`ultralytics 8.0.87` improved Pose models (#2202)

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Kirolos Atef <keroatef295@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

.github/workflows/ci.yaml

@@ -56,6 +56,14 @@ jobs:
           hub.reset_model(model_id)
           model = YOLO('https://hub.ultralytics.com/models/' + model_id)
           model.train()
+      - name: Notify on failure
+        if: failure() && github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push')
+        uses: slackapi/slack-github-action@v1.23.0
+        with:
+          payload: |
+            {"text": "<!channel> GitHub Actions error for ${{ github.workflow }} ❌\n\n\n*Repository:* https://github.com/${{ github.repository }}\n*Action:* https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}\n*Author:* ${{ github.actor }}\n*Event:* ${{ github.event_name }}\n*Job Status:* ${{ job.status }}\n"}
+        env:
+          SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL_HUBWEB }}
 
   Benchmarks:
     runs-on: ${{ matrix.os }}
@@ -116,6 +124,14 @@ jobs:
         run: |
           cat benchmarks.log
           echo "$(cat benchmarks.log)" >> $GITHUB_STEP_SUMMARY
+      - name: Notify on failure
+        if: failure() && github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push')
+        uses: slackapi/slack-github-action@v1.23.0
+        with:
+          payload: |
+            {"text": "<!channel> GitHub Actions error for ${{ github.workflow }} ❌\n\n\n*Repository:* https://github.com/${{ github.repository }}\n*Action:* https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}\n*Author:* ${{ github.actor }}\n*Event:* ${{ github.event_name }}\n*Job Status:* ${{ job.status }}\n"}
+        env:
+          SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL_YOLO }}
 
   Tests:
     timeout-minutes: 60
@@ -193,3 +209,11 @@ jobs:
       - name: Pytest tests
         shell: bash  # for Windows compatibility
         run: pytest tests
+      - name: Notify on failure
+        if: failure() && github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push')
+        uses: slackapi/slack-github-action@v1.23.0
+        with:
+          payload: |
+            {"text": "<!channel> GitHub Actions error for ${{ github.workflow }} ❌\n\n\n*Repository:* https://github.com/${{ github.repository }}\n*Action:* https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}\n*Author:* ${{ github.actor }}\n*Event:* ${{ github.event_name }}\n*Job Status:* ${{ job.status }}\n"}
+        env:
+          SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL_YOLO }}

.github/workflows/links.yml

@@ -19,20 +19,20 @@ jobs:
       - uses: actions/checkout@v3
 
       - name: Test Markdown and HTML links
-        uses: lycheeverse/lychee-action@v1.6.1
+        uses: lycheeverse/lychee-action@v1.7.0
         with:
           fail: true
           # accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter)
-          args: --accept 429,999 --exclude-loopback --exclude twitter.com --exclude-mail './**/*.md' './**/*.html'
+          args: --accept 429,999 --exclude-loopback --exclude twitter.com --exclude-path '**/ci.yaml' --exclude-mail './**/*.md' './**/*.html'
         env:
           GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
 
       - name: Test Markdown, HTML, YAML, Python and Notebook links
         if: github.event_name == 'workflow_dispatch'
-        uses: lycheeverse/lychee-action@v1.6.1
+        uses: lycheeverse/lychee-action@v1.7.0
         with:
           fail: true
           # accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter)
-          args: --accept 429,999 --exclude-loopback --exclude twitter.com,url.com --exclude-mail './**/*.md' './**/*.html' './**/*.yml' './**/*.yaml' './**/*.py' './**/*.ipynb'
+          args: --accept 429,999 --exclude-loopback --exclude twitter.com,url.com --exclude-path '**/ci.yaml' --exclude-mail './**/*.md' './**/*.html' './**/*.yml' './**/*.yaml' './**/*.py' './**/*.ipynb'
         env:
           GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

