ultralytics 8.0.136 refactor and simplify package (ultralytics#3748)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <[email protected]>

.github/workflows/ci.yaml

@@ -111,22 +111,22 @@ jobs:
       - name: Benchmark DetectionModel
         shell: python
         run: |
-          from ultralytics.yolo.utils.benchmarks import benchmark
+          from ultralytics.utils.benchmarks import benchmark
           benchmark(model='${{ matrix.model }}.pt', imgsz=160, half=False, hard_fail=0.26)
       - name: Benchmark SegmentationModel
         shell: python
         run: |
-          from ultralytics.yolo.utils.benchmarks import benchmark
+          from ultralytics.utils.benchmarks import benchmark
           benchmark(model='${{ matrix.model }}-seg.pt', imgsz=160, half=False, hard_fail=0.30)
       - name: Benchmark ClassificationModel
         shell: python
         run: |
-          from ultralytics.yolo.utils.benchmarks import benchmark
+          from ultralytics.utils.benchmarks import benchmark
           benchmark(model='${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.36)
       - name: Benchmark PoseModel
         shell: python
         run: |
-          from ultralytics.yolo.utils.benchmarks import benchmark
+          from ultralytics.utils.benchmarks import benchmark
           benchmark(model='${{ matrix.model }}-pose.pt', imgsz=160, half=False, hard_fail=0.17)
       - name: Benchmark Summary
         run: |

.github/workflows/publish.yml

@@ -40,7 +40,7 @@ jobs:
           import os
           import pkg_resources as pkg
           import ultralytics
-          from ultralytics.yolo.utils.checks import check_latest_pypi_version
+          from ultralytics.utils.checks import check_latest_pypi_version
 
           v_local = pkg.parse_version(ultralytics.__version__).release
           v_pypi = pkg.parse_version(check_latest_pypi_version()).release

README.md

@@ -100,7 +100,7 @@ results = model("https://ultralytics.com/images/bus.jpg")  # predict on an image
 path = model.export(format="onnx")  # export the model to ONNX format
 ```
 
-[Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases). See YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more examples.
+[Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases). See YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more examples.
 
 </details>
 
@@ -110,7 +110,7 @@ YOLOv8 [Detect](https://docs.ultralytics.com/tasks/detect), [Segment](https://do
 
 <img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/main/im/banner-tasks.png">
 
-All [Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) on first use.
+All [Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) on first use.
 
 <details open><summary>Detection</summary>
 

README.zh-CN.md

@@ -100,7 +100,7 @@ results = model("https://ultralytics.com/images/bus.jpg")  # 对图像进行预
 success = model.export(format="onnx")  # 将模型导出为 ONNX 格式
 ```
 
-[模型](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models) 会自动从最新的 Ultralytics [发布版本](https://github.com/ultralytics/assets/releases)中下载。查看 YOLOv8 [Python 文档](https://docs.ultralytics.com/usage/python)以获取更多示例。
+[模型](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models) 会自动从最新的 Ultralytics [发布版本](https://github.com/ultralytics/assets/releases)中下载。查看 YOLOv8 [Python 文档](https://docs.ultralytics.com/usage/python)以获取更多示例。
 
 </details>
 
@@ -110,7 +110,7 @@ success = model.export(format="onnx")  # 将模型导出为 ONNX 格式
 
 <img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/main/im/banner-tasks.png">
 
-所有[模型](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/models)在首次使用时会自动从最新的Ultralytics [发布版本](https://github.com/ultralytics/assets/releases)下载。
+所有[模型](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models)在首次使用时会自动从最新的Ultralytics [发布版本](https://github.com/ultralytics/assets/releases)下载。
 
 <details open><summary>检测</summary>
 

docs/build_reference.py

@@ -10,7 +10,7 @@
 import re
 from collections import defaultdict
 from pathlib import Path
-from ultralytics.yolo.utils import ROOT
+from ultralytics.utils import ROOT
 
