ultralytics 8.0.223 add YOLOv8-Ghost P2 and P6 variants (#6826)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com> Co-authored-by: Awsome <1579093407@qq.com>
2023-12-07 01:01:02 +01:00 · 2023-12-07 01:01:02 +01:00 · d74a5a9499
commit d74a5a9499
parent 742cbc1b4e
20 changed files with 153 additions and 16 deletions
--- a/docs/ar/index.md
+++ b/docs/ar/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics، YOLOv8، كشف الكائنات، تجزئة الصور
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics Code Coverage"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 Citation"></a>
  <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>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <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/docs/de/index.md
+++ b/docs/de/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, Objekterkennung, Bildsegmentierung, maschinelles
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics Code Coverage"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 Zitation"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Docker Ziehungen"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Auf Gradient ausführen"></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="In Colab öffnen"></a>
--- a/docs/en/guides/isolating-segmentation-objects.md
+++ b/docs/en/guides/isolating-segmentation-objects.md
@ -24,7 +24,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab
    from ultralytics import YOLO
    ```

-   ???+ tip "Ultralytics Install"
+    ???+ tip "Ultralytics Install"

        See the Ultralytics [Quickstart](../quickstart.md/#install-ultralytics) Installation section for a quick walkthrough on installing the required libraries.

@ -42,7 +42,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab
    result = model.predict()
    ```

-   ??? question "No Prediction Arguments?"
+    ??? question "No Prediction Arguments?"

        Without specifying a source, the example images from the library will be used:

@ -53,7 +53,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab

        This is helpful for rapid testing with the `predict()` method.

-   For additional information about Segmentation Models, visit the [Segment Task](../tasks/segment.md#models) page. To learn more about `predict()` method, see [Predict Mode](../modes/predict.md) section of the Documentation.
+    For additional information about Segmentation Models, visit the [Segment Task](../tasks/segment.md#models) page. To learn more about `predict()` method, see [Predict Mode](../modes/predict.md) section of the Documentation.

    ---

@ -75,7 +75,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab
    1. To learn more about working with detection results, see [Boxes Section for Predict Mode](../modes/predict.md#boxes).
    2. To learn more about `predict()` results see [Working with Results for Predict Mode](../modes/predict.md#working-with-results)

-   ??? info "For-Loop"
+    ??? info "For-Loop"

        A single image will only iterate the first loop once. A single image with only a single detection will iterate each loop _only_ once.

@ -83,7 +83,8 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab

 4. Start with generating a binary mask from the source image and then draw a filled contour onto the mask. This will allow the object to be isolated from the other parts of the image. An example from `bus.jpg` for one of the detected `person` class objects is shown on the right.

-   ![Binary Mask Image](https://github.com/ultralytics/ultralytics/assets/62214284/59bce684-fdda-4b17-8104-0b4b51149aca){ width="240", align="right" }
+    ![Binary Mask Image](https://github.com/ultralytics/ultralytics/assets/62214284/59bce684-fdda-4b17-8104-0b4b51149aca){ width="240", align="right" }
+
    ``` { .py .annotate }
    # Create binary mask
    b_mask = np.zeros(img.shape[:2], np.uint8)
@ -146,9 +147,9 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab

 5. Next the there are 2 options for how to move forward with the image from this point and a subsequent option for each.

-   ### Object Isolation Options
+    ### Object Isolation Options

-   !!! Example ""
+    !!! example ""

        === "Black Background Pixels"

@ -251,7 +252,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab

                    - Finally the image region for the bounding box is cropped using index slicing, where the bounds are set using the `[ymin:ymax, xmin:xmax]` coordinates of the detection bounding box.

-   ??? question "What if I want the cropped object **including** the background?"
+    ??? question "What if I want the cropped object **including** the background?"

        This is a built in feature for the Ultralytics library. See the `save_crop` argument for  [Predict Mode Inference Arguments](../modes/predict.md/#inference-arguments) for details.

@ -261,7 +262,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab

    - **NOTE:** this step is optional and can be skipped if not required for your specific use case.

-   ??? example "Example Final Step"
+    ??? example "Example Final Step"

        ```py
        # Save isolated object to file
--- a/docs/en/index.md
+++ b/docs/en/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, object detection, image segmentation, machine lea
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics Code Coverage"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 Citation"></a>
  <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>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <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/docs/en/models/yolov8.md
+++ b/docs/en/models/yolov8.md
@ -12,6 +12,17 @@ YOLOv8 is the latest iteration in the YOLO series of real-time object detectors,

 ![Ultralytics YOLOv8](https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/yolo-comparison-plots.png)

+<p align="center">
+  <br>
+  <iframe width="720" height="405" src="https://www.youtube.com/embed/Na0HvJ4hkk0"
+    title="YouTube video player" frameborder="0"
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
+    allowfullscreen>
+  </iframe>
+  <br>
+  <strong>Watch:</strong> Ultralytics YOLOv8 Model Overview
+</p>
+
 ## Key Features

 - **Advanced Backbone and Neck Architectures:** YOLOv8 employs state-of-the-art backbone and neck architectures, resulting in improved feature extraction and object detection performance.
--- a/docs/es/index.md
+++ b/docs/es/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, detección de objetos, segmentación de imágenes
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Cobertura de código de Ultralytics"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="Cita de YOLOv8"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Descargas de Docker"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Ejecutar en 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="Abrir en Colab"></a>
--- a/docs/fr/index.md
+++ b/docs/fr/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, détection d'objets, segmentation d'images, appre
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Couverture de code Ultralytics"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="Citation YOLOv8"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Téléchargements Docker"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Exécuter sur 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="Ouvrir dans Colab"></a>
--- a/docs/hi/index.md
+++ b/docs/hi/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, वस्तु पता लगाना, छव
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics Code Coverage"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 Citation"></a>
  <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>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <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/docs/ja/index.md
+++ b/docs/ja/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, オブジェクト検出, 画像セグメンテ
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics コードカバレッジ"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 引用情報"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Docker プル"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Gradient上で実行"></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="Colabで開く"></a>
--- a/docs/ko/index.md
+++ b/docs/ko/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, 객체 탐지, 이미지 분할, 기계 학습,
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics 코드 커버리지"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 인용"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Docker 당기기"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <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/docs/pt/index.md
+++ b/docs/pt/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, detecção de objetos, segmentação de imagens,
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Cobertura de Código da Ultralytics"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="Citação do YOLOv8"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Contagem de Pulls no Docker"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Executar no 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="Abrir no Colab"></a>
--- a/docs/ru/index.md
+++ b/docs/ru/index.md
@ -28,6 +28,7 @@ keywords: Ultralytics, YOLOv8, обнаружение объектов, сегм
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Покрытие кода Ultralytics"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="Цитирование YOLOv8"></a>
  <a href="https://hub.docker.com/r/ultralytics/ultralytics"><img src="https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker" alt="Загрузки Docker"></a>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <a href="https://console.paperspace.com/github/ultralytics/ultralytics"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Запустить на 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="Открыть в Colab"></a>
--- a/docs/zh/index.md
+++ b/docs/zh/index.md
@ -30,6 +30,7 @@ keywords: Ultralytics, YOLOv8, 目标检测, 图像分割, 机器学习, 深度
  <a href="https://codecov.io/github/ultralytics/ultralytics"><img src="https://codecov.io/github/ultralytics/ultralytics/branch/main/graph/badge.svg?token=HHW7IIVFVY" alt="Ultralytics Code Coverage"></a>
  <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv8 Citation"></a>
  <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>
+  <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a>
  <br>
  <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>