README.md

@@ -169,12 +169,12 @@ See [Pose Docs](https://docs.ultralytics.com/tasks/pose) for usage examples with
 
 | Model                                                                                                | size<br><sup>(pixels) | mAP<sup>pose<br>50-95 | mAP<sup>pose<br>50 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
 | ---------------------------------------------------------------------------------------------------- | --------------------- | --------------------- | ------------------ | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 49.7                  | 79.7               | 131.8                          | 1.18                                | 3.3                | 9.2               |
-| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 59.2                  | 85.8               | 233.2                          | 1.42                                | 11.6               | 30.2              |
-| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 63.6                  | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
-| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.0                  | 89.9               | 784.5                          | 2.59                                | 44.4               | 168.6             |
-| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 68.9                  | 90.4               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
-| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.5                  | 91.3               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
+| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 50.4                  | 80.1               | 131.8                          | 1.18                                | 3.3                | 9.2               |
+| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 60.0                  | 86.2               | 233.2                          | 1.42                                | 11.6               | 30.2              |
+| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 65.0                  | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
+| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.6                  | 90.0               | 784.5                          | 2.59                                | 44.4               | 168.6             |
+| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 69.2                  | 90.2               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
+| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.6                  | 91.2               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
 
 - **mAP<sup>val</sup>** values are for single-model single-scale on [COCO Keypoints val2017](http://cocodataset.org)
   dataset.

README.zh-CN.md

@@ -169,12 +169,12 @@ success = model.export(format="onnx")  # 将模型导出为 ONNX 格式
 
 | 模型                                                                                                   | 尺寸<br><sup>(像素) | mAP<sup>pose<br>50-95 | mAP<sup>pose<br>50 | 速度<br><sup>CPU ONNX<br>(ms) | 速度<br><sup>A100 TensorRT<br>(ms) | 参数<br><sup>(M) | FLOPs<br><sup>(B) |
 | ---------------------------------------------------------------------------------------------------- | --------------- | --------------------- | ------------------ | --------------------------- | -------------------------------- | -------------- | ----------------- |
-| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640             | 49.7                  | 79.7               | 131.8                       | 1.18                             | 3.3            | 9.2               |
-| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640             | 59.2                  | 85.8               | 233.2                       | 1.42                             | 11.6           | 30.2              |
-| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640             | 63.6                  | 88.8               | 456.3                       | 2.00                             | 26.4           | 81.0              |
-| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640             | 67.0                  | 89.9               | 784.5                       | 2.59                             | 44.4           | 168.6             |
-| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640             | 68.9                  | 90.4               | 1607.1                      | 3.73                             | 69.4           | 263.2             |
-| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280            | 71.5                  | 91.3               | 4088.7                      | 10.04                            | 99.1           | 1066.4            |
+| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640             | 50.4                  | 80.1               | 131.8                       | 1.18                             | 3.3            | 9.2               |
+| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640             | 60.0                  | 86.2               | 233.2                       | 1.42                             | 11.6           | 30.2              |
+| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640             | 65.0                  | 88.8               | 456.3                       | 2.00                             | 26.4           | 81.0              |
+| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640             | 67.6                  | 90.0               | 784.5                       | 2.59                             | 44.4           | 168.6             |
+| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640             | 69.2                  | 90.2               | 1607.1                      | 3.73                             | 69.4           | 263.2             |
+| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280            | 71.6                  | 91.2               | 4088.7                      | 10.04                            | 99.1           | 1066.4            |
 
 - **mAP<sup>val</sup>** 值是基于单模型单尺度在 [COCO Keypoints val2017](http://cocodataset.org) 数据集上的结果。
   <br>通过 `yolo val pose data=coco-pose.yaml device=0` 复现

docs/modes/train.md

@@ -72,7 +72,6 @@ task.
 | `seed`            | `0`      | random seed for reproducibility                                             |
 | `deterministic`   | `True`   | whether to enable deterministic mode                                        |
 | `single_cls`      | `False`  | train multi-class data as single-class                                      |
-| `image_weights`   | `False`  | use weighted image selection for training                                   |
 | `rect`            | `False`  | rectangular training with each batch collated for minimum padding           |
 | `cos_lr`          | `False`  | use cosine learning rate scheduler                                          |
 | `close_mosaic`    | `0`      | (int) disable mosaic augmentation for final epochs                          |

docs/tasks/pose.md

@@ -24,13 +24,13 @@ the [ImageNet](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/
 Ultralytics [release](https://github.com/ultralytics/assets/releases) on first use.
 