 NEW_YAML_DIR = ROOT.parent
 CODE_DIR = ROOT
@@ -39,7 +39,7 @@ def create_markdown(py_filepath, module_path, classes, functions):
         with open(md_filepath, 'r') as file:
             existing_content = file.read()
             header_parts = existing_content.split('---', 2)
-            if len(header_parts) >= 3:
+            if 'description:' in header_parts or 'comments:' in header_parts and len(header_parts) >= 3:
                 header_content = f"{header_parts[0]}---{header_parts[1]}---\n\n"
 
     module_path = module_path.replace('.__init__', '')

docs/datasets/detect/argoverse.md

@@ -29,12 +29,12 @@ The Argoverse dataset is widely used for training and evaluating deep learning m
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Argoverse dataset, the `Argoverse.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/Argoverse.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/Argoverse.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Argoverse dataset, the `Argoverse.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Argoverse.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Argoverse.yaml).
 
-!!! example "ultralytics/datasets/Argoverse.yaml"
+!!! example "ultralytics/cfg/datasets/Argoverse.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/Argoverse.yaml"
+    --8<-- "ultralytics/cfg/datasets/Argoverse.yaml"
     ```
 
 ## Usage

docs/datasets/detect/coco.md

@@ -29,12 +29,12 @@ The COCO dataset is widely used for training and evaluating deep learning models
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO dataset, the `coco.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO dataset, the `coco.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml).
 
-!!! example "ultralytics/datasets/coco.yaml"
+!!! example "ultralytics/cfg/datasets/coco.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/coco.yaml"
+    --8<-- "ultralytics/cfg/datasets/coco.yaml"
     ```
 
 ## Usage

docs/datasets/detect/coco8.md

@@ -19,12 +19,12 @@ and [YOLOv8](https://github.com/ultralytics/ultralytics).
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO8 dataset, the `coco8.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco8.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco8.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO8 dataset, the `coco8.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8.yaml).
 
-!!! example "ultralytics/datasets/coco8.yaml"
+!!! example "ultralytics/cfg/datasets/coco8.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/coco8.yaml"
+    --8<-- "ultralytics/cfg/datasets/coco8.yaml"
     ```
 
 ## Usage

docs/datasets/detect/globalwheat2020.md

@@ -28,12 +28,12 @@ The Global Wheat Head Dataset is widely used for training and evaluating deep le
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Global Wheat Head Dataset, the `GlobalWheat2020.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/GlobalWheat2020.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/GlobalWheat2020.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Global Wheat Head Dataset, the `GlobalWheat2020.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/GlobalWheat2020.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/GlobalWheat2020.yaml).
 
-!!! example "ultralytics/datasets/GlobalWheat2020.yaml"
+!!! example "ultralytics/cfg/datasets/GlobalWheat2020.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/GlobalWheat2020.yaml"
+    --8<-- "ultralytics/cfg/datasets/GlobalWheat2020.yaml"
     ```
 
 ## Usage

docs/datasets/detect/index.md

@@ -93,7 +93,7 @@ If you have your own dataset and would like to use it for training detection mod
 You can easily convert labels from the popular COCO dataset format to the YOLO format using the following code snippet:
 
 ```python
-from ultralytics.yolo.data.converter import convert_coco
+from ultralytics.data.converter import convert_coco
 
 convert_coco(labels_dir='../coco/annotations/')
 ```

docs/datasets/detect/objects365.md

@@ -28,12 +28,12 @@ The Objects365 dataset is widely used for training and evaluating deep learning
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Objects365 Dataset, the `Objects365.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/Objects365.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/Objects365.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Objects365 Dataset, the `Objects365.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Objects365.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Objects365.yaml).
 
-!!! example "ultralytics/datasets/Objects365.yaml"
+!!! example "ultralytics/cfg/datasets/Objects365.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/Objects365.yaml"
+    --8<-- "ultralytics/cfg/datasets/Objects365.yaml"
     ```
 
 ## Usage

docs/datasets/detect/sku-110k.md

@@ -30,12 +30,12 @@ The SKU-110k dataset is widely used for training and evaluating deep learning mo
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the SKU-110K dataset, the `SKU-110K.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/SKU-110K.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/SKU-110K.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the SKU-110K dataset, the `SKU-110K.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/SKU-110K.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/SKU-110K.yaml).
 
