can be controlled by the `TFDS_DATA_DIR`
 environment variable.
-   [API] Better usability when developing datasets outside TFDS: downloads are
 always cached, checksums are optional.
-   Scripts to help deployment/documentation (Generate catalog documentation,
 export all metadata files, ...).
-   [Documentation] Catalog display images
 ([example](https://www.tensorflow.org/datasets/catalog/sun397#sun397standard-part2-120k)).
-   [Documentation] Catalog shows which dataset have been recently added and are
 only available in `tfds-nightly`
 &lt;span class=&quot;material-icons&quot;&gt;nights_stay&lt;/span&gt;.
-   [API] `tfds.show_statistics(ds_info)` to display
 [FACETS OVERVIEW](https://pair-code.github.io/facets/). Note: This require
 the dataset to have been generated with the statistics.

Deprecated

-   `tfds.features.text` encoding API. Please use
 [tensorflow_text](https://www.tensorflow.org/tutorials/tensorflow_text/intro)
 instead.

Removed

-   `tfds.load(&#x27;image_label_folder&#x27;)` in favor of the more user-friendly
 `tfds.ImageFolder`.

Fixed

-   Fix deterministic example order on Windows when path was used as key (this
 only impacts a few datasets). Now example order should be the same on all
 platforms.
-   Misc performances improvements for both generation and reading (e.g. use
 `__slot__`, fix parallelisation bug in `tf.data.TFRecordReader`, ...).
-   Misc fixes (typo, types annotations, better error messages, fixing dead
 links, better windows compatibility, ...).

3.1.0

Added

-   [API] `tfds.builder_cls(name)` to access a DatasetBuilder class by name
-   [API] `info.split[&#x27;train&#x27;].filenames` for access to the tf-record files.
-   [API] `tfds.core.add_data_dir` to register an additional data dir.
-   [Testing] Support for custom decoders in `tfds.testing.mock_data`.
-   [Documentation] Shows which datasets are only present in `tfds-nightly`.
-   [Documentation] Display images for supported datasets.

Changed

-   Rename `tfds.core.NamedSplit`, `tfds.core.SplitBase` -&gt; `tfds.Split`. Now
 `tfds.Split.TRAIN`,... are instance of `tfds.Split`.
-   Rename `interleave_parallel_reads` -&gt; `interleave_cycle_length` for
 `tfds.ReadConfig`.
-   Invert ds, ds_info argument orders for `tfds.show_examples`.

Deprecated

-   `tfds.features.text` encoding API. Please use `tensorflow_text` instead.

Removed

-   `num_shards` argument from `tfds.core.SplitGenerator`. This argument was
 ignored as shards are automatically computed.
-   Most `ds.with_options` which where applied by TFDS. Now use `tf.data`
 default.

Fixed

-   Better error messages.
-   Windows compatibility.

3.0.0

Added

-   `DownloadManager` is now pickable (can be used inside Beam pipelines).
-   `tfds.features.Audio`:
 -   Support float as returned value.
 -   Expose sample_rate through `info.features[&#x27;audio&#x27;].sample_rate`.
 -   Support for encoding audio features from file objects.
-   More datasets.

Changed

-   New `image_classification` section. Some datasets have been move there from
 `images`.
-   `DownloadConfig` does not append the dataset name anymore (manual data
 should be in `&lt;manual_dir&gt;/` instead of `&lt;manual_dir&gt;/&lt;dataset_name&gt;/`).
-   Tests now check that all `dl_manager.download` urls has registered
 checksums. To opt-out, add `SKIP_CHECKSUMS = True` to your
 `DatasetBuilderTestCase`.
-   `tfds.load` now always returns `tf.compat.v2.Dataset`. If you&#x27;re using still
 using `tf.compat.v1`:
 -   Use `tf.compat.v1.data.make_one_shot_iterator(ds)` rather than
     `ds.make_one_shot_iterator()`.
 -   Use `isinstance(ds, tf.compat.v2.Dataset)` instead of `isinstance(ds,
     tf.data.Dataset)`.

