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ultralytics 8.0.141 create new SettingsManager (#3790)

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Glenn Jocher 2023-07-23 16:03:34 +02:00 • committed by GitHub
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docs/usage/cfg.md
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@ -13,19 +13,19 @@ YOLOv8 'yolo' CLI commands use the following syntax:
!!! example ""
=== "CLI"
```bash
yolo TASK MODE ARGS
```
=== "Python"
```python
from ultralytics import YOLO
# Load a YOLOv8 model from a pre-trained weights file
model = YOLO('yolov8n.pt')
# Run MODE mode using the custom arguments ARGS (guess TASK)
model.MODE(ARGS)
```
@ -45,9 +45,9 @@ Where:
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.
**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 |
@ -61,11 +61,11 @@ differ in the type of output they produce and the specific problem they are desi
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.
**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 |
@ -251,4 +251,4 @@ it easier to debug and optimize the training process.
| `name` | `'exp'` | experiment name. `exp` gets automatically incremented if not specified, i.e, `exp`, `exp2` ... |
| `exist_ok` | `False` | whether to overwrite existing experiment |
| `plots` | `False` | save plots during train/val |
| `save` | `False` | save train checkpoints and predict results |
| `save` | `False` | save train checkpoints and predict results |