 | Model                                                                                                | size<br><sup>(pixels) | mAP<sup>pose<br>50-95 | mAP<sup>pose<br>50 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
-| ---------------------------------------------------------------------------------------------------- | --------------------- | -------------------- | ------------------ | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 49.7                 | 79.7               | 131.8                          | 1.18                                | 3.3                | 9.2               |
-| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 59.2                 | 85.8               | 233.2                          | 1.42                                | 11.6               | 30.2              |
-| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 63.6                 | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
-| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.0                 | 89.9               | 784.5                          | 2.59                                | 44.4               | 168.6             |
-| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 68.9                 | 90.4               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
-| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.5                 | 91.3               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
+| ---------------------------------------------------------------------------------------------------- | --------------------- |-----------------------|--------------------| ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
+| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 50.4                  | 80.1               | 131.8                          | 1.18                                | 3.3                | 9.2               |
+| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 60.0                  | 86.2               | 233.2                          | 1.42                                | 11.6               | 30.2              |
+| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 65.0                  | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
+| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.6                  | 90.0               | 784.5                          | 2.59                                | 44.4               | 168.6             |
+| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 69.2                  | 90.2               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
+| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.6                  | 91.2               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
 
 - **mAP<sup>val</sup>** values are for single-model single-scale on [COCO Keypoints val2017](http://cocodataset.org)
   dataset.

docs/usage/cfg.md

@@ -94,7 +94,6 @@ The training settings for YOLO models encompass various hyperparameters and conf
 | `seed`            | `0`      | random seed for reproducibility                                             |
 | `deterministic`   | `True`   | whether to enable deterministic mode                                        |
 | `single_cls`      | `False`  | train multi-class data as single-class                                      |
-| `image_weights`   | `False`  | use weighted image selection for training                                   |
 | `rect`            | `False`  | rectangular training with each batch collated for minimum padding           |
 | `cos_lr`          | `False`  | use cosine learning rate scheduler                                          |
 | `close_mosaic`    | `0`      | (int) disable mosaic augmentation for final epochs                          |

mkdocs.yml

@@ -143,6 +143,21 @@ nav:
           - Segment: tasks/segment.md
           - Classify: tasks/classify.md
           - Pose: tasks/pose.md
+  - Quickstart: quickstart.md
+  - Modes:
+      - modes/index.md
+      - Train: modes/train.md
+      - Val: modes/val.md
+      - Predict: modes/predict.md
+      - Export: modes/export.md
+      - Track: modes/track.md
+      - Benchmark: modes/benchmark.md
+  - Tasks:
+      - tasks/index.md
+      - Detect: tasks/detect.md
+      - Segment: tasks/segment.md
+      - Classify: tasks/classify.md
+      - Pose: tasks/pose.md
   - Usage:
       - CLI: usage/cli.md
       - Python: usage/python.md

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.86'
+__version__ = '8.0.87'
 
 from ultralytics.hub import start
 from ultralytics.yolo.engine.model import YOLO

ultralytics/models/README.md

@@ -89,12 +89,12 @@ Available Models:
 