Deprecated

-   The `tfds.features.text` encoding API is deprecated. Please use
 [tensorflow_text](https://www.tensorflow.org/tutorials/tensorflow_text/intro)
 instead.
-   `num_shards` argument of `tfds.core.SplitGenerator` is currently ignored and
 will be removed in the next version.

Removed

-   Legacy mode `tfds.experiment.S3` has been removed
-   `in_memory` argument has been removed from `as_dataset`/`tfds.load` (small
 datasets are now auto-cached).
-   `tfds.Split.ALL`.

Fixed

-   Various bugs, better error messages, documentation improvements.

Links

PyPI: https://pypi.org/project/datasets
Changelog: https://data.safetycli.com/changelogs/datasets/
Repo: https://github.com/huggingface/datasets/tags

Update ultralytics from 8.3.47 to 8.3.55.

Changelog

8.3.55

🌟 Summary  
The **v8.3.55** release of Ultralytics YOLO introduces a new dataset, **Medical Pills Detection Dataset**, aimed at advancing AI applications in pharmaceutical automation, alongside several feature enhancements, bug fixes, and documentation improvements. 💊💻✨

---

📊 Key Changes  
- **New Dataset Added**: Medical Pills with 92 training and 23 validation images. 🩺  
- **Enhanced `auto_annotate` Documentation**: Centralized details of YOLO-SAM integration for creating segmentation datasets. 📖  
- **Fixed ConfusionMatrix**: Corrected FP calculation logic for unmatched predictions. 🛠️  
- **User-Friendly Updates**: Improved workflow cloning speeds and UI components for solutions workflows. 🚀  
- **Code Quality Upgrades**: Type hinting for better flexibility, Python 3.12 support tweaks, and bug fixes. ⚙️  

---

🎯 Purpose &amp; Impact  
- **Purpose**:  
- Enable automation in pharmaceutical workflows, e.g., pill quality control and sorting.  
- Provide clearer usage examples for dataset annotation via YOLO-SAM tools.  
- Refine existing tools with a developer-friendly codebase.  

- **Impact**:  
- **Improved AI Training**: Medical innovators can train models for specific industries using the new dataset.  
- **Documentation Clarity**: Ease of adoption for advanced features like hybrid YOLO-SAM workflows.  
- **Bug Fixes**: These ensure more accurate predictions (e.g., ConfusionMatrix FP fix) and reduce user-errors in workflows.  
- **Streamlined DevOps**: Faster docs deployment and CI pipelines benefit larger teams.  

🚀 This release is a forward leap for developers and researchers aiming to innovate in specialized fields like healthcare!

What&#x27;s Changed
* Use `Any` type-hints for `args` and `kwargs` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18372
* Update FAQ examples in callbacks.md by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18377
* Add MobileSAM auto annotation feature 🚀 by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18374
* Fix Docs calls to `model.benchmark()` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18391
* PyCharm Code Inspect fixes by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18392
* Remove docs.yml fetch-depth 0 by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18394
* Clone Docs `gh-pages` branch `--depth 1` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18396
* Update image count information for COCO-Pose by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18395
* PyCharm Code Inspect fixes for Solutions and Examples by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18393
* Simplify links.yml by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18399
* Code scan fixes by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18398
* Restrict ONNX ExecutionProviders by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18400
* Update yolo11n-pose to yolo11n in `speed-estimation.md` by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18410
* fix bug in the ConfusionMatrix class by yuzhj in https://github.com/ultralytics/ultralytics/pull/18409
* `ultralytics 8.3.55` New Medical-pills dataset by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18389

New Contributors
* yuzhj made their first contribution in https://github.com/ultralytics/ultralytics/pull/18409

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.54...v8.3.55

8.3.54

🌟 Summary
Ultralytics `v8.3.54` delivers a significant overhaul in the **Streamlit-based real-time inference solution**, making it easier for users to perform live predictions with a better interface. It also introduces enhancements around exporting flexibility for OpenVINO models, updates to documentation for YOLO11 use, and streamlines development and compatibility workflows.

