ultralytics 8.0.51 add assets and CI actions (#1296)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Paul Kehrer <paulhkehrer@gmail.com>
2025-05-22 21:04:21 +08:00 · 2023-03-07 20:25:10 +01:00 · 2023-03-07 20:25:10 +01:00 · 790f9c067c
commit 790f9c067c
parent f0d8e4718b
21 changed files with 272 additions and 107 deletions
--- a/.github/workflows/ci.yaml
+++ b/.github/workflows/ci.yaml
@ -26,16 +26,7 @@ jobs:
      - uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
-      - name: Get cache dir  # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow
-        id: pip-cache
-        run: echo "dir=$(pip cache dir)" >> $GITHUB_OUTPUT
-        shell: bash  # for Windows compatibility
-      - name: Cache pip
-        uses: actions/cache@v3
-        with:
-          path: ${{ steps.pip-cache.outputs.dir }}
-          key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }}
-          restore-keys: ${{ runner.os }}-${{ matrix.python-version }}-pip-
+          cache: 'pip' # caching pip dependencies
      - name: Install requirements
        shell: bash  # for Windows compatibility
        run: |
@ -76,16 +67,7 @@ jobs:
      - uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
-      - name: Get cache dir  # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow
-        id: pip-cache
-        run: echo "dir=$(pip cache dir)" >> $GITHUB_OUTPUT
-        shell: bash  # for Windows compatibility
-      - name: Cache pip
-        uses: actions/cache@v3
-        with:
-          path: ${{ steps.pip-cache.outputs.dir }}
-          key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }}
-          restore-keys: ${{ runner.os }}-${{ matrix.python-version }}-pip-
+          cache: 'pip' # caching pip dependencies
      - name: Install requirements
        shell: bash  # for Windows compatibility
        run: |
@ -145,16 +127,7 @@ jobs:
      - uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
-      - name: Get cache dir  # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow
-        id: pip-cache
-        run: echo "dir=$(pip cache dir)" >> $GITHUB_OUTPUT
-        shell: bash  # for Windows compatibility
-      - name: Cache pip
-        uses: actions/cache@v3
-        with:
-          path: ${{ steps.pip-cache.outputs.dir }}
-          key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }}
-          restore-keys: ${{ runner.os }}-${{ matrix.python-version }}-pip-
+          cache: 'pip' # caching pip dependencies
      - name: Install requirements
        shell: bash  # for Windows compatibility
        run: |
--- a/.github/workflows/greetings.yml
+++ b/.github/workflows/greetings.yml
@ -0,0 +1,55 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
+name: Greetings
+
+on:
+  pull_request_target:
+    types: [opened]
+  issues:
+    types: [opened]
+
+jobs:
+  greeting:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/first-interaction@v1
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+          pr-message: |
+            👋 Hello @${{ github.actor }}, thank you for submitting a YOLOv8 🚀 PR! To allow your work to be integrated as seamlessly as possible, we advise you to:
+
+            - ✅ Verify your PR is **up-to-date** with `ultralytics/ultralytics` `main` branch. If your PR is behind you can update your code by clicking the 'Update branch' button or by running `git pull` and `git merge master` locally.
+            - ✅ Verify all YOLOv8 Continuous Integration (CI) **checks are passing**.
+            - ✅ Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_  — Bruce Lee
+
+            See our [Contributing Guide](https://github.com/ultralytics/ultralytics/blob/main/CONTRIBUTING.md) for details and let us know if you have any questions!
+
+          issue-message: |
+            👋 Hello @${{ github.actor }}, thank you for your interest in YOLOv8 🚀! We recommend a visit to the [YOLOv8 Docs](https://docs.ultralytics.com) for new users where you can find many [Python](https://docs.ultralytics.com/python/) and [CLI](https://docs.ultralytics.com/cli/) usage examples and where many of the most common questions may already be answered.
+
+            If this is a 🐛 Bug Report, please provide a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us debug it.
+
+            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results).
+
+            ## Install
+
+            Pip install the `ultralytics` package including all [requirements.txt](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt) in a [**Python>=3.7**](https://www.python.org/) environment with [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/).
+
+            ```bash
+            pip install ultralytics
+            ```
+
+            ## Environments
+
+            YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including [CUDA](https://developer.nvidia.com/cuda)/[CUDNN](https://developer.nvidia.com/cudnn), [Python](https://www.python.org/) and [PyTorch](https://pytorch.org/) preinstalled):
+
+            - **Notebooks** with free GPU: <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Run on Gradient"/></a> <a href="https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> <a href="https://www.kaggle.com/ultralytics/yolov8"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a>
+            - **Google Cloud** Deep Learning VM. See [GCP Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart)
+            - **Amazon** Deep Learning AMI. See [AWS Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart)
+            - **Docker Image**. See [Docker Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/Docker-Quickstart) <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Docker Pulls"></a>
