From 2cad1c597b301b29e53d8a5ebab21d40700ca738 Mon Sep 17 00:00:00 2001 From: Lakshantha Dissanayake Date: Mon, 17 Feb 2025 02:27:47 -0800 Subject: [PATCH] Standardize `str` formatting in docs (#19276) Co-authored-by: UltralyticsAssistant --- docs/en/guides/analytics.md | 12 ++++---- docs/en/integrations/coreml.md | 16 +++++------ docs/en/integrations/edge-tpu.md | 8 +++--- docs/en/integrations/mnn.md | 2 +- docs/en/integrations/ncnn.md | 12 ++++---- docs/en/integrations/onnx.md | 20 +++++++------- docs/en/integrations/openvino.md | 20 +++++++------- docs/en/integrations/paddlepaddle.md | 10 +++---- docs/en/integrations/rockchip-rknn.md | 12 ++++---- docs/en/integrations/sony-imx500.md | 12 ++++---- docs/en/integrations/tensorrt.md | 24 ++++++++-------- docs/en/integrations/tf-graphdef.md | 2 +- docs/en/integrations/tf-savedmodel.md | 16 +++++------ docs/en/integrations/tfjs.md | 16 +++++------ docs/en/integrations/tflite.md | 18 ++++++------ docs/en/integrations/torchscript.md | 14 +++++----- docs/en/macros/augmentation-args.md | 40 +++++++++++++-------------- docs/en/macros/export-args.md | 2 +- docs/en/macros/sam-auto-annotate.md | 6 ++-- docs/en/macros/solutions-args.md | 2 +- docs/en/macros/track-args.md | 18 ++++++------ docs/en/macros/validation-args.md | 2 +- 22 files changed, 142 insertions(+), 142 deletions(-) diff --git a/docs/en/guides/analytics.md b/docs/en/guides/analytics.md index cd7fc40d..12b5fe8e 100644 --- a/docs/en/guides/analytics.md +++ b/docs/en/guides/analytics.md @@ -100,12 +100,12 @@ This guide provides a comprehensive overview of three fundamental types of [data Here's a table with the `Analytics` arguments: -| Name | Type | Default | Description | -| ---------------- | ------ | ------- | ---------------------------------------------------- | -| `analytics_type` | `str` | `line` | Type of graph i.e "line", "bar", "area", "pie" | -| `model` | `str` | `None` | Path to Ultralytics YOLO Model File | -| `line_width` | `int` | `2` | Line thickness for bounding boxes. | -| `show` | `bool` | `False` | Flag to control whether to display the video stream. | +| Name | Type | Default | Description | +| ---------------- | ------ | -------- | ---------------------------------------------------- | +| `analytics_type` | `str` | `'line'` | Type of graph i.e "line", "bar", "area", "pie" | +| `model` | `str` | `None` | Path to Ultralytics YOLO Model File | +| `line_width` | `int` | `2` | Line thickness for bounding boxes. | +| `show` | `bool` | `False` | Flag to control whether to display the video stream. | ### Arguments `model.track` diff --git a/docs/en/integrations/coreml.md b/docs/en/integrations/coreml.md index 284d27f1..d0845fa7 100644 --- a/docs/en/integrations/coreml.md +++ b/docs/en/integrations/coreml.md @@ -107,14 +107,14 @@ Before diving into the usage instructions, be sure to check out the range of [YO ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `coreml` | 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. | -| `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. | +| Argument | Type | Default | Description | +| -------- | ---------------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'coreml'` | 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. | +| `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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/edge-tpu.md b/docs/en/integrations/edge-tpu.md index eabb093a..b5a6e8b8 100644 --- a/docs/en/integrations/edge-tpu.md +++ b/docs/en/integrations/edge-tpu.md @@ -97,10 +97,10 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | --------- | --------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `edgetpu` | 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. | +| Argument | Type | Default | Description | +| -------- | ---------------- | ----------- | --------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'edgetpu'` | 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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/mnn.md b/docs/en/integrations/mnn.md index 7c2aeaf9..7f00c8df 100644 --- a/docs/en/integrations/mnn.md +++ b/docs/en/integrations/mnn.md @@ -70,7 +70,7 @@ Before diving into the usage instructions, it's important to note that while all | Argument | Type | Default | Description | | -------- | ---------------- | ------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `mnn` | Target format for the exported model, defining compatibility with various deployment environments. | +| `format` | `str` | `'mnn'` | 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. | diff --git a/docs/en/integrations/ncnn.md b/docs/en/integrations/ncnn.md index bba42562..366999c8 100644 --- a/docs/en/integrations/ncnn.md +++ b/docs/en/integrations/ncnn.md @@ -99,12 +99,12 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | ------- | --------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `ncnn` | 