---

📊 Key Changes
- **🚀 Revamped Streamlit Inference Tool**: Streamlit apps now feature an all-new `Inference` class.
- Sidebar for quick video source, model selection, and settings like confidence thresholds.
- Support for webcam and video uploads for real-time predictions and visualizations.
- Enhanced interactivity with class selection, live FPS monitoring, and tracking features.
- **📦 OpenVINO Export Enhancements**:
- Added support for `dynamic` shapes, expanding deployment flexibility.
- Unified argument ordering (`batch`, `dynamic`, etc.) across multiple export formats.
- **📖 YOLO11 Documentation Updates**: Updated guides to reflect the latest **YOLO11** usage in region counting.
- **🐍 Python Workflow Updates**: Minimum Python version for CI workflows updated to 3.9 for compatibility alignment.
- **🌐 ONNXRuntime Example for RTDETR**:
- Added an example for deploying RTDETR models with ONNXRuntime in Python.
- **⚙️ Dependency Updates**: Updated GitHub Actions `setup-uv` workflow to v5 to improve caching and build processes.

---

🎯 Purpose &amp; Impact
- **Better User Experience with Streamlit**:
- Easier navigation and configuration for real-time inference tasks. 🖥️
- Developers and beginners alike can now perform live inference with minimal setup.
- **Deployment Flexibility**: Support for `dynamic` OpenVINO exports ensures models work smoothly across various scenarios and hardware configurations. 🧩
- **Clearer Documentation**: The shift to YOLO11 references builds clarity and trust for users working with region-based object counting. 📘
- **Future-Proofing Development**:
- Updating Python versions ensures long-term ecosystem compatibility. 🔧
- **ONNXRuntime Examples**: Simplifies adopting RTDETR models for developers using ONNXRuntime in Python, with clear setup and usage guidance. 🚀
- **Faster CI/CD Pipelines**: Updated dependencies in GitHub workflows boost speed and efficiency. ⚡

This release is ideal for users looking for a blend of usability in inference workflows and robustness in model deployment workflows! 🌟

What&#x27;s Changed
* Add `dynamic` to approved OpenVINO export args by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18353
* Bump astral-sh/setup-uv from 4 to 5 in /.github/workflows by dependabot[bot] in https://github.com/ultralytics/ultralytics/pull/18358
* Update `YOLOv8` to `YOLO11` in `region-counting.md` by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18360
* Min CI Python 3.9 from 3.8 by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18355
* [Example] RTDETR-ONNXRuntime-Python by semihhdemirel in https://github.com/ultralytics/ultralytics/pull/18369
* `ultralytics 8.3.54` New Streamlit inference Solution by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18316


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.53...v8.3.54

8.3.53

🌟 Summary  
The `v8.3.53` release introduces **enhanced argument validation during model export** to improve error handling and reduce user confusion, alongside other updates focusing on Dockerfile improvements for NVIDIA Jetson devices and internal code enhancements. 🚀  

---

📊 Key Changes  
Primary Feature: Enhanced Export Argument Validation  
- ✅ Introduced a mechanism to check whether export arguments are valid for specific formats (e.g., ONNX, TensorRT).  
- 🚫 Previously unsupported or incompatible arguments (e.g., `int8` without required calibration data) will now raise clear errors.  

Other Updates:  
- 🔧 **JetPack Dockerfile Enhancements**  
- JetPack 5: Updated base image, streamlined dependencies, and improved TensorRT compatibility.  
- JetPack 6: Removed unnecessary ONNX Runtime GPU package references for cleaner setup.  
- 🛠️ **Improved `settings.update()` Validation**: Ensures proper handling of input types and keys for user settings.  
- 🧹 **Code Cleanup**: Improved internal structures such as string representations for configuration objects (`JSONDict`) and URL handling (`clean_url`), improving performance and readability.  

---

🎯 Purpose &amp; Impact  
- **Export Validation Improvements**  
- 🚀 Provides users with **immediate feedback** on invalid export configurations.  
- 💪 Reduces confusion by preventing potentially misleading silent failures during export.  
- 🛡️ Ensures more **reliable model deployment** by enforcing compatibility checks early.  

- **Jetson Dockerfile Updates**  
- 🖥️ **Increased compatibility** with updated JetPack versions for NVIDIA Jetson devices.  
- 🔨 **Streamlined setup** for AI model training and deployment with YOLO on Jetsons.  