+
+            ## Status
+
+            <a href="https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml?query=event%3Aschedule"><img src="https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml/badge.svg" alt="Ultralytics CI"></a>
+
+            If this badge is green, all [Ultralytics CI](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml?query=event%3Aschedule) tests are currently passing. CI tests verify correct operation of all YOLOv8 modes and tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
--- a/.github/workflows/publish.yml
+++ b/.github/workflows/publish.yml
@ -0,0 +1,67 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+# Publish pip package to PyPI https://pypi.org/project/ultralytics/ and Docs to https://docs.ultralytics.com
+
+name: Publish to PyPI and Deploy Docs
+
+on:
+  workflow_dispatch:
+    inputs:
+      pypi:
+        type: boolean
+        description: Publish to PyPI
+      docs:
+        type: boolean
+        description: Deploy Docs
+  push:
+    branches: [main]
+
+jobs:
+  publish:
+    if: github.repository == 'ultralytics/ultralytics' && github.actor == 'glenn-jocher'
+    name: Publish
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+      - name: Set up Python environment
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+          cache: 'pip' # caching pip dependencies
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip wheel build twine
+          pip install -e '.[dev]' --extra-index-url https://download.pytorch.org/whl/cpu
+      - name: Check PyPI version
+        shell: python
+        run: |
+          import pkg_resources as pkg
+          import ultralytics
+          import os
+          from ultralytics.yolo.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
+          print(f'Local version is {v_local}')
+          print(f'PyPI version is {v_pypi}')
+          d = [a - b for a, b in zip(v_local, v_pypi)]  # diff
+          increment = (d[0] == d[1] == 0) and d[2] == 1  # only patch increment by 1
+          os.system(f'echo "increment={increment}" >> $GITHUB_OUTPUT')
+          if increment:
+              print('Local version is higher than PyPI version. Publishing new version to PyPI ✅.')
+        id: check_pypi
+      - name: Publish to PyPI
+        continue-on-error: true
+        if: (github.event_name == 'push' || github.event.inputs.pypi == 'true')  && steps.check_pypi.outputs.increment == 'True'
+        env:
+          PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }}
+        run: |
+          python -m build
+          python -m twine upload dist/* -u __token__ -p $PYPI_TOKEN
+      - name: Deploy Docs
+        continue-on-error: true
+        if: (github.event_name == 'push' && steps.check_pypi.outputs.increment == 'True') || github.event.inputs.docs == 'true'
+        run: |
+          mkdocs gh-deploy || true
+          git checkout gh-pages
+          git push https://github.com/ultralytics/docs gh-pages --force
--- a/.github/workflows/stale.yml
+++ b/.github/workflows/stale.yml
@ -0,0 +1,47 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+
+name: Close stale issues
+on:
+  schedule:
+    - cron: '0 0 * * *'  # Runs at 00:00 UTC every day
+
+jobs:
+  stale:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/stale@v7
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+          stale-issue-message: |
+            👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.
+
+            For additional resources and information, please see the links below:
+
+            - **Docs**: https://docs.ultralytics.com
+            - **HUB**: https://hub.ultralytics.com
+            - **Community**: https://community.ultralytics.com
+
+            Feel free to inform us of any other **issues** you discover or **feature requests** that come to mind in the future. Pull Requests (PRs) are also always welcomed!
+
+            Thank you for your contributions to YOLO 🚀 and Vision AI ⭐
+
+          stale-pr-message: |
+            👋 Hello there! We wanted to let you know that we've decided to close this pull request due to inactivity. We appreciate the effort you put into contributing to our project, but unfortunately, not all contributions are suitable or aligned with our product roadmap.
+
+            We hope you understand our decision, and please don't let it discourage you from contributing to open source projects in the future. We value all of our community members and their contributions, and we encourage you to keep exploring new projects and ways to get involved.
+
+            For additional resources and information, please see the links below:
+
+            - **Docs**: https://docs.ultralytics.com
+            - **HUB**: https://hub.ultralytics.com
+            - **Community**: https://community.ultralytics.com
+
+            Thank you for your contributions to YOLO 🚀 and Vision AI ⭐
+
+          days-before-issue-stale: 30
+          days-before-issue-close: 10
+          days-before-pr-stale: 90
+          days-before-pr-close: 30
+          exempt-issue-labels: 'documentation,tutorial,TODO'
+          operations-per-run: 300  # The maximum number of operations per run, used to control rate limiting.
--- a/MANIFEST.in
+++ b/MANIFEST.in
@ -2,5 +2,7 @@ include *.md
 include requirements.txt
 include LICENSE
 include setup.py
+include ultralytics/assets/bus.jpg
+include ultralytics/assets/zidane.jpg
 recursive-include ultralytics *.yaml
 recursive-exclude __pycache__ *
--- a/requirements.txt
+++ b/requirements.txt
@ -14,7 +14,7 @@ torchvision>=0.8.1
 tqdm>=4.64.0