 | Model                                                                                                | size<br><sup>(pixels) | mAP<sup>pose<br>50-95 | mAP<sup>pose<br>50 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
 | ---------------------------------------------------------------------------------------------------- | --------------------- | --------------------- | ------------------ | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 49.7                  | 79.7               | 131.8                          | 1.18                                | 3.3                | 9.2               |
-| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 59.2                  | 85.8               | 233.2                          | 1.42                                | 11.6               | 30.2              |
-| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 63.6                  | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
-| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.0                  | 89.9               | 784.5                          | 2.59                                | 44.4               | 168.6             |
-| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 68.9                  | 90.4               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
-| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.5                  | 91.3               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
+| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 50.4                  | 80.1               | 131.8                          | 1.18                                | 3.3                | 9.2               |
+| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 60.0                  | 86.2               | 233.2                          | 1.42                                | 11.6               | 30.2              |
+| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 65.0                  | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
+| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.6                  | 90.0               | 784.5                          | 2.59                                | 44.4               | 168.6             |
+| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 69.2                  | 90.2               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
+| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.6                  | 91.2               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
 
 </details>
 

ultralytics/tracker/README.md

@@ -1,13 +1,15 @@
-## Tracker
+# Tracker
 
-### Trackers
+## Supported Trackers
 
 - [x] ByteTracker
 - [x] BoT-SORT
 
-### Usage
+## Usage
 
-python interface:
+### python interface:
+
+You can use the Python interface to track objects using the YOLO model.
 
 ```python
 from ultralytics import YOLO
@@ -17,17 +19,68 @@ model.track(
     source="video/streams",
     stream=True,
     tracker="botsort.yaml",  # or 'bytetrack.yaml'
-    ...,
+    show=True,
 )
 ```
 
-cli:
+You can get the IDs of the tracked objects using the following code:
+
+```python
+from ultralytics import YOLO
+
+model = YOLO("yolov8n.pt")
+
+for result in model.track(source="video.mp4"):
+    print(
+        result.boxes.id.cpu().numpy().astype(int)
+    )  # this will print the IDs of the tracked objects in the frame
+```
+
+If you want to use the tracker with a folder of images or when you loop on the video frames, you should use the `persist` parameter to tell the model that these frames are related to each other so the IDs will be fixed for the same objects. Otherwise, the IDs will be different in each frame because in each loop, the model creates a new object for tracking, but the `persist` parameter makes it use the same object for tracking.
+
+```python
+import cv2
+from ultralytics import YOLO
+
+cap = cv2.VideoCapture("video.mp4")
+model = YOLO("yolov8n.pt")
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        break
+    results = model.track(frame, persist=True)
+    boxes = results[0].boxes.xyxy.cpu().numpy().astype(int)
+    ids = results[0].boxes.id.cpu().numpy().astype(int)
+    for box, id in zip(boxes, ids):
+        cv2.rectangle(frame, (box[0], box[1]), (box[2], box[3]), (0, 255, 0), 2)
+        cv2.putText(
+            frame,
+            f"Id {id}",
+            (box[0], box[1]),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            1,
+            (0, 0, 255),
+            2,
+        )
+    cv2.imshow("frame", frame)
+    if cv2.waitKey(1) & 0xFF == ord("q"):
+        break
+```
+
+## Change tracker parameters
+
+You can change the tracker parameters by eding the `tracker.yaml` file which is located in the ultralytics/tracker/cfg folder.
+
+## Command Line Interface (CLI)
+
+You can also use the command line interface to track objects using the YOLO model.
 
 ```bash
 yolo detect track source=... tracker=...
 yolo segment track source=... tracker=...
+yolo pose track source=... tracker=...
 ```
 
 By default, trackers will use the configuration in `ultralytics/tracker/cfg`.
 We also support using a modified tracker config file. Please refer to the tracker config files
-in `ultralytics/tracker/cfg`.
+in `ultralytics/tracker/cfg`.<br>