- **User-Friendly Enhancements**  
- 💡 Easier troubleshooting with clearer error messages for user settings and export configurations.  
- 📜 Simpler and more maintainable project codebase with reduced clutter in utilities and configuration processing.  

This release strongly benefits both developers configuring their models for export and users building YOLO models on NVIDIA platforms, ensuring smoother workflows and better system compatibility. 🚦

What&#x27;s Changed
* Fix JetPack6 Dockerfile for NVIDIA Jetson by lakshanthad in https://github.com/ultralytics/ultralytics/pull/18335
* Improve JetPack5 Dockerfile for NVIDIA Jetson by lakshanthad in https://github.com/ultralytics/ultralytics/pull/18334
* Validate arguments passed as dict to `settings.update()` by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18337
* `ultralytics 8.3.53` New Export argument validation by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18185


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.52...v8.3.53

8.3.52

📊 Key Changes
- **🚀 New `cuda_memory_usage` Utility**: Introduced a tool for dynamic monitoring and management of CUDA memory during operations.
- **💡 Improved Model Profiling**: Integrated memory tracking into the profiling process to report GPU memory usage alongside performance stats.
- **🔄 Enhanced Object Segmentation**: Modified `segment2box` for precise bounding box calculations when segments extend beyond the image boundaries.
- **📦 JetPack 6.1 Dockerfile Update**: Added compatibility for NVIDIA Jetson Orin Nano Super Developer Kit with dependency upgrades and performance benchmarks.
- **📖 Richer Documentation**: Added a CIFAR-100 tutorial video, improved clarity on `scale` parameter for multiscale training, and updated ROS and NVIDIA Jetson guides.
- **🧹 TFLite Example Cleanup**: Removed unnecessary RGB-to-BGR conversions for simpler and clearer example usage.

🎯 Purpose &amp; Impact
- **🚀 Enhanced Performance**: The `cuda_memory_usage` utility ensures more efficient GPU memory handling, reducing the risk of out-of-memory crashes during complex operations.
- **📈 Model Optimization**: Developers get richer profiling insights, aiding faster debugging and improving training/production readiness.
- **🖼️ Robust Object Detection**: Improved segmentation functionality provides accuracy even with challenging edge cases, making models more reliable.
- **🤖 Wider Compatibility**: Updating to JetPack 6.1 enables users to fully leverage NVIDIA Jetson’s latest hardware advancements (e.g., Orin Nano Super’s 67 TOPS).
- **📚 Simplified Learning**: Documentation improvements, including engaging tutorials and clarified parameters, lower the barrier to entry for both beginners and experts.
- **🧑‍💻 Beginner-Friendly Examples**: Streamlined TFLite examples ensure ease of adoption for new developers.

This release delivers meaningful improvements for developers working across GPU-heavy tasks, embedded systems, and edge AI deployments! 🚀

What&#x27;s Changed
* Revert `segment2box` and clip segments by Laughing-q in https://github.com/ultralytics/ultralytics/pull/18294
* Update JetPack6 Dockerfile with latest JetPack6.1 by lakshanthad in https://github.com/ultralytics/ultralytics/pull/18295
* Add https://youtu.be/6bZeCs0xwO4 to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18292
* Fix RGB to BGR conversion in TFLite example by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18305
* Align solutions YAML with `default.yaml` by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18300
* Fix incorrect `scale` description by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18303
* Update Jetson doc with NVIDIA Jetson Orin Nano Super Developer Kit by lakshanthad in https://github.com/ultralytics/ultralytics/pull/18289
* ROS Guide, updated YOLO version by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/18325
* `ultralytics 8.3.52` AutoBatch CUDA computation improvements by Laughing-q in https://github.com/ultralytics/ultralytics/pull/18291


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.51...v8.3.52

8.3.51

🌟 Summary
The **Ultralytics v8.3.51** release introduces improved robustness for training batch size optimization, documentation enhancements, new features like a security alarm system, and updates to facilitate the transition from YOLOv8 to YOLO11. 🚀