 # Logging -------------------------------------
-tensorboard>=2.4.1
+# tensorboard>=2.4.1
 # clearml
 # comet

@ -41,4 +41,3 @@ thop>=0.1.1  # FLOPs computation
 # albumentations>=1.0.3
 # pycocotools>=2.0.6  # COCO mAP
 # roboflow
-certifi>=2022.12.7 # not directly required, pinned by Snyk to avoid a vulnerability
--- a/ultralytics/init.py
+++ b/ultralytics/init.py
@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, GPL-3.0 license

-__version__ = '8.0.50'
+__version__ = '8.0.51'

 from ultralytics.yolo.engine.model import YOLO
 from ultralytics.yolo.utils.checks import check_yolo as checks
--- a/ultralytics/assets/bus.jpg
+++ b/ultralytics/assets/bus.jpg
--- a/ultralytics/assets/zidane.jpg
+++ b/ultralytics/assets/zidane.jpg
--- a/ultralytics/nn/autobackend.py
+++ b/ultralytics/nn/autobackend.py
@ -14,7 +14,7 @@ import torch
 import torch.nn as nn
 from PIL import Image

-from ultralytics.yolo.utils import LOGGER, ROOT, yaml_load
+from ultralytics.yolo.utils import LINUX, LOGGER, ROOT, yaml_load
 from ultralytics.yolo.utils.checks import check_requirements, check_suffix, check_version, check_yaml
 from ultralytics.yolo.utils.downloads import attempt_download_asset, is_url
 from ultralytics.yolo.utils.ops import xywh2xyxy
@ -143,7 +143,12 @@ class AutoBackend(nn.Module):
            metadata = w.parent / 'metadata.yaml'
        elif engine:  # TensorRT
            LOGGER.info(f'Loading {w} for TensorRT inference...')
-            import tensorrt as trt  # https://developer.nvidia.com/nvidia-tensorrt-download
+            try:
+                import tensorrt as trt  # noqa https://developer.nvidia.com/nvidia-tensorrt-download
+            except ImportError:
+                if LINUX:
+                    check_requirements('nvidia-tensorrt', cmds='-U --index-url https://pypi.ngc.nvidia.com')
+                import tensorrt as trt  # noqa
            check_version(trt.__version__, '7.0.0', hard=True)  # require tensorrt>=7.0.0
            if device.type == 'cpu':
                device = torch.device('cuda:0')
@ -230,7 +235,7 @@ class AutoBackend(nn.Module):
        elif paddle:  # PaddlePaddle
            LOGGER.info(f'Loading {w} for PaddlePaddle inference...')
            check_requirements('paddlepaddle-gpu' if cuda else 'paddlepaddle')
-            import paddle.inference as pdi
+            import paddle.inference as pdi  # noqa
            w = Path(w)
            if not w.is_file():  # if not *.pdmodel
                w = next(w.rglob('*.pdmodel'))  # get *.pdmodel file from *_paddle_model dir
@ -260,11 +265,16 @@ class AutoBackend(nn.Module):
        if isinstance(metadata, (str, Path)) and Path(metadata).exists():
            metadata = yaml_load(metadata)
        if metadata:
-            stride = int(metadata['stride'])
+            for k, v in metadata.items():
+                if k in ('stride', 'batch'):
+                    metadata[k] = int(v)
+                elif k in ('imgsz', 'names') and isinstance(v, str):
+                    metadata[k] = eval(v)
+            stride = metadata['stride']
            task = metadata['task']
-            batch = int(metadata['batch'])
-            imgsz = eval(metadata['imgsz']) if isinstance(metadata['imgsz'], str) else metadata['imgsz']
-            names = eval(metadata['names']) if isinstance(metadata['names'], str) else metadata['names']
+            batch = metadata['batch']
+            imgsz = metadata['imgsz']
+            names = metadata['names']
        elif not (pt or triton or nn_module):
            LOGGER.warning(f"WARNING ⚠️ Metadata not found for 'model={weights}'")

