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Standardize str formatting in docs (#19276)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Lakshantha Dissanayake 2025-02-17 02:27:47 -08:00 • committed by GitHub
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docs/en/integrations/tensorrt.md
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@ -109,18 +109,18 @@ Before diving into the usage instructions, be sure to check out the range of [YO
### Export Arguments
| Argument | Type | Default | Description |
| ----------- | ----------------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `format` | `str` | `engine` | 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. |
| `simplify` | `bool` | `True` | Simplifies the model graph with `onnxslim`, potentially improving performance and compatibility. |
| `workspace` | `float` or `None` | `None` | Sets the maximum workspace size in GiB for TensorRT optimizations, balancing memory usage and performance; use `None` for auto-allocation by TensorRT up to device maximum. |
| `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. |
| Argument | Type | Default | Description |
| ----------- | ----------------- | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `format` | `str` | `'engine'` | 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. |
| `simplify` | `bool` | `True` | Simplifies the model graph with `onnxslim`, potentially improving performance and compatibility. |
| `workspace` | `float` or `None` | `None` | Sets the maximum workspace size in GiB for TensorRT optimizations, balancing memory usage and performance; use `None` for auto-allocation by TensorRT up to device maximum. |
| `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. |
For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md).