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ultralytics 8.0.87 improved Pose models (#2202)

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Glenn Jocher 2023-04-24 16:04:40 +02:00 committed by GitHub
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14 changed files with 150 additions and 56 deletions
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24
.github/workflows/ci.yaml vendored
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@ -56,6 +56,14 @@ jobs:
hub.reset_model(model_id) hub.reset_model(model_id)
model = YOLO('https://hub.ultralytics.com/models/' + model_id) model = YOLO('https://hub.ultralytics.com/models/' + model_id)
model.train() 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: Benchmarks:
runs-on: ${{ matrix.os }} runs-on: ${{ matrix.os }}
@ -116,6 +124,14 @@ jobs:
run: | run: |
cat benchmarks.log cat benchmarks.log
echo "$(cat benchmarks.log)" >> $GITHUB_STEP_SUMMARY echo "$(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: Tests:
timeout-minutes: 60 timeout-minutes: 60
@ -193,3 +209,11 @@ jobs:
- name: Pytest tests - name: Pytest tests
shell: bash # for Windows compatibility shell: bash # for Windows compatibility
run: pytest tests 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 }}

8
.github/workflows/links.yml vendored
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@ -19,20 +19,20 @@ jobs:
- uses: actions/checkout@v3 - uses: actions/checkout@v3
- name: Test Markdown and HTML links - name: Test Markdown and HTML links
uses: lycheeverse/lychee-action@v1.6.1 uses: lycheeverse/lychee-action@v1.7.0
with: with:
fail: true fail: true
# accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter) # 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: env:
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}} GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
- name: Test Markdown, HTML, YAML, Python and Notebook links - name: Test Markdown, HTML, YAML, Python and Notebook links
if: github.event_name == 'workflow_dispatch' if: github.event_name == 'workflow_dispatch'
uses: lycheeverse/lychee-action@v1.6.1 uses: lycheeverse/lychee-action@v1.7.0
with: with:
fail: true fail: true
# accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter) # 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: env:
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}} GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

12
README.md
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@ -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) | | 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 | | [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 | 59.2 | 85.8 | 233.2 | 1.42 | 11.6 | 30.2 | | [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 | 63.6 | 88.8 | 456.3 | 2.00 | 26.4 | 81.0 | | [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 | 67.0 | 89.9 | 784.5 | 2.59 | 44.4 | 168.6 | | [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 | 68.9 | 90.4 | 1607.1 | 3.73 | 69.4 | 263.2 | | [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 | 71.5 | 91.3 | 4088.7 | 10.04 | 99.1 | 1066.4 | | [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) - **mAP<sup>val</sup>** values are for single-model single-scale on [COCO Keypoints val2017](http://cocodataset.org)
dataset. dataset.

12
README.zh-CN.md
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@ -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) | | 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 | | [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 | 59.2 | 85.8 | 233.2 | 1.42 | 11.6 | 30.2 | | [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 | 63.6 | 88.8 | 456.3 | 2.00 | 26.4 | 81.0 | | [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 | 67.0 | 89.9 | 784.5 | 2.59 | 44.4 | 168.6 | | [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 | 68.9 | 90.4 | 1607.1 | 3.73 | 69.4 | 263.2 | | [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 | 71.5 | 91.3 | 4088.7 | 10.04 | 99.1 | 1066.4 | | [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。 - **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 <br>通过 `yolo val pose data=coco-pose.yaml device=0` 复现

1
docs/modes/train.md
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@ -72,7 +72,6 @@ task.
| `seed` | `0` | random seed for reproducibility | | `seed` | `0` | random seed for reproducibility |
| `deterministic` | `True` | whether to enable deterministic mode | | `deterministic` | `True` | whether to enable deterministic mode |
| `single_cls` | `False` | train multi-class data as single-class | | `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 | | `rect` | `False` | rectangular training with each batch collated for minimum padding |
| `cos_lr` | `False` | use cosine learning rate scheduler | | `cos_lr` | `False` | use cosine learning rate scheduler |
| `close_mosaic` | `0` | (int) disable mosaic augmentation for final epochs | | `close_mosaic` | `0` | (int) disable mosaic augmentation for final epochs |

14
docs/tasks/pose.md
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@ -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. 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) | | 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 | | [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 | 59.2 | 85.8 | 233.2 | 1.42 | 11.6 | 30.2 | | [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 | 63.6 | 88.8 | 456.3 | 2.00 | 26.4 | 81.0 | | [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 | 67.0 | 89.9 | 784.5 | 2.59 | 44.4 | 168.6 | | [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 | 68.9 | 90.4 | 1607.1 | 3.73 | 69.4 | 263.2 | | [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 | 71.5 | 91.3 | 4088.7 | 10.04 | 99.1 | 1066.4 | | [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) - **mAP<sup>val</sup>** values are for single-model single-scale on [COCO Keypoints val2017](http://cocodataset.org)
dataset. dataset.