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. | -| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | +| Argument | Type | Default | Description | +| -------- | ---------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'ncnn'` | 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. | +| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/onnx.md b/docs/en/integrations/onnx.md index 3f5eff4c..465ad6fd 100644 --- a/docs/en/integrations/onnx.md +++ b/docs/en/integrations/onnx.md @@ -115,16 +115,16 @@ Before diving into the usage instructions, be sure to check out the range of [YO ### Export Arguments -| Argument | Type | Default | Description | -| ---------- | ---------------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `onnx` | 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. | -| `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. | -| `opset` | `int` | `None` | Specifies the ONNX opset version for compatibility with different ONNX parsers and runtimes. If not set, uses the latest supported version. | -| `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. | +| Argument | Type | Default | Description | +| ---------- | ---------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'onnx'` | 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. | +| `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. | +| `opset` | `int` | `None` | Specifies the ONNX opset version for compatibility with different ONNX parsers and runtimes. If not set, uses the latest supported version. | +| `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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/openvino.md b/docs/en/integrations/openvino.md index a7e834bc..9a3f9f33 100644 --- a/docs/en/integrations/openvino.md +++ b/docs/en/integrations/openvino.md @@ -59,16 +59,16 @@ Export a YOLOv8n model to OpenVINO format and run inference with the exported mo ## Export Arguments -| 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. | +| 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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/paddlepaddle.md b/docs/en/integrations/paddlepaddle.md index 5eae09a9..4050d3c8 100644 --- a/docs/en/integrations/paddlepaddle.md +++ b/docs/en/integrations/paddlepaddle.md @@ -112,11 +112,11 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `paddle` | 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. | -| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | +| Argument | Type | Default | Description | +| -------- | ---------------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'paddle'` | 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. | +| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/rockchip-rknn.md b/docs/en/integrations/rockchip-rknn.md index c8688975..17db9716 100644 --- a/docs/en/integrations/rockchip-rknn.md +++ b/docs/en/integrations/rockchip-rknn.md @@ -93,12 +93,12 @@ For detailed instructions and best practices related to the installation process ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `rknn` | 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. | -| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | -| `name` | `str` | `rk3588` | Specifies the Rockchip model (rk3588, rk3576, rk3566, rk3568, rk3562, rv1103, rv1106, rv1103b, rv1106b, rk2118) | +| Argument | Type | Default | Description | +| -------- | ---------------- | ---------- | --------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'rknn'` | 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. | +| `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | +| `name` | `str` | `'rk3588'` | Specifies the Rockchip model (rk3588, rk3576, rk3566, rk3568, rk3562, rv1103, rv1106, rv1103b, rv1106b, rk2118) | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/sony-imx500.md b/docs/en/integrations/sony-imx500.md index f0dab01d..95cf47b8 100644 --- a/docs/en/integrations/sony-imx500.md +++ b/docs/en/integrations/sony-imx500.md @@ -87,12 +87,12 @@ yolov8n_imx_model ## Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `imx` | 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. | -| `int8` | `bool` | `True` | 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. | -| `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` | `'imx'` | 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. | +| `int8` | `bool` | `True` | 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. | +| `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). diff --git a/docs/en/integrations/tensorrt.md b/docs/en/integrations/tensorrt.md index 5464ad62..c9ed310f 100644 --- a/docs/en/integrations/tensorrt.md +++ b/docs/en/integrations/tensorrt.md @@ -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). diff --git a/docs/en/integrations/tf-graphdef.md