-!!! example "ultralytics/datasets/SKU-110K.yaml"
+!!! example "ultralytics/cfg/datasets/SKU-110K.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/SKU-110K.yaml"
+    --8<-- "ultralytics/cfg/datasets/SKU-110K.yaml"
     ```
 
 ## Usage

docs/datasets/detect/visdrone.md

@@ -26,12 +26,12 @@ The VisDrone dataset is widely used for training and evaluating deep learning mo
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the Visdrone dataset, the `VisDrone.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/VisDrone.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/VisDrone.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the Visdrone dataset, the `VisDrone.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VisDrone.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VisDrone.yaml).
 
-!!! example "ultralytics/datasets/VisDrone.yaml"
+!!! example "ultralytics/cfg/datasets/VisDrone.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/VisDrone.yaml"
+    --8<-- "ultralytics/cfg/datasets/VisDrone.yaml"
     ```
 
 ## Usage

docs/datasets/detect/voc.md

@@ -29,12 +29,12 @@ The VOC dataset is widely used for training and evaluating deep learning models
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the VOC dataset, the `VOC.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/VOC.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/VOC.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the VOC dataset, the `VOC.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VOC.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VOC.yaml).
 
-!!! example "ultralytics/datasets/VOC.yaml"
+!!! example "ultralytics/cfg/datasets/VOC.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/VOC.yaml"
+    --8<-- "ultralytics/cfg/datasets/VOC.yaml"
     ```
 
 ## Usage

docs/datasets/detect/xview.md

@@ -32,12 +32,12 @@ The xView dataset is widely used for training and evaluating deep learning model
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the xView dataset, the `xView.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/xView.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/xView.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the xView dataset, the `xView.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/xView.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/xView.yaml).
 
-!!! example "ultralytics/datasets/xView.yaml"
+!!! example "ultralytics/cfg/datasets/xView.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/xView.yaml"
+    --8<-- "ultralytics/cfg/datasets/xView.yaml"
     ```
 
 ## Usage

docs/datasets/pose/coco.md

@@ -30,12 +30,12 @@ The COCO-Pose dataset is specifically used for training and evaluating deep lear
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO-Pose dataset, the `coco-pose.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco-pose.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco-pose.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO-Pose dataset, the `coco-pose.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco-pose.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco-pose.yaml).
 
-!!! example "ultralytics/datasets/coco-pose.yaml"
+!!! example "ultralytics/cfg/datasets/coco-pose.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/coco-pose.yaml"
+    --8<-- "ultralytics/cfg/datasets/coco-pose.yaml"
     ```
 
 ## Usage

docs/datasets/pose/coco8-pose.md

@@ -19,12 +19,12 @@ and [YOLOv8](https://github.com/ultralytics/ultralytics).
 
 ## Dataset YAML
 
-A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO8-Pose dataset, the `coco8-pose.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco8-pose.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/datasets/coco8-pose.yaml).
+A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO8-Pose dataset, the `coco8-pose.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8-pose.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8-pose.yaml).
 
-!!! example "ultralytics/datasets/coco8-pose.yaml"
+!!! example "ultralytics/cfg/datasets/coco8-pose.yaml"
 
     ```yaml
-    --8<-- "ultralytics/datasets/coco8-pose.yaml"
+    --8<-- "ultralytics/cfg/datasets/coco8-pose.yaml"
     ```
 
 ## Usage

docs/datasets/pose/index.md

@@ -120,7 +120,7 @@ If you have your own dataset and would like to use it for training pose estimati
 Ultralytics provides a convenient conversion tool to convert labels from the popular COCO dataset format to YOLO format:
 
 ```python
-from ultralytics.yolo.data.converter import convert_coco
+from ultralytics.data.converter import convert_coco
 
 convert_coco(labels_dir='../coco/annotations/', use_keypoints=True)
 ```