---

📊 Key Changes
- **Improved Batch Size Calculation**:
- Automated batch size determination now uses **logarithmic polynomial fitting** for better accuracy. 🧮
- Stricter checks ensure safe memory usage and prevent crashes due to misconfigurations. ✅
- **Hyperparameter Tuning**:
- Added **default hyperparameter search spaces** and clear examples in documentation for easier customization. 🛠️
- Updated training process to improve reliability by using `shell=True` for subprocess execution. ⚙️
- **YOLO11 Integration**:
- Updated examples, references, and documentation to reflect the transition from YOLOv8 to **YOLO11**. 📚
- Enhanced support for SAHI (Slicing Aided Hyper Inference) with YOLO11 models.
- **New Security Alarm System**:
- Added a ready-to-use, customizable **security alarm system** solution leveraging YOLO11. Includes email alerts when detections exceed thresholds. 🛡️
- **Expanded Export Options**:
- New formats supported, including **MNN** and **Sony IMX500**, enhancing deployment flexibility for diverse platforms. 🎉

---

🎯 Purpose &amp; Impact
- **Optimized Performance**:
- The refined autobatch method improves training stability and **GPU utilization** across various devices, helping users achieve smoother workflows.
- **Enhanced Usability**:
- New documentation simplifies hyperparameter tuning for beginners and advanced users alike, reducing the learning curve. 
- Updates to SAHI and model examples make it easier to adopt YOLO11.
- **Greater Flexibility**:
- Broader export options and integration tools expand YOLO&#x27;s adaptability for edge devices like **IMX500**.
- **Real-World Applications**:
- With the newly added **Security Alarm System**, users gain a powerful, practical monitoring tool ready for deployment in surveillance scenarios. 🚨

This release elevates Ultralytics by streamlining processes, expanding use cases, and improving reliability for developers and organizations. ⭐

What&#x27;s Changed
* Update SAHI example from `YOLOv8` to `YOLO11` by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18276
* Add `imx500` and `MNN` in `tutorial.ipynb` export table by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18254
* Add hyperparameter search space to Docs by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18259
* Use `shell=True` to run hyperparameter tuning by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18284
* Add security alarm system as ultralytics solution by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18281
* `ultralytics 8.3.51` AutoBach logspace fit and checks by Laughing-q in https://github.com/ultralytics/ultralytics/pull/18283


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.50...v8.3.51

8.3.50

---

📊 Key Changes  
- **Enhanced Segment Handling**:
- Segment resampling now dynamically adjusts the number of points based on the longest segment for better consistency. 🖌️  
- Empty segments during concatenation are gracefully handled to avoid errors.  
- **Improved Validation &amp; Model Workflow**:  
- Validation callbacks for OBB models now work correctly during training. 🔄  
- Updates to fix validation warnings when using untrained model YAMLs.  
- **Model Saving Updates**:  
- Improved checkpoint handling when saving models to reduce initialization errors. 💾  
- **Documentation Tweaks**:  
- Added multimedia content (audio &amp; video) to YOLO11 documentation for a richer learning experience. 🎧🎥  
- Cleaned up outdated entries (like the Sony IMX500) and enhanced clarity with new formatting and annotated argument types.  
- Internal docs configuration now supports cleaner URLs and auto-deployment enhancements. 🌐  
- **Bug Fixes**:
- Fixed CUDA-related bugs in the SAM module for more consistent device handling. 🛠️  
- Adjustments to prevent crashes in scenarios with mixed device usage.  

---

🎯 Purpose &amp; Impact  
- ✅ **Reliability Boost**: The improved resampling logic ensures stable training and avoids breaking workflows when handling variable-length segments.  
- 📈 **Performance Optimization**: Better checkpoint and validation handling streamlines user workflows and minimizes potential runtime errors.  
- 🌍 **Usability Improvements**: Updated Docs and multimedia resources make discovering and using features more user-friendly for both beginners and experts.  
- 🚀 **Cross-Device Consistency**: Fixes in CUDA logic ensure model compatibility on both CPU and GPU systems, enhancing accessibility.  
- 🖹 **Clean Documentation**: Removing outdated content and refining resources helps users focus on the latest tools and avoid confusion.  