b/docs/en/integrations/tf-graphdef.md index 7ae66812..f265bde5 100644 --- a/docs/en/integrations/tf-graphdef.md +++ b/docs/en/integrations/tf-graphdef.md @@ -107,7 +107,7 @@ Before diving into the usage instructions, it's important to note that while all | Argument | Type | Default | Description | | -------- | ---------------- | ------- | --------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `pb` | Target format for the exported model, defining compatibility with various deployment environments. | +| `format` | `str` | `'pb'` | 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. | | `batch` | `int` | `1` | Specifies export model batch inference size or the max number of images the exported model will process concurrently in `predict` mode. | diff --git a/docs/en/integrations/tf-savedmodel.md b/docs/en/integrations/tf-savedmodel.md index bc0d093c..0ec979e7 100644 --- a/docs/en/integrations/tf-savedmodel.md +++ b/docs/en/integrations/tf-savedmodel.md @@ -99,14 +99,14 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `saved_model` | 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. | -| `keras` | `bool` | `False` | Enables export to Keras format, providing compatibility with TensorFlow serving and APIs. | -| `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. | -| `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. | +| Argument | Type | Default | Description | +| -------- | ---------------- | --------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'saved_model'` | 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. | +| `keras` | `bool` | `False` | Enables export to Keras format, providing compatibility with TensorFlow serving and APIs. | +| `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. | +| `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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/tfjs.md b/docs/en/integrations/tfjs.md index eec6d301..7834ddea 100644 --- a/docs/en/integrations/tfjs.md +++ b/docs/en/integrations/tfjs.md @@ -97,14 +97,14 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | ------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `tfjs` | 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. | -| `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. | +| Argument | Type | Default | Description | +| -------- | ---------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'tfjs'` | 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. | +| `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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/integrations/tflite.md b/docs/en/integrations/tflite.md index 82b96708..01009d0a 100644 --- a/docs/en/integrations/tflite.md +++ b/docs/en/integrations/tflite.md @@ -103,15 +103,15 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| -------- | ---------------- | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `tflite` | 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. | -| `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` | `'tflite'` | 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. | +| `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). diff --git a/docs/en/integrations/torchscript.md b/docs/en/integrations/torchscript.md index 3746e6b6..f80e8bd1 100644 --- a/docs/en/integrations/torchscript.md +++ b/docs/en/integrations/torchscript.md @@ -107,13 +107,13 @@ Before diving into the usage instructions, it's important to note that while all ### Export Arguments -| Argument | Type | Default | Description | -| ---------- | ---------------- | ------------- | --------------------------------------------------------------------------------------------------------------------------------------- | -| `format` | `str` | `torchscript` | 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. | -| `optimize` | `bool` | `False` | Applies optimization for mobile devices, potentially reducing model size and improving performance. | -| `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. | +| Argument | Type | Default | Description | +| ---------- | ---------------- | --------------- | --------------------------------------------------------------------------------------------------------------------------------------- | +| `format` | `str` | `'torchscript'` | 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. | +| `optimize` | `bool` | `False` | Applies optimization for mobile devices, potentially reducing model size and improving performance. | +| `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. | For more details about the export process, visit the [Ultralytics documentation page on exporting](../modes/export.md). diff --git a/docs/en/macros/augmentation-args.md b/docs/en/macros/augmentation-args.md index bee27ddd..fae363ff 100644 --- a/docs/en/macros/augmentation-args.md +++ b/docs/en/macros/augmentation-args.md @@ -1,20 +1,20 @@ -| Argument | Type | Default | Range | Description | -| ----------------- | ------- | ------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `hsv_h` | `float` | `0.015` | `0.0 - 1.0` | Adjusts the hue of the image by a fraction of the color wheel, introducing color variability. Helps the model generalize across different lighting conditions. | -| `hsv_s` | `float` | `0.7` | `0.0 - 1.0` | Alters the saturation of the image by a fraction, affecting the intensity of colors. Useful for simulating different environmental conditions. | -| `hsv_v` | `float` | `0.4` | `0.0 - 1.0` | Modifies the value (brightness) of the image by a fraction, helping the model to perform well under various lighting conditions. | -| `degrees` | `float` | `0.0` | `-180 - +180` | Rotates the image randomly within the specified degree range, improving the model's ability to recognize objects at various orientations. | -| `translate` | `float` | `0.1` | `0.0 - 1.0` | Translates the image horizontally and vertically by a fraction of the image size, aiding in learning to detect partially visible objects. | -| `scale` | `float` | `0.5` | `>=0.0` | Scales the image by a gain factor, simulating objects at different distances from the camera. | -| `shear` | `float` | `0.0` | `-180 - +180` | Shears the image by a specified degree, mimicking the effect of objects being viewed from different angles. | -| `perspective` | `float` | `0.0` | `0.0 - 0.001` | Applies a random perspective transformation to the image, enhancing the model's ability to understand objects in 3D space. | -| `flipud` | `float` | `0.0` | `0.0 - 1.0` | Flips the image upside down with the specified probability, increasing the data variability without affecting the object's characteristics. | -| `fliplr` | `float` | `0.5` | `0.0 - 1.0` | Flips the image left to right with the specified probability, useful for learning symmetrical objects and increasing dataset diversity. | -| `bgr` | `float` | `0.0` | `0.0 - 1.0` | Flips the image channels from RGB to BGR with the specified probability, useful for increasing robustness to incorrect channel ordering. | -| `mosaic` | `float` | `1.0` | `0.0 - 1.0` | Combines four training images into one, simulating different scene compositions and object interactions. Highly effective for complex scene understanding. | -| `mixup` | `float` | `0.0` | `0.0 - 1.0` | Blends two images and their labels, creating a composite image. Enhances the model's ability to generalize by introducing label noise and visual variability. | -| `copy_paste` | `float` | `0.0` | `0.0 - 1.0` | Copies and pastes objects across images, useful for increasing object instances and learning object occlusion. Requires segmentation labels. | -| `copy_paste_mode` | `str` | `flip` | - | Copy-Paste augmentation method selection among the options of (`"flip"`, `"mixup"`). | -| `auto_augment` | `str` | `randaugment` | - | Automatically applies a predefined augmentation policy (`randaugment`, `autoaugment`, `augmix`), optimizing for classification tasks by diversifying the visual features. | -| `erasing` | `float` | `0.4` | `0.0 - 0.9` | Randomly erases a portion of the image during classification training, encouraging the model to focus on less obvious features for recognition. | -| `crop_fraction` | `float` | `1.0` | `0.1 - 1.0` | Crops the classification image to a fraction of its size to emphasize central features and adapt to object scales, reducing background distractions. | +| Argument | Type | Default | Range | Description | +| ----------------- | ------- | --------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `hsv_h` | `float` | `0.015` | `0.0 - 1.0` | Adjusts the hue of the image by a fraction of the color wheel, introducing color variability. Helps the model generalize across different lighting conditions. | +| `hsv_s` | `float` | `0.7` | `0.0 - 1.0` | Alters the saturation of the image by a fraction, affecting the intensity of colors. Useful for simulating different environmental conditions. | +| `hsv_v` | `float` | `0.4` | `0.0 - 1.0` | Modifies the value (brightness) of the image by a fraction, helping the model to perform well under various lighting conditions. | +| `degrees` | `float` | `0.0` | `-180 - +180` | Rotates the image randomly within the specified degree range, improving the model's ability to recognize objects at various orientations. | +| `translate` | `float` | `0.1` | `0.0 - 1.0` | Translates the image horizontally and vertically by a fraction of the image size, aiding in learning to detect partially visible objects. | +| `scale` | `float` | `0.5` | `>=0.0` | Scales the image by a gain factor, simulating objects at different distances from the camera. | +| `shear` | `float` | `0.0` | `-180 - +180` | Shears the image by a specified degree, mimicking