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ultralytics 8.0.196 instance-mean Segment loss (#5285)

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Co-authored-by: Andy <39454881+yermandy@users.noreply.github.com>
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docs/usage/cli.md
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@ -6,8 +6,7 @@ keywords: Ultralytics, YOLO, CLI, train, validation, prediction, command line in
# Command Line Interface Usage
The YOLO command line interface (CLI) allows for simple single-line commands without the need for a Python environment.
CLI requires no customization or Python code. You can simply run all tasks from the terminal with the `yolo` command.
The YOLO command line interface (CLI) allows for simple single-line commands without the need for a Python environment. CLI requires no customization or Python code. You can simply run all tasks from the terminal with the `yolo` command.
!!! example
@ -65,11 +64,9 @@ CLI requires no customization or Python code. You can simply run all tasks from
Where:
- `TASK` (optional) is one of `[detect, segment, classify]`. If it is not passed explicitly YOLOv8 will try to guess
the `TASK` from the model type.
- `TASK` (optional) is one of `[detect, segment, classify]`. If it is not passed explicitly YOLOv8 will try to guess the `TASK` from the model type.
- `MODE` (required) is one of `[train, val, predict, export, track]`
- `ARGS` (optional) are any number of custom `arg=value` pairs like `imgsz=320` that override defaults.
For a full list of available `ARGS` see the [Configuration](cfg.md) page and `defaults.yaml`
- `ARGS` (optional) are any number of custom `arg=value` pairs like `imgsz=320` that override defaults. For a full list of available `ARGS` see the [Configuration](cfg.md) page and `defaults.yaml`
GitHub [source](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/default.yaml).
!!! warning "Warning"
@ -82,8 +79,7 @@ Where:
## Train
Train YOLOv8n on the COCO128 dataset for 100 epochs at image size 640. For a full list of available arguments see
the [Configuration](cfg.md) page.
Train YOLOv8n on the COCO128 dataset for 100 epochs at image size 640. For a full list of available arguments see the [Configuration](cfg.md) page.
!!! example "Example"
@ -103,8 +99,7 @@ the [Configuration](cfg.md) page.
## Val
Validate trained YOLOv8n model accuracy on the COCO128 dataset. No argument need to passed as the `model` retains it's
training `data` and arguments as model attributes.
Validate trained YOLOv8n model accuracy on the COCO128 dataset. No argument need to passed as the `model` retains it's training `data` and arguments as model attributes.
!!! example "Example"
@ -162,8 +157,7 @@ Export a YOLOv8n model to a different format like ONNX, CoreML, etc.
yolo export model=path/to/best.pt format=onnx
```
Available YOLOv8 export formats are in the table below. You can export to any format using the `format` argument,
i.e. `format='onnx'` or `format='engine'`.
Available YOLOv8 export formats are in the table below. You can export to any format using the `format` argument, i.e. `format='onnx'` or `format='engine'`.
| Format | `format` Argument | Model | Metadata | Arguments |
|--------------------------------------------------------------------|-------------------|---------------------------|----------|-----------------------------------------------------|
@ -207,13 +201,11 @@ Default arguments can be overridden by simply passing them as arguments in the C
## Overriding default config file
You can override the `default.yaml` config file entirely by passing a new file with the `cfg` arguments,
i.e. `cfg=custom.yaml`.
You can override the `default.yaml` config file entirely by passing a new file with the `cfg` arguments, i.e. `cfg=custom.yaml`.
To do this first create a copy of `default.yaml` in your current working dir with the `yolo copy-cfg` command.
This will create `default_copy.yaml`, which you can then pass as `cfg=default_copy.yaml` along with any additional args,
like `imgsz=320` in this example:
This will create `default_copy.yaml`, which you can then pass as `cfg=default_copy.yaml` along with any additional args, like `imgsz=320` in this example:
!!! example ""