Skip to content

Commit

Permalink
Update pyproject.toml and Docs (ultralytics#7274)
Browse files Browse the repository at this point in the history
Signed-off-by: Glenn Jocher <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Yaofu <[email protected]>
Co-authored-by: Umit Kacar, PhD <[email protected]>
  • Loading branch information
4 people authored Jan 4, 2024
1 parent e687c09 commit f702b34
Show file tree
Hide file tree
Showing 6 changed files with 18 additions and 15 deletions.
2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ repos:
name: Upgrade code

- repo: https://github.com/PyCQA/isort
rev: 5.12.0
rev: 5.13.2
hooks:
- id: isort
name: Sort imports
Expand Down
6 changes: 4 additions & 2 deletions docs/en/integrations/index.md
Original file line number Diff line number Diff line change
Expand Up @@ -30,13 +30,15 @@ Welcome to the Ultralytics Integrations page! This page provides an overview of

- [Ray Tune](ray-tune.md): Optimize the hyperparameters of your Ultralytics models at any scale.

- [TensorBoard](https://tensorboard.dev/): Visualize your Ultralytics ML workflows, monitor model metrics, and foster team collaboration.
- [TensorBoard](tensorboard.md): Visualize your Ultralytics ML workflows, monitor model metrics, and foster team collaboration.

- [Weights & Biases (W&B)](weights-biases.md): Monitor experiments, visualize metrics, and foster reproducibility and collaboration on Ultralytics projects.

- [Amazon SageMaker](amazon-sagemaker.md): Leverage Amazon SageMaker to efficiently build, train, and deploy Ultralytics models, providing an all-in-one platform for the ML lifecycle.

## Deployment Integrations

- [Neural Magic](https://neuralmagic.com/): Leverage Quantization Aware Training (QAT) and pruning techniques to optimize Ultralytics models for superior performance and leaner size.
- [Neural Magic](neural-magic.md): Leverage Quantization Aware Training (QAT) and pruning techniques to optimize Ultralytics models for superior performance and leaner size.

- [OpenVino](openvino.md): OpenVINO is Intel's toolkit for optimizing and deploying computer vision models efficiently across various Intel hardware platforms.

Expand Down
6 changes: 1 addition & 5 deletions docs/en/reference/data/augment.md
Original file line number Diff line number Diff line change
Expand Up @@ -79,10 +79,6 @@ keywords: Ultralytics, Data Augmentation, BaseTransform, MixUp, RandomHSV, Lette

<br><br>

## ::: ultralytics.data.augment.hsv2colorjitter

<br><br>

## ::: ultralytics.data.augment.classify_albumentations
## ::: ultralytics.data.augment.classify_augmentations

<br><br>
5 changes: 4 additions & 1 deletion docs/mkdocs.yml
Original file line number Diff line number Diff line change
Expand Up @@ -289,6 +289,9 @@ nav:
- ClearML: integrations/clearml.md
- DVC: integrations/dvc.md
- Weights & Biases: integrations/weights-biases.md
- Neural Magic: integrations/neural-magic.md
- TensorBoard: integrations/tensorboard.md
- Amazon SageMaker: integrations/amazon-sagemaker.md
- Usage:
- CLI: usage/cli.md
- Python: usage/python.md
Expand Down Expand Up @@ -416,8 +419,8 @@ nav:
- tasks: reference/nn/tasks.md
- solutions:
- ai_gym: reference/solutions/ai_gym.md
- object_counter: reference/solutions/object_counter.md
- heatmap: reference/solutions/heatmap.md
- object_counter: reference/solutions/object_counter.md
- trackers:
- basetrack: reference/trackers/basetrack.md
- bot_sort: reference/trackers/bot_sort.md
Expand Down
9 changes: 6 additions & 3 deletions pyproject.toml
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
#

# Overview:
# This pyproject.toml file manages the build, packaging, and distribution of the Ultralytics library.
# It defines essential project metadata, dependencies, and settings used to develop and deploy the library.
Expand Down Expand Up @@ -159,6 +159,9 @@ space_between_ending_comma_and_closing_bracket = true
split_before_closing_bracket = false
split_before_first_argument = false

[tool.ruff]
line-length = 120

[tool.docformatter]
wrap-summaries = 120
wrap-descriptions = 120
Expand All @@ -167,5 +170,5 @@ pre-summary-newline = true
close-quotes-on-newline = true

[tool.codespell]
ignore-words-list = "crate,nd,strack,dota,ane,segway,fo,gool,winn"
skip = '*.csv,*venv*,docs/de,docs/fr,docs/pt,docs/es,docs/mkdocs_de.yml'
ignore-words-list = "crate,nd,strack,dota,ane,segway,fo,gool,winn,commend"
skip = '*.csv,*venv*,docs/??/,docs/mkdocs_??.yml'
5 changes: 2 additions & 3 deletions ultralytics/data/augment.py
Original file line number Diff line number Diff line change
Expand Up @@ -1005,7 +1005,7 @@ def classify_transforms(
crop_fraction (float): fraction of image to crop. default is 1.0.
Returns:
T.Compose: torchvision transforms
(T.Compose): torchvision transforms
"""

if isinstance(size, (tuple, list)):
Expand Down Expand Up @@ -1064,13 +1064,12 @@ def classify_augmentations(
hsv_h (float): image HSV-Hue augmentation (fraction)
hsv_s (float): image HSV-Saturation augmentation (fraction)
hsv_v (float): image HSV-Value augmentation (fraction)
contrast (float): image contrast augmentation (fraction)
force_color_jitter (bool): force to apply color jitter even if auto augment is enabled
erasing (float): probability of random erasing
interpolation (T.InterpolationMode): interpolation mode. default is T.InterpolationMode.BILINEAR.
Returns:
T.Compose: torchvision transforms
(T.Compose): torchvision transforms
"""
# Transforms to apply if albumentations not installed
if not isinstance(size, int):
Expand Down

0 comments on commit f702b34

Please sign in to comment.