@ -285,7 +295,7 @@ class AutoBackend(nn.Module):
            visualize (bool): whether to visualize the output predictions, defaults to False

        Returns:
-            (tuple): Tuple containing the raw output tensor, and the processed output for visualization (if visualize=True)
+            (tuple): Tuple containing the raw output tensor, and processed output for visualization (if visualize=True)
        """
        b, ch, h, w = im.shape  # batch, channel, height, width
        if self.fp16 and im.dtype != torch.float16:
--- a/ultralytics/nn/modules.py
+++ b/ultralytics/nn/modules.py
@ -67,7 +67,8 @@ class ConvTranspose(nn.Module):


 class DFL(nn.Module):
-    # Integral module of Distribution Focal Loss (DFL) proposed in Generalized Focal Loss https://ieeexplore.ieee.org/document/9792391
+    # Integral module of Distribution Focal Loss (DFL)
+    # Proposed in Generalized Focal Loss https://ieeexplore.ieee.org/document/9792391
    def __init__(self, c1=16):
        super().__init__()
        self.conv = nn.Conv2d(c1, 1, 1, bias=False).requires_grad_(False)
--- a/ultralytics/nn/tasks.py
+++ b/ultralytics/nn/tasks.py
@ -8,7 +8,9 @@ import thop
 import torch
 import torch.nn as nn

-from ultralytics.nn.modules import *  # noqa: F403
+from ultralytics.nn.modules import (C1, C2, C3, C3TR, SPP, SPPF, Bottleneck, BottleneckCSP, C2f, C3Ghost, C3x, Classify,
+                                    Concat, Conv, ConvTranspose, Detect, DWConv, DWConvTranspose2d, Ensemble, Focus,
+                                    GhostBottleneck, GhostConv, Segment)
 from ultralytics.yolo.utils import DEFAULT_CFG_DICT, DEFAULT_CFG_KEYS, LOGGER, RANK, colorstr, emojis, yaml_load
 from ultralytics.yolo.utils.checks import check_requirements, check_yaml
 from ultralytics.yolo.utils.torch_utils import (fuse_conv_and_bn, fuse_deconv_and_bn, initialize_weights,
@ -324,9 +326,9 @@ class ClassificationModel(BaseModel):

 def torch_safe_load(weight):
    """
-    This function attempts to load a PyTorch model with the torch.load() function. If a ModuleNotFoundError is raised, it
-    catches the error, logs a warning message, and attempts to install the missing module via the check_requirements()
-    function. After installation, the function again attempts to load the model using torch.load().
+    This function attempts to load a PyTorch model with the torch.load() function. If a ModuleNotFoundError is raised,
+    it catches the error, logs a warning message, and attempts to install the missing module via the
+    check_requirements() function. After installation, the function again attempts to load the model using torch.load().

