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Add Export Arguments tables to all Export docs (#18952)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Francesco Mattioli <Francesco.mttl@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Lakshantha Dissanayake 2025-02-05 18:43:02 -08:00 • committed by GitHub
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docs/en/integrations/openvino.md
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@ -57,21 +57,20 @@ Export a YOLOv8n model to OpenVINO format and run inference with the exported mo
yolo predict model=yolov8n_openvino_model source='https://ultralytics.com/images/bus.jpg'
```
## Arguments
## Export Arguments
| Key | Value | Description |
| --------- | ------------ | ------------------------------------------------------------------------------------------- |
| `format` | `'openvino'` | format to export to |
| `imgsz` | `640` | image size as scalar or (h, w) list, i.e. (640, 480) |
| `half` | `False` | FP16 quantization |
| `int8` | `False` | INT8 quantization |
| `batch` | `1` | [batch size](https://www.ultralytics.com/glossary/batch-size) for inference |
| `dynamic` | `False` | allows dynamic input sizes |
| `data` | `coco8.yaml` | Path to the dataset configuration file (default: `coco8.yaml`), essential for quantization. |
| Argument | Type | Default | Description |
| --------- | ---------------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `format` | `str` | `openvino` | Target format for the exported model, defining compatibility with various deployment environments. |
| `imgsz` | `int` or `tuple` | `640` | Desired image size for the model input. Can be an integer for square images or a tuple `(height, width)` for specific dimensions. |
| `half` | `bool` | `False` | Enables FP16 (half-precision) quantization, reducing model size and potentially speeding up inference on supported hardware. |
| `int8` | `bool` | `False` | Activates INT8 quantization, further compressing the model and speeding up inference with minimal [accuracy](https://www.ultralytics.com/glossary/accuracy) loss, primarily for edge devices. |
| `dynamic` | `bool` | `False` | Allows dynamic input sizes, enhancing flexibility in handling varying image dimensions. |
| `nms` | `bool` | `False` | Adds Non-Maximum Suppression (NMS), essential for accurate and efficient detection post-processing. |
| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. |
| `data` | `str` | `coco8.yaml` | Path to the [dataset](https://docs.ultralytics.com/datasets) configuration file (default: `coco8.yaml`), essential for quantization. |
!!! note
When using `data` argument for quantization, please check [Dataset Guide](https://docs.ultralytics.com/datasets/detect) to learn more about the dataset format.
For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md).
## Benefits of OpenVINO