the effect of objects being viewed from different angles. | +| `perspective` | `float` | `0.0` | `0.0 - 0.001` | Applies a random perspective transformation to the image, enhancing the model's ability to understand objects in 3D space. | +| `flipud` | `float` | `0.0` | `0.0 - 1.0` | Flips the image upside down with the specified probability, increasing the data variability without affecting the object's characteristics. | +| `fliplr` | `float` | `0.5` | `0.0 - 1.0` | Flips the image left to right with the specified probability, useful for learning symmetrical objects and increasing dataset diversity. | +| `bgr` | `float` | `0.0` | `0.0 - 1.0` | Flips the image channels from RGB to BGR with the specified probability, useful for increasing robustness to incorrect channel ordering. | +| `mosaic` | `float` | `1.0` | `0.0 - 1.0` | Combines four training images into one, simulating different scene compositions and object interactions. Highly effective for complex scene understanding. | +| `mixup` | `float` | `0.0` | `0.0 - 1.0` | Blends two images and their labels, creating a composite image. Enhances the model's ability to generalize by introducing label noise and visual variability. | +| `copy_paste` | `float` | `0.0` | `0.0 - 1.0` | Copies and pastes objects across images, useful for increasing object instances and learning object occlusion. Requires segmentation labels. | +| `copy_paste_mode` | `str` | `'flip'` | - | Copy-Paste augmentation method selection among the options of (`"flip"`, `"mixup"`). | +| `auto_augment` | `str` | `'randaugment'` | - | Automatically applies a predefined augmentation policy (`randaugment`, `autoaugment`, `augmix`), optimizing for classification tasks by diversifying the visual features. | +| `erasing` | `float` | `0.4` | `0.0 - 0.9` | Randomly erases a portion of the image during classification training, encouraging the model to focus on less obvious features for recognition. | +| `crop_fraction` | `float` | `1.0` | `0.1 - 1.0` | Crops the classification image to a fraction of its size to emphasize central features and adapt to object scales, reducing background distractions. | diff --git a/docs/en/macros/export-args.md b/docs/en/macros/export-args.md index 35361274..92e62bb3 100644 --- a/docs/en/macros/export-args.md +++ b/docs/en/macros/export-args.md @@ -13,4 +13,4 @@ | `nms` | `bool` | `False` | Adds Non-Maximum Suppression (NMS) to the exported model when supported (see Export Formats), improving detection post-processing efficiency. | | `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](https://docs.ultralytics.com/datasets) configuration file (default: `coco8.yaml`), essential for quantization. | +| `data` | `str` | `'coco8.yaml'` | Path to the [dataset](https://docs.ultralytics.com/datasets) configuration file (default: `coco8.yaml`), essential for quantization. | diff --git a/docs/en/macros/sam-auto-annotate.md b/docs/en/macros/sam-auto-annotate.md index 12204e3d..a4b8e44b 100644 --- a/docs/en/macros/sam-auto-annotate.md +++ b/docs/en/macros/sam-auto-annotate.md @@ -1,9 +1,9 @@ | Argument | Type | Default | Description | | ------------ | ----------- | -------------- | ---------------------------------------------------------------------------------------------- | | `data` | `str` | required | Path to directory containing target images for annotation or segmentation. | -| `det_model` | `str` | `"yolo11x.pt"` | YOLO detection model path for initial object detection. | -| `sam_model` | `str` | `"sam2_b.pt"` | SAM2 model path for segmentation (supports t/s/b/l variants and SAM2.1) and mobile_sam models. | -| `device` | `str` | `""` | Computation device (e.g., 'cuda:0', 'cpu', or '' for automatic device detection). | +| `det_model` | `str` | `'yolo11x.pt'` | YOLO detection model path for initial object detection. | +| `sam_model` | `str` | `'sam2_b.pt'` | SAM2 model path for segmentation (supports t/s/b/l variants and SAM2.1) and mobile_sam models. | +| `device` | `str` | `''` | Computation device (e.g., 'cuda:0', 'cpu', or '' for automatic device detection). | | `conf` | `float` | `0.25` | YOLO detection confidence threshold for filtering weak detections. | | `iou` | `float` | `0.45` | IoU threshold for Non-Maximum Suppression to filter overlapping boxes. | | `imgsz` | `int` | `640` | Input size for resizing images (must be multiple of 32). | diff --git a/docs/en/macros/solutions-args.md b/docs/en/macros/solutions-args.md index 42ae58e6..14f939f1 100644 --- a/docs/en/macros/solutions-args.md +++ b/docs/en/macros/solutions-args.md @@ -7,6 +7,6 @@ | `up_angle` | `float` | `145.0` | Angle threshold for detecting the "up" position in workouts monitoring. Can be adjusted based on the position of keypoints for different exercises. | | `down_angle` | `float` | `90.0` | Angle threshold for detecting the "down" position in workouts monitoring. Adjust this based on keypoint positions for specific exercises. | | `kpts` | `list` | `[6, 8, 10]` | List of keypoints used for monitoring workouts. These keypoints correspond to body joints or parts, such as shoulders, elbows, and wrists, for exercises like push-ups, pull-ups, squats, ab-workouts. | -| `analytics_type` | `str` | `line` | Specifies the type of analytics visualization to generate. Options include `"line"`, `"pie"`, `"bar"`, or `"area"`. The default is `"line"` for trend visualization. | +| `analytics_type` | `str` | `'line'` | Specifies the type of analytics visualization to generate. Options include `"line"`, `"pie"`, `"bar"`, or `"area"`. The default is `"line"` for trend visualization. | | `json_file` | `str` | `None` | Path to the JSON file defining regions for parking systems or similar applications. Enables flexible configuration of analysis areas. | | `records` | `int` | `5` | Total detections count that triggers an automated email notification about unusual activity. | diff --git a/docs/en/macros/track-args.md b/docs/en/macros/track-args.md index a6678b70..e94d6c2d 100644 --- a/docs/en/macros/track-args.md +++ b/docs/en/macros/track-args.md @@ -1,9 +1,9 @@ -| Argument | Type | Default | Description | -| --------- | ------- | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `source` | `str` | `None` | Specifies the source directory for images or videos. Supports file paths and URLs. | -| `persist` | `bool` | `False` | Enables persistent tracking of objects between frames, maintaining IDs across video sequences. | -| `tracker` | `str` | `botsort.yaml` | Specifies the tracking algorithm to use, e.g., `bytetrack.yaml` or `botsort.yaml`. | -| `conf` | `float` | `0.3` | Sets the confidence threshold for detections; lower values allow more objects to be tracked but may include false positives. | -| `iou` | `float` | `0.5` | Sets the [Intersection over Union](https://www.ultralytics.com/glossary/intersection-over-union-iou) (IoU) threshold for filtering overlapping detections. | -| `classes` | `list` | `None` | Filters results by class index. For example, `classes=[0, 2, 3]` only tracks the specified classes. | -| `verbose` | `bool` | `True` | Controls the display of tracking results, providing a visual output of tracked objects. | +| Argument | Type | Default | Description | +| --------- | ------- | ---------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `source` | `str` | `None` | Specifies the source directory for images or videos. Supports file paths and URLs. | +| `persist` | `bool` | `False` | Enables persistent tracking of objects between frames, maintaining IDs across video sequences. | +| `tracker` | `str` | `'botsort.yaml'` | Specifies the tracking algorithm to use, e.g., `bytetrack.yaml` or `botsort.yaml`. | +| `conf` | `float` | `0.3` | Sets the confidence threshold for detections; lower values allow more objects to be tracked but may include false positives. | +| `iou` | `float` | `0.5` | Sets the [Intersection over Union](https://www.ultralytics.com/glossary/intersection-over-union-iou) (IoU) threshold for filtering overlapping detections. | +| `classes` | `list` | `None` | Filters results by class index. For example, `classes=[0, 2, 3]` only tracks the specified classes. | +| `verbose` | `bool` | `True` | Controls the display of tracking results, providing a visual output of tracked objects. | diff --git a/docs/en/macros/validation-args.md b/docs/en/macros/validation-args.md index ab5014c0..4f90506e 100644 --- a/docs/en/macros/validation-args.md +++ b/docs/en/macros/validation-args.md @@ -13,6 +13,6 @@ | `dnn` | `bool` | `False` | If `True`, uses the [OpenCV](https://www.ultralytics.com/glossary/opencv) DNN module for ONNX model inference, offering an alternative to [PyTorch](https://www.ultralytics.com/glossary/pytorch) inference methods. | | `plots` | `bool` | `False` | When set to `True`, generates and saves plots of predictions versus ground truth for visual evaluation of the model's performance. | | `rect` | `bool` | `True` | If `True`, uses rectangular inference for batching, reducing padding and potentially increasing speed and efficiency. | -| `split` | `str` | `val` | Determines the dataset split to use for validation (`val`, `test`, or `train`). Allows flexibility in choosing the data segment for performance evaluation. | +| `split` | `str` | `'val'` | Determines the dataset split to use for validation (`val`, `test`, or `train`). Allows flexibility in choosing the data segment for performance evaluation. | | `project` | `str` | `None` | Name of the project directory where validation outputs are saved. | | `name` | `str` | `None` | Name of the validation run. Used for creating a subdirectory within the project folder, where validation logs and outputs are stored. |