    Args:
        weight (str): The file path of the PyTorch model.
--- a/ultralytics/tracker/utils/matching.py
+++ b/ultralytics/tracker/utils/matching.py
@ -40,7 +40,10 @@ def linear_assignment(cost_matrix, thresh):
    if cost_matrix.size == 0:
        return np.empty((0, 2), dtype=int), tuple(range(cost_matrix.shape[0])), tuple(range(cost_matrix.shape[1]))
    matches, unmatched_a, unmatched_b = [], [], []
+
+    # TODO: investigate scipy.optimize.linear_sum_assignment() for lap.lapjv()
    cost, x, y = lap.lapjv(cost_matrix, extend_cost=True, cost_limit=thresh)
+
    matches.extend([ix, mx] for ix, mx in enumerate(x) if mx >= 0)
    unmatched_a = np.where(x < 0)[0]
    unmatched_b = np.where(y < 0)[0]
--- a/ultralytics/yolo/cfg/init.py
+++ b/ultralytics/yolo/cfg/init.py
@ -327,4 +327,4 @@ def copy_default_cfg():

 if __name__ == '__main__':
    # entrypoint(debug='yolo predict model=yolov8n.pt')
-    entrypoint(debug='yolo train model=yolov8n-seg.pt')
+    entrypoint(debug='')
--- a/ultralytics/yolo/data/utils.py
+++ b/ultralytics/yolo/data/utils.py
@ -210,8 +210,7 @@ def check_det_dataset(dataset, autodownload=True):
    for k in 'train', 'val', 'names':
        if k not in data:
            raise SyntaxError(
-                emojis(f"{dataset} '{k}:' key missing ❌.\n"
-                       f"'train', 'val' and 'names' are required in data.yaml files."))
+                emojis(f"{dataset} '{k}:' key missing ❌.\n'train', 'val' and 'names' are required in all data YAMLs."))
    data['names'] = check_class_names(data['names'])
    data['nc'] = len(data['names'])

@ -236,11 +235,11 @@ def check_det_dataset(dataset, autodownload=True):
    if val:
        val = [Path(x).resolve() for x in (val if isinstance(val, list) else [val])]  # val path
        if not all(x.exists() for x in val):
-            msg = f"\nDataset '{dataset}' not found ⚠️, missing paths %s" % [str(x) for x in val if not x.exists()]
+            m = f"\nDataset '{dataset}' images not found ⚠️, missing paths %s" % [str(x) for x in val if not x.exists()]
            if s and autodownload:
-                LOGGER.warning(msg)
+                LOGGER.warning(m)
            else:
-                raise FileNotFoundError(msg)
+                raise FileNotFoundError(m)
            t = time.time()
            if s.startswith('http') and s.endswith('.zip'):  # URL
                safe_download(url=s, dir=DATASETS_DIR, delete=True)
--- a/ultralytics/yolo/engine/exporter.py
+++ b/ultralytics/yolo/engine/exporter.py
@ -69,7 +69,7 @@ from ultralytics.yolo.data.dataloaders.stream_loaders import LoadImages
 from ultralytics.yolo.data.utils import IMAGENET_MEAN, IMAGENET_STD, check_det_dataset
 from ultralytics.yolo.utils import (DEFAULT_CFG, LINUX, LOGGER, MACOS, __version__, callbacks, colorstr,
                                    get_default_args, yaml_save)
-from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version, check_yaml
+from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version
 from ultralytics.yolo.utils.files import file_size
 from ultralytics.yolo.utils.ops import Profile
 from ultralytics.yolo.utils.torch_utils import get_latest_opset, select_device, smart_inference_mode
@ -601,7 +601,7 @@ class Exporter:
                    if n >= n_images:
                        break

-            dataset = LoadImages(check_det_dataset(check_yaml(self.args.data))['train'], imgsz=imgsz, auto=False)
+            dataset = LoadImages(check_det_dataset(self.args.data)['train'], imgsz=imgsz, auto=False)
            converter.representative_dataset = lambda: representative_dataset_gen(dataset, n_images=100)
            converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
            converter.target_spec.supported_types = []
--- a/ultralytics/yolo/engine/model.py
+++ b/ultralytics/yolo/engine/model.py
@ -10,7 +10,7 @@ from ultralytics.yolo.cfg import get_cfg
 from ultralytics.yolo.engine.exporter import Exporter
 from ultralytics.yolo.utils import (DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_KEYS, LOGGER, ONLINE, RANK, ROOT,
                                    callbacks, is_git_dir, is_pip_package, yaml_load)
-from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_pip_update, check_yaml
+from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_pip_update_available, check_yaml
 from ultralytics.yolo.utils.downloads import GITHUB_ASSET_STEMS
 from ultralytics.yolo.utils.torch_utils import smart_inference_mode

