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ultralytics 8.3.70 add data argument to Sony IMX500 export (#18852)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.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 2025-01-30 03:28:19 -08:00 • committed by GitHub
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docs/en/macros/export-args.md
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@ -13,3 +13,4 @@
| `nms` | `bool` | `False` | Adds Non-Maximum Suppression (NMS) to the CoreML export, 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. |
| `device` | `str` | `None` | Specifies the device for exporting: GPU (`device=0`), CPU (`device=cpu`), MPS for Apple silicon (`device=mps`) or DLA for NVIDIA Jetson (`device=dla:0` or `device=dla:1`). |
| `data` | `str` | `coco8.yaml` | Path to the dataset configuration file (default: `coco8.yaml`), essential for quantization. |

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docs/en/macros/export-table.md
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@ -1,18 +1,18 @@
| Format | `format` Argument | Model | Metadata | Arguments |
| ------------------------------------------------- | ----------------- | ----------------------------------------------- | -------- | --------------------------------------------------------------------------- |
| [PyTorch](https://pytorch.org/) | - | `{{ model_name or "yolo11n" }}.pt` | ✅ | - |
| [TorchScript](../integrations/torchscript.md) | `torchscript` | `{{ model_name or "yolo11n" }}.torchscript` | ✅ | `imgsz`, `optimize`, `nms`, `batch` |
| [ONNX](../integrations/onnx.md) | `onnx` | `{{ model_name or "yolo11n" }}.onnx` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `opset`, `nms`, `batch` |
| [OpenVINO](../integrations/openvino.md) | `openvino` | `{{ model_name or "yolo11n" }}_openvino_model/` | ✅ | `imgsz`, `half`, `dynamic`, `int8`, `nms`, `batch` |
| [TensorRT](../integrations/tensorrt.md) | `engine` | `{{ model_name or "yolo11n" }}.engine` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `workspace`, `int8`, `nms`, `batch` |
| [CoreML](../integrations/coreml.md) | `coreml` | `{{ model_name or "yolo11n" }}.mlpackage` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `{{ model_name or "yolo11n" }}_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `nms`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `{{ model_name or "yolo11n" }}.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `{{ model_name or "yolo11n" }}.tflite` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `{{ model_name or "yolo11n" }}_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `{{ model_name or "yolo11n" }}_web_model/` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `{{ model_name or "yolo11n" }}_paddle_model/` | ✅ | `imgsz`, `batch` |
| [MNN](../integrations/mnn.md) | `mnn` | `{{ model_name or "yolo11n" }}.mnn` | ✅ | `imgsz`, `batch`, `int8`, `half` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `{{ model_name or "yolo11n" }}_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |
| [IMX500](../integrations/sony-imx500.md) | `imx` | `{{ model_name or "yolov8n" }}_imx_model/` | ✅ | `imgsz`, `int8` |
| [RKNN](../integrations/rockchip-rknn.md) | `rknn` | `{{ model_name or "yolo11n" }}_rknn_model/` | ✅ | `imgsz`, `batch`, `name` |
| Format | `format` Argument | Model | Metadata | Arguments |
| ------------------------------------------------- | ----------------- | ----------------------------------------------- | -------- | ----------------------------------------------------------------------------------- |
| [PyTorch](https://pytorch.org/) | - | `{{ model_name or "yolo11n" }}.pt` | ✅ | - |
| [TorchScript](../integrations/torchscript.md) | `torchscript` | `{{ model_name or "yolo11n" }}.torchscript` | ✅ | `imgsz`, `optimize`, `nms`, `batch` |
| [ONNX](../integrations/onnx.md) | `onnx` | `{{ model_name or "yolo11n" }}.onnx` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `opset`, `nms`, `batch` |
| [OpenVINO](../integrations/openvino.md) | `openvino` | `{{ model_name or "yolo11n" }}_openvino_model/` | ✅ | `imgsz`, `half`, `dynamic`, `int8`, `nms`, `batch`, `data` |
| [TensorRT](../integrations/tensorrt.md) | `engine` | `{{ model_name or "yolo11n" }}.engine` | ✅ | `imgsz`, `half`, `dynamic`, `simplify`, `workspace`, `int8`, `nms`, `batch`, `data` |
| [CoreML](../integrations/coreml.md) | `coreml` | `{{ model_name or "yolo11n" }}.mlpackage` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [TF SavedModel](../integrations/tf-savedmodel.md) | `saved_model` | `{{ model_name or "yolo11n" }}_saved_model/` | ✅ | `imgsz`, `keras`, `int8`, `nms`, `batch` |
| [TF GraphDef](../integrations/tf-graphdef.md) | `pb` | `{{ model_name or "yolo11n" }}.pb` | ❌ | `imgsz`, `batch` |
| [TF Lite](../integrations/tflite.md) | `tflite` | `{{ model_name or "yolo11n" }}.tflite` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch`, `data` |
| [TF Edge TPU](../integrations/edge-tpu.md) | `edgetpu` | `{{ model_name or "yolo11n" }}_edgetpu.tflite` | ✅ | `imgsz` |
| [TF.js](../integrations/tfjs.md) | `tfjs` | `{{ model_name or "yolo11n" }}_web_model/` | ✅ | `imgsz`, `half`, `int8`, `nms`, `batch` |
| [PaddlePaddle](../integrations/paddlepaddle.md) | `paddle` | `{{ model_name or "yolo11n" }}_paddle_model/` | ✅ | `imgsz`, `batch` |
| [MNN](../integrations/mnn.md) | `mnn` | `{{ model_name or "yolo11n" }}.mnn` | ✅ | `imgsz`, `batch`, `int8`, `half` |
| [NCNN](../integrations/ncnn.md) | `ncnn` | `{{ model_name or "yolo11n" }}_ncnn_model/` | ✅ | `imgsz`, `half`, `batch` |
| [IMX500](../integrations/sony-imx500.md) | `imx` | `{{ model_name or "yolov8n" }}_imx_model/` | ✅ | `imgsz`, `int8`, `data` |
| [RKNN](../integrations/rockchip-rknn.md) | `rknn` | `{{ model_name or "yolo11n" }}_rknn_model/` | ✅ | `imgsz`, `batch`, `name` |