ultralytics/yolo/cfg/__init__.py

@@ -69,10 +69,10 @@ CFG_FRACTION_KEYS = ('dropout', 'iou', 'lr0', 'lrf', 'momentum', 'weight_decay',
                      'fliplr', 'mosaic', 'mixup', 'copy_paste', 'conf', 'iou')  # fractional floats limited to 0.0 - 1.0
 CFG_INT_KEYS = ('epochs', 'patience', 'batch', 'workers', 'seed', 'close_mosaic', 'mask_ratio', 'max_det', 'vid_stride',
                 'line_thickness', 'workspace', 'nbs', 'save_period')
-CFG_BOOL_KEYS = ('save', 'exist_ok', 'verbose', 'deterministic', 'single_cls', 'image_weights', 'rect', 'cos_lr',
-                 'overlap_mask', 'val', 'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', 'save_txt',
-                 'save_conf', 'save_crop', 'show_labels', 'show_conf', 'visualize', 'augment', 'agnostic_nms',
-                 'retina_masks', 'boxes', 'keras', 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'v5loader')
+CFG_BOOL_KEYS = ('save', 'exist_ok', 'verbose', 'deterministic', 'single_cls', 'rect', 'cos_lr', 'overlap_mask', 'val',
+                 'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', 'save_txt', 'save_conf', 'save_crop',
+                 'show_labels', 'show_conf', 'visualize', 'augment', 'agnostic_nms', 'retina_masks', 'boxes', 'keras',
+                 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'v5loader')
 
 
 def cfg2dict(cfg):

ultralytics/yolo/data/build.py

@@ -7,7 +7,7 @@ from pathlib import Path
 import numpy as np
 import torch
 from PIL import Image
-from torch.utils.data import DataLoader, dataloader, distributed
+from torch.utils.data import dataloader, distributed
 
 from ultralytics.yolo.data.dataloaders.stream_loaders import (LOADERS, LoadImages, LoadPilAndNumpy, LoadScreenshots,
                                                               LoadStreams, LoadTensor, SourceTypes, autocast_list)
@@ -38,6 +38,12 @@ class InfiniteDataLoader(dataloader.DataLoader):
         for _ in range(len(self)):
             yield next(self.iterator)
 
+    def reset(self):
+        """Reset iterator.
+        This is useful when we want to modify settings of dataset while training.
+        """
+        self.iterator = self._get_iterator()
+
 
 class _RepeatSampler:
     """
@@ -94,20 +100,17 @@ def build_dataloader(cfg, batch, img_path, data_info, stride=32, rect=False, ran
     workers = cfg.workers if mode == 'train' else cfg.workers * 2
     nw = min([os.cpu_count() // max(nd, 1), batch if batch > 1 else 0, workers])  # number of workers
     sampler = None if rank == -1 else distributed.DistributedSampler(dataset, shuffle=shuffle)
-    loader = DataLoader if cfg.image_weights or cfg.close_mosaic else InfiniteDataLoader  # allow attribute updates
     generator = torch.Generator()
     generator.manual_seed(6148914691236517205 + RANK)
-    return loader(
-        dataset=dataset,
-        batch_size=batch,
-        shuffle=shuffle and sampler is None,
-        num_workers=nw,
-        sampler=sampler,
-        pin_memory=PIN_MEMORY,
-        collate_fn=getattr(dataset, 'collate_fn', None),
-        worker_init_fn=seed_worker,
-        persistent_workers=(nw > 0) and (loader == DataLoader),  # persist workers if using default PyTorch DataLoader
-        generator=generator), dataset
+    return InfiniteDataLoader(dataset=dataset,
+                              batch_size=batch,
+                              shuffle=shuffle and sampler is None,
+                              num_workers=nw,
+                              sampler=sampler,
+                              pin_memory=PIN_MEMORY,
+                              collate_fn=getattr(dataset, 'collate_fn', None),
+                              worker_init_fn=seed_worker,
+                              generator=generator), dataset
 
 
 # Build classification

ultralytics/yolo/engine/trainer.py

@@ -296,6 +296,7 @@ class BaseTrainer:
                     self.train_loader.dataset.mosaic = False
                 if hasattr(self.train_loader.dataset, 'close_mosaic'):
                     self.train_loader.dataset.close_mosaic(hyp=self.args)
+                self.train_loader.reset()
 
             if RANK in (-1, 0):
                 LOGGER.info(self.progress_string())