@ -158,7 +158,7 @@ class YOLO:
        Inform user of ultralytics package update availability
        """
        if ONLINE and is_pip_package():
-            check_pip_update()
+            check_pip_update_available()

    def reset(self):
        """
--- a/ultralytics/yolo/engine/results.py
+++ b/ultralytics/yolo/engine/results.py
@ -263,8 +263,11 @@ class Boxes:
        return self.boxes.__str__()

    def __repr__(self):
-        return (f'Ultralytics YOLO {self.__class__.__name__}\n' + f'type: {type(self.boxes)}\n' +
-                f'shape: {self.boxes.shape}\n' + f'dtype: {self.boxes.dtype}\n + {self.boxes.__repr__()}')
+        return (f'{self.__class__.__module__}.{self.__class__.__name__}\n'
+                f'type:  {self.boxes.__class__.__module__}.{self.boxes.__class__.__name__}\n'
+                f'shape: {self.boxes.shape}\n'
+                f'dtype: {self.boxes.dtype}\n'
+                f'{self.boxes.__repr__()}')

    def __getitem__(self, idx):
        return Boxes(self.boxes[idx], self.orig_shape)
@ -339,8 +342,11 @@ class Masks:
        return self.masks.__str__()

    def __repr__(self):
-        return (f'Ultralytics YOLO {self.__class__.__name__}\n' + f'type: {type(self.masks)}\n' +
-                f'shape: {self.masks.shape}\n' + f'dtype: {self.masks.dtype}\n + {self.masks.__repr__()}')
+        return (f'{self.__class__.__module__}.{self.__class__.__name__}\n'
+                f'type:  {self.masks.__class__.__module__}.{self.masks.__class__.__name__}\n'
+                f'shape: {self.masks.shape}\n'
+                f'dtype: {self.masks.dtype}\n'
+                f'{self.masks.__repr__()}')

    def __getitem__(self, idx):
        return Masks(self.masks[idx], self.orig_shape)
--- a/ultralytics/yolo/utils/init.py
+++ b/ultralytics/yolo/utils/init.py
@ -126,6 +126,37 @@ class IterableSimpleNamespace(SimpleNamespace):
        return getattr(self, key, default)


+def set_logging(name=LOGGING_NAME, verbose=True):
+    # sets up logging for the given name
+    rank = int(os.getenv('RANK', -1))  # rank in world for Multi-GPU trainings
+    level = logging.INFO if verbose and rank in {-1, 0} else logging.ERROR
+    logging.config.dictConfig({
+        'version': 1,
+        'disable_existing_loggers': False,
+        'formatters': {
+            name: {
+                'format': '%(message)s'}},
+        'handlers': {
+            name: {
+                'class': 'logging.StreamHandler',
+                'formatter': name,
+                'level': level}},
+        'loggers': {
+            name: {
+                'level': level,
+                'handlers': [name],
+                'propagate': False}}})
+
+
+# Set logger
+set_logging(LOGGING_NAME, verbose=VERBOSE)  # run before defining LOGGER
+LOGGER = logging.getLogger(LOGGING_NAME)  # define globally (used in train.py, val.py, detect.py, etc.)
+if WINDOWS:  # emoji-safe logging
+    info_fn, warning_fn = LOGGER.info, LOGGER.warning
+    setattr(LOGGER, info_fn.__name__, lambda x: info_fn(emojis(x)))
+    setattr(LOGGER, warning_fn.__name__, lambda x: warning_fn(emojis(x)))
+
+
 def yaml_save(file='data.yaml', data=None):
    """
    Save YAML data to a file.
@ -163,10 +194,13 @@ def yaml_load(file='data.yaml', append_filename=False):
        dict: YAML data and file name.
    """
    with open(file, errors='ignore', encoding='utf-8') as f:
-        # Add YAML filename to dict and return
        s = f.read()  # string
-        if not s.isprintable():  # remove special characters
+
+        # Remove special characters
+        if not s.isprintable():
            s = re.sub(r'[^\x09\x0A\x0D\x20-\x7E\x85\xA0-\uD7FF\uE000-\uFFFD\U00010000-\U0010ffff]+', '', s)
+
+        # Add YAML filename to dict and return
        return {**yaml.safe_load(s), 'yaml_file': str(file)} if append_filename else yaml.safe_load(s)