This update is pivotal for developers and users working with segmentation models, large datasets, or seeking smoother workflows during benchmarking, training, and inference with YOLO models.

What&#x27;s Changed
* Removed duplicate IMX500 docs reference by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/18178
* Fix deleted author profile by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18180
* Fix validation callbacks not triggered during OBB model training by dagokl in https://github.com/ultralytics/ultralytics/pull/18175
* Fix untrained warning when training from yaml by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18168
* Fix SAM CUDA hard-code by adamp87 in https://github.com/ultralytics/ultralytics/pull/18153
* Add YOLO11 audio podcast by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18174
* Add https://youtu.be/qE-dfbB5Sis to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18207
* Add https://youtu.be/j0MOGKBqx7E to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18222
* Add type for `train` arguments by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18221
* Fix Docs relative trailing backlash bug by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18244
* Fix `model.save()` for model YAMLs by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18212
* `ultralytics 8.3.50` Enhanced segment resample by Laughing-q in https://github.com/ultralytics/ultralytics/pull/18171

New Contributors
* dagokl made their first contribution in https://github.com/ultralytics/ultralytics/pull/18175

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.49...v8.3.50

8.3.49

---

📊 Key Changes  
- **Docker Enhancements**:  
- Replaced standard `pip install` with `uv pip install` for better Python package management. 🐍🛠️  
- System-level package installations across all Dockerfiles for increased reliability.  
- Included flags like `--index-strategy` to handle edge cases more robustly.  

- **YOLO Dataset Compatibility**:  
- Standardized `category_id` indexing in COCO and LVIS datasets, starting indices from 1 for consistency. 📊  

- **PyTorch Version Support**:  
- Added compatibility for PyTorch `2.5` and Torchvision `0.20` versions. 🔄  

- **Documentation Improvements**:  
- Updated NVIDIA Jetson guide to explain Deep Learning Accelerator (DLA) functionality and limitations more clearly. 📝  
- Refined export format table for YOLOv5 to include improved links to relevant integration guides. 🌐  

- **Testing Optimization**:  
- Removed slow and outdated Google Drive-dependent tests to streamline testing workflows. 🧪  

- **GitHub Workflow Update**:  
- Added a `git pull` step to ensure the latest documentation changes are fetched before updates. ⚙️  

---

🎯 Purpose &amp; Impact  
- **Enhanced Package Management**:  
Consolidating Python package installations with `uv pip` ensures safer and more predictable setups, reducing dependency issues. 🛡️  

- **Better Dataset Compatibility**:  
Improved indexing logic aligns with common standards, reducing confusion during COCO/LVIS dataset evaluations. 📋  

- **Future-Ready PyTorch Support**:  
Developers leveraging the latest PyTorch and Torchvision versions can seamlessly integrate without compatibility issues, unlocking new features and performance improvements. 🚀  

- **Improved Documentation Usability**:  
Clearer and more accessible docs guide users in leveraging advanced features, such as model exporting and NVIDIA DLA usage, empowering informed decision-making. 📖✨  

- **More Efficient Testing**:  
By removing redundant tests, testing processes are faster and less prone to failure caused by external factors like rate limits. ⏩  

- **Robust Documentation Workflow**:  
Ensures smooth updates and reduces the likelihood of conflicts or overwriting recent changes in collaborative environments. ✅  

---

This update reflects Ultralytics&#x27; commitment to improving usability, stability, and developer experience across the board! 🌟

What&#x27;s Changed
* Bump astral-sh/setup-uv from 3 to 4 in /.github/workflows by dependabot[bot] in https://github.com/ultralytics/ultralytics/pull/18123
* Update Jetson Doc with DLA info by lakshanthad in https://github.com/ultralytics/ultralytics/pull/18128
* Update YOLOv5 export table links by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18130
* Update `torchvision` compatibility table by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18117
* Change index to start from 1 by default in `predictions.json` by Y-T-G in https://github.com/ultralytics/ultralytics/pull/18140
* Remove Google Drive test by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18162
* Git pull docs before updating by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18163
* `ultralytics 8.3.49` Docker images `uv pip install` by pderrenger in https://github.com/ultralytics/ultralytics/pull/18115


