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Docs partial mdformat improvements (#7378)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2024-01-07 17:13:42 +01:00 • committed by GitHub
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docs/en/usage/cfg.md
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@ -51,10 +51,10 @@ Default `ARG` values are defined on this page from the `cfg/defaults.yaml` [file
YOLO models can be used for a variety of tasks, including detection, segmentation, classification and pose. These tasks differ in the type of output they produce and the specific problem they are designed to solve.
**Detect**: For identifying and localizing objects or regions of interest in an image or video.
**Segment**: For dividing an image or video into regions or pixels that correspond to different objects or classes.
**Classify**: For predicting the class label of an input image.
**Pose**: For identifying objects and estimating their keypoints in an image or video.
- **Detect**: For identifying and localizing objects or regions of interest in an image or video.
- **Segment**: For dividing an image or video into regions or pixels that correspond to different objects or classes.
- **Classify**: For predicting the class label of an input image.
- **Pose**: For identifying objects and estimating their keypoints in an image or video.
| Key | Value | Description |
|--------|------------|-------------------------------------------------|
@ -66,12 +66,12 @@ YOLO models can be used for a variety of tasks, including detection, segmentatio
YOLO models can be used in different modes depending on the specific problem you are trying to solve. These modes include:
**Train**: For training a YOLOv8 model on a custom dataset.
**Val**: For validating a YOLOv8 model after it has been trained.
**Predict**: For making predictions using a trained YOLOv8 model on new images or videos.
**Export**: For exporting a YOLOv8 model to a format that can be used for deployment.
**Track**: For tracking objects in real-time using a YOLOv8 model.
**Benchmark**: For benchmarking YOLOv8 exports (ONNX, TensorRT, etc.) speed and accuracy.
- **Train**: For training a YOLOv8 model on a custom dataset.
- **Val**: For validating a YOLOv8 model after it has been trained.
- **Predict**: For making predictions using a trained YOLOv8 model on new images or videos.
- **Export**: For exporting a YOLOv8 model to a format that can be used for deployment.
- **Track**: For tracking objects in real-time using a YOLOv8 model.
- **Benchmark**: For benchmarking YOLOv8 exports (ONNX, TensorRT, etc.) speed and accuracy.
| Key | Value | Description |
|--------|-----------|---------------------------------------------------------------|