@ -448,41 +482,6 @@ def colorstr(*input):
    return ''.join(colors[x] for x in args) + f'{string}' + colors['end']


-def remove_ansi_codes(string):
-    """
-    Remove ANSI escape sequences from a string.
-
-    Args:
-        string (str): The input string that may contain ANSI escape sequences.
-
-    Returns:
-        str: The input string with ANSI escape sequences removed.
-    """
-    return re.sub(r'\x1B\[([0-9]{1,2}(;[0-9]{1,2})?)?[m|K]', '', string)
-
-
-def set_logging(name=LOGGING_NAME, verbose=True):
-    # sets up logging for the given name
-    rank = int(os.getenv('RANK', -1))  # rank in world for Multi-GPU trainings
-    level = logging.INFO if verbose and rank in {-1, 0} else logging.ERROR
-    logging.config.dictConfig({
-        'version': 1,
-        'disable_existing_loggers': False,
-        'formatters': {
-            name: {
-                'format': '%(message)s'}},
-        'handlers': {
-            name: {
-                'class': 'logging.StreamHandler',
-                'formatter': name,
-                'level': level}},
-        'loggers': {
-            name: {
-                'level': level,
-                'handlers': [name],
-                'propagate': False}}})
-
-
 class TryExcept(contextlib.ContextDecorator):
    # YOLOv8 TryExcept class. Usage: @TryExcept() decorator or 'with TryExcept():' context manager
    def __init__(self, msg='', verbose=True):
@ -609,13 +608,6 @@ def set_settings(kwargs, file=USER_CONFIG_DIR / 'settings.yaml'):

 # Run below code on yolo/utils init ------------------------------------------------------------------------------------

-# Set logger
-set_logging(LOGGING_NAME, verbose=VERBOSE)  # run before defining LOGGER
-LOGGER = logging.getLogger(LOGGING_NAME)  # define globally (used in train.py, val.py, detect.py, etc.)
-if WINDOWS:
-    for fn in LOGGER.info, LOGGER.warning:
-        setattr(LOGGER, fn.__name__, lambda x: fn(emojis(x)))  # emoji safe logging
-
 # Check first-install steps
 PREFIX = colorstr('Ultralytics: ')
 SETTINGS = get_settings()
--- a/ultralytics/yolo/utils/checks.py
+++ b/ultralytics/yolo/utils/checks.py
@ -134,12 +134,20 @@ def check_latest_pypi_version(package_name='ultralytics'):
    return None


-def check_pip_update():
+def check_pip_update_available():
+    """
+    Checks if a new version of the ultralytics package is available on PyPI.
+
+    Returns:
+        bool: True if an update is available, False otherwise.
+    """
    from ultralytics import __version__
    latest = check_latest_pypi_version()
-    if pkg.parse_version(__version__) < pkg.parse_version(latest):
+    if pkg.parse_version(__version__) < pkg.parse_version(latest):  # update is available
        LOGGER.info(f'New https://pypi.org/project/ultralytics/{latest} available 😃 '
                    f"Update with 'pip install -U ultralytics'")
+        return True
+    return False


 def check_font(font='Arial.ttf'):
--- a/ultralytics/yolo/utils/plotting.py
+++ b/ultralytics/yolo/utils/plotting.py
@ -9,7 +9,6 @@ import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import seaborn as sn
 import torch
 from PIL import Image, ImageDraw, ImageFont
 from PIL import __version__ as pil_version
@ -161,6 +160,8 @@ class Annotator:

@TryExcept()  # known issue https://github.com/ultralytics/yolov5/issues/5395
 def plot_labels(boxes, cls, names=(), save_dir=Path('')):
+    import seaborn as sn
+
    # plot dataset labels
    LOGGER.info(f"Plotting labels to {save_dir / 'labels.jpg'}... ")
    b = boxes.transpose()  # classes, boxes