1
docs/usage/cfg.md
View File

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

15
mkdocs.yml
View File

@ -143,6 +143,21 @@ nav:
- Segment: tasks/segment.md - Segment: tasks/segment.md
- Classify: tasks/classify.md - Classify: tasks/classify.md
- Pose: tasks/pose.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: - Usage:
- CLI: usage/cli.md - CLI: usage/cli.md
- Python: usage/python.md - Python: usage/python.md

2
ultralytics/__init__.py
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = '8.0.86' __version__ = '8.0.87'
from ultralytics.hub import start from ultralytics.hub import start
from ultralytics.yolo.engine.model import YOLO from ultralytics.yolo.engine.model import YOLO

12
ultralytics/models/README.md
View File

@ -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) | | 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 | | [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 | 59.2 | 85.8 | 233.2 | 1.42 | 11.6 | 30.2 | | [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 | 63.6 | 88.8 | 456.3 | 2.00 | 26.4 | 81.0 | | [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 | 67.0 | 89.9 | 784.5 | 2.59 | 44.4 | 168.6 | | [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 | 68.9 | 90.4 | 1607.1 | 3.73 | 69.4 | 263.2 | | [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 | 71.5 | 91.3 | 4088.7 | 10.04 | 99.1 | 1066.4 | | [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> </details>

67
ultralytics/tracker/README.md
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@ -1,13 +1,15 @@
## Tracker # Tracker
### Trackers ## Supported Trackers
- [x] ByteTracker - [x] ByteTracker
- [x] BoT-SORT - [x] BoT-SORT
### Usage ## Usage
python interface: ### python interface:
You can use the Python interface to track objects using the YOLO model.
```python ```python
from ultralytics import YOLO from ultralytics import YOLO
@ -17,17 +19,68 @@ model.track(
source="video/streams", source="video/streams",
stream=True, stream=True,
tracker="botsort.yaml", # or 'bytetrack.yaml' 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 ```bash
yolo detect track source=... tracker=... yolo detect track source=... tracker=...
yolo segment track source=... tracker=... yolo segment track source=... tracker=...
yolo pose track source=... tracker=...
``` ```
By default, trackers will use the configuration in `ultralytics/tracker/cfg`. 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 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>

8
ultralytics/yolo/cfg/__init__.py
View File

@ -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 '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', CFG_INT_KEYS = ('epochs', 'patience', 'batch', 'workers', 'seed', 'close_mosaic', 'mask_ratio', 'max_det', 'vid_stride',
'line_thickness', 'workspace', 'nbs', 'save_period') 'line_thickness', 'workspace', 'nbs', 'save_period')
CFG_BOOL_KEYS = ('save', 'exist_ok', 'verbose', 'deterministic', 'single_cls', 'image_weights', 'rect', 'cos_lr', CFG_BOOL_KEYS = ('save', 'exist_ok', 'verbose', 'deterministic', 'single_cls', 'rect', 'cos_lr', 'overlap_mask', 'val',
'overlap_mask', 'val', 'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', 'save_txt', 'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', 'save_txt', 'save_conf', 'save_crop',
'save_conf', 'save_crop', 'show_labels', 'show_conf', 'visualize', 'augment', 'agnostic_nms', 'show_labels', 'show_conf', 'visualize', 'augment', 'agnostic_nms', 'retina_masks', 'boxes', 'keras',
'retina_masks', 'boxes', 'keras', 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'v5loader') 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'v5loader')
def cfg2dict(cfg): def cfg2dict(cfg):

29
ultralytics/yolo/data/build.py
View File

@ -7,7 +7,7 @@ from pathlib import Path
import numpy as np import numpy as np
import torch import torch
from PIL import Image 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, from ultralytics.yolo.data.dataloaders.stream_loaders import (LOADERS, LoadImages, LoadPilAndNumpy, LoadScreenshots,
LoadStreams, LoadTensor, SourceTypes, autocast_list) LoadStreams, LoadTensor, SourceTypes, autocast_list)
@ -38,6 +38,12 @@ class InfiniteDataLoader(dataloader.DataLoader):
for _ in range(len(self)): for _ in range(len(self)):
yield next(self.iterator) 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: 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 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 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) 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 = torch.Generator()
generator.manual_seed(6148914691236517205 + RANK) generator.manual_seed(6148914691236517205 + RANK)
return loader( return InfiniteDataLoader(dataset=dataset,
dataset=dataset, batch_size=batch,
batch_size=batch, shuffle=shuffle and sampler is None,
shuffle=shuffle and sampler is None, num_workers=nw,
num_workers=nw, sampler=sampler,
sampler=sampler, pin_memory=PIN_MEMORY,
pin_memory=PIN_MEMORY, collate_fn=getattr(dataset, 'collate_fn', None),
collate_fn=getattr(dataset, 'collate_fn', None), worker_init_fn=seed_worker,
worker_init_fn=seed_worker, generator=generator), dataset
persistent_workers=(nw > 0) and (loader == DataLoader), # persist workers if using default PyTorch DataLoader
generator=generator), dataset
# Build classification # Build classification

1
ultralytics/yolo/engine/trainer.py
View File

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