docs/macros/export-args.md
| Argument | Type | Default | Description |
|---|---|---|---|
format | str | 'torchscript' | Target format for the exported model, such as 'onnx', 'torchscript', 'engine' (TensorRT), or others. Each format enables compatibility with different deployment environments. |
imgsz | int or tuple | 640 | Desired image size for the model input. Can be an integer for square images (e.g., 640 for 640×640) or a tuple (height, width) for specific dimensions. |
keras | bool | False | Enables export to Keras format for TensorFlow SavedModel, providing compatibility with TensorFlow serving and APIs. |
optimize | bool | False | Applies optimization for mobile devices when exporting to TorchScript, potentially reducing model size and improving inference performance. Not compatible with NCNN format or CUDA devices. For DEEPX, enables a higher compiler optimization which reduces inference latency and increases compilation time. |
quantize | int or str | None | Quantization precision: 16 (FP16, reduces model size and can speed up inference on supported hardware) or 8 (INT8/PTQ, further compresses the model with minimal accuracy loss, primarily for edge devices; needs calibration data/fraction); 32/unset is FP32. Export formats that support mixed weight/activation precision also accept the 'w8a8'/'w16a16'/'w8a16' notation. Replaces the deprecated half/int8 flags (half=True → 16, int8=True → 8, still accepted with a deprecation warning). Only precisions supported by the target format are allowed (see below). |
dynamic | bool | False | Allows dynamic input sizes for TorchScript, ONNX, OpenVINO, TensorRT, and CoreML exports, enhancing flexibility in handling varying image dimensions. |
simplify | bool | True | Simplifies the model graph for ONNX exports with onnxslim, potentially improving performance and compatibility with inference engines. |
opset | int | None | Specifies the ONNX opset version for compatibility with different ONNX parsers and runtimes. If not set, uses the latest supported version. |
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) to the exported model when supported (see Export Formats), improving detection post-processing efficiency. Not available for end2end models. |
batch | int | 1 | Specifies export model batch inference size or the maximum number of images the exported model will process concurrently in predict mode. For Edge TPU exports, this is automatically set to 1. |
device | str | None | Specifies the device for exporting: GPU (device=0), CPU (device=cpu), MPS for Apple silicon (device=mps), Huawei Ascend NPU (device=npu or device=npu:0), or DLA for NVIDIA Jetson (device=dla:0 or device=dla:1). TensorRT exports automatically use GPU, but TensorRT 11.0 does not support DLA. |
data | str | None | Path to the dataset configuration file, essential for INT8 quantization calibration. If not specified with INT8 enabled, Ultralytics selects a task-specific calibration dataset where required, or falls back to the default dataset for the model task. |
fraction | float | 1.0 | Specifies the fraction of the dataset to use for INT8 quantization calibration. Allows for calibrating on a subset of the full dataset, useful for experiments or when resources are limited. If not specified with INT8 enabled, the full dataset will be used. |
end2end | bool | None | Overrides the end-to-end mode in YOLO models that support NMS-free inference (YOLO26, YOLOv10). Setting it to False lets you export these models to be compatible with the traditional NMS-based postprocessing pipeline. See the End-to-End Detection guide for details. |