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.48...v8.3.49

8.3.48

🌟 Summary  
The `v8.3.48` release focuses on **enhanced security, efficiency, and user convenience** for the Ultralytics CI/CD pipelines and broader ecosystem. Key highlights include improved workflows for publishing, caching, documentation updates, and dependency handling. 🚀✨

---

📊 Key Changes
- **Workflow Security Enhancements**:
- Split PyPI publishing into **stages** (`check`, `build`, `publish`, and `notify`) for better control and automation. 🛠️
- Enabled version handling to ensure only necessary updates are pushed to PyPI. 🔄
- Improved notification systems for success or failure reporting. 📣
- **Dependency Improvements**:
- Added a `--no-cache` flag to ensure cleaner and more reliable Python installations during publishing workflows. 🧹
- **Better Cache Management**:
- Introduced automated CI cache pruning across workflows, reclaiming gigabytes of disk space in tests and GPU CI jobs. 🧑‍💻💾
- **Documentation Fixes**:
- Updated OpenVINO links to guide users toward the most recent version, ensuring accurate and up-to-date information. 🔗📄

---

🎯 Purpose &amp; Impact
- **Stronger Security** 🔒:
- The new CI/CD structure minimizes risks by organizing tasks into stricter, separate stages and limiting unnecessary permission exposure during workflows.
- **Improved CI/CD Efficiency** ✅:
- Automatic cache pruning and artifact handling enable faster builds/tests while reducing redundant storage usage.
- The `--no-cache` flag ensures the freshest dependencies, reducing debugging time caused by outdated installations.  
- **Enhanced User Experience** 🌟:
- Developers benefit from cleaner workflows in the open-source Ultralytics ecosystem, ensuring smoother package publishing and version management.
- Updated OpenVINO references ensure users can fully leverage recent AI acceleration tools for optimized model performance.

What&#x27;s Changed
* Update publish.yml with `--no-cache` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18095
* Add CI cache pruning by Burhan-Q in https://github.com/ultralytics/ultralytics/pull/17664
* OpenVINO broken link fix by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18107
* `ultralytics 8.3.48` split PyPI publish jobs for security by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18111


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.47...v8.3.48

Links

PyPI: https://pypi.org/project/ultralytics
Changelog: https://data.safetycli.com/changelogs/ultralytics/

dagshub · 2024-12-30T14:53:13Z

Join the discussion on DagsHub!

pyup-bot · 2025-01-13T14:53:14Z

Closing this in favor of #581

pyup-bot added 11 commits December 30, 2024 16:53

Update sphinx from 7.3.7 to 8.1.3

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Update furo from 2024.5.6 to 2024.8.6

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Update sphinx-autobuild from 2024.4.16 to 2024.10.3

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Update sphinx-click from 5.0.1 to 6.0.0

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Update setuptools from 70.0.0 to 75.6.0

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Update pytest from 8.2.1 to 8.3.4

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Update respx from 0.21.1 to 0.22.0

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Update pytest-env from 1.1.3 to 1.1.5

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Update fiftyone from 0.23.8 to 1.2.0

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Update datasets from 2.19.1 to 3.2.0

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Update ultralytics from 8.3.47 to 8.3.55

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pyup-bot mentioned this pull request Dec 30, 2024

Scheduled weekly dependency update for week 51 #570

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guysmoilov deleted the pyup-scheduled-update-2024-12-30 branch January 13, 2025 14:53

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Update sphinx from 7.3.7 to 8.1.3.

8.1.3

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8.1.1

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Update furo from 2024.5.6 to 2024.8.6.

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Update sphinx-autobuild from 2024.4.16 to 2024.10.3.

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2024.09.03

Update sphinx-click from 5.0.1 to 6.0.0.

Update setuptools from 70.0.0 to 75.6.0.

Update pytest from 8.2.1 to 8.3.4.

Update respx from 0.21.1 to 0.22.0.

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Update pytest-env from 1.1.3 to 1.1.5.

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Update fiftyone from 0.23.8 to 1.2.0.

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1.0.2

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Update datasets from 2.19.1 to 3.2.0.

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Update ultralytics from 8.3.47 to 8.3.55.

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