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本页目录

  • 如何放置
  • 输入和输出
  • 用法
  • 功能示例
  • 深度对齐
  • 配置摄像头以实现高 FPS
  • 在运行时更改摄像头校准
  • 特定平台配置
  • 参考

StereoDepth

Supported on:RVC2RVC4
StereoDepth 节点可从立体摄像头的立体图像对计算视差和/或深度。

配置立体深度

通过分步配置指南了解如何获得最佳深度结果。
打开教程
要查看精度测量结果，请参阅 深度精度。

如何放置

Python

Python
1pipeline = dai.Pipeline()
2stereo = pipeline.create(dai.node.StereoDepth)

C++

C++
1dai::Pipeline pipeline;
2auto stereo = pipeline.create<dai::node::StereoDepth>();

输入和输出

用法

Python

Python
1pipeline = dai.Pipeline()
2stereo = pipeline.create(dai.node.StereoDepth)
3
4# 设置配置文件预设为 ROBOTICS
5stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.ROBOTICS)
6# 更好地处理遮挡：
7stereo.setLeftRightCheck(True)
8# 更近的最小深度，视差范围加倍：
9stereo.setExtendedDisparity(True)
10# 更远的距离精度更高，小数视差 32 级：
11stereo.setSubpixel(True)
12
13# 提前定义并配置 MonoCamera 节点
14left.out.link(stereo.left)
15right.out.link(stereo.right)

C++

C++
1dai::Pipeline pipeline;
2auto stereo = pipeline.create<dai::node::StereoDepth>();
3
4// 设置配置文件预设为 ROBOTICS
5stereo->setDefaultProfilePreset(dai::node::StereoDepth::PresetMode::ROBOTICS);
6// 更好地处理遮挡：
7stereo->setLeftRightCheck(true);
8// 更近的最小深度，视差范围加倍：
9stereo->setExtendedDisparity(true);
10// 更远的距离精度更高，小数视差 32 级：
11stereo->setSubpixel(true);
12
13// 提前定义并配置 MonoCamera 节点
14left->out.link(stereo->left);
15right->out.link(stereo->right);

功能示例

深度对齐

图像对齐用于将深度图与特定流对齐。对于 Depthai v3，默认的立体深度对齐是 RECTIFIED_LEFT。
Python
1pipeline = dai.Pipeline()
2stereo = pipeline.create(dai.node.StereoDepth)
3 # alignment to RECTIFIED_LEFT or RECTIFIED_RIGHT
4stereo.setDepthAlign(dai.StereoDepthConfig.AlgorithmControl.DepthAlign.RECTIFIED_LEFT)
或者您可以使用 ImageAlign 节点：
Python
1align = pipeline.create(dai.node.ImageAlign)
2stereo.depth.link(align.input)
3rgbOut.link(align.inputAlignTo)  # Align depth to RGB
4align.outputAligned.link(sync.inputs["depth_aligned"])

配置摄像头以实现高 FPS

立体节点的性能直接受限于单目摄像头配置。 要以高帧率（例如 60 FPS）实现立体深度，必须将单目摄像头配置为以所需速率传输帧。
Python
1with dai.Pipeline(device) as pipeline:
2  stereo = pipeline.create(dai.node.StereoDepth)
3  mono_left = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_B)
4  mono_right = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_C)
5
6  def configure_cam(cam, size_x: int, size_y: int, fps: float):
7    cap = dai.ImgFrameCapability()
8    cap.size.fixed((size_x, size_y))
9    cap.fps.fixed(fps)
10  return cam.requestOutput(cap, True)
11
12  # Configure MonoCameras for 60 FPS at 640x400
13  mono_left_out = configure_cam(mono_left, 640, 400, 60)
14  mono_right_out = configure_cam(mono_right, 640, 400, 60)
从处理角度来看，在没有单目摄像头输入限制的情况下，立体节点本身能够以高达 400 FPS 的速率处理图像对，前提是输入为 256×256 像素。 但是，默认情况下，单目摄像头以 30 FPS 运行，这会相应地限制整体立体深度输出。

在运行时更改摄像头校准

可以在运行时更改摄像头校准。 可以使用 device.setCalibration() 方法更改校准，并且可以与 动态校准 结合使用，以防设备立体质量随时间因环境因素而下降。 可以使用 device.getCalibration() 获取相同的数据。

特定平台配置

选择您的平台（RVC2 或 RVC4）以查看特定于平台的文档、预设、配置选项和限制。

RVC2

StereoDepth 节点内部框图

software/depthai/nodes//depth_diagram.webp

深度预设

我们提供了一些深度预设，可用于快速为不同场景设置 StereoDepth 节点，而无需手动设置所有参数。 有关包含所有参数值的详细预设规格，请参阅 配置立体深度。
立体深度预设用途FPS @800PFPS @400P输出分辨率运动模糊范围（米）
默认通用1630输入分辨率的 1/2是0–10
人脸人脸跟踪、生物识别1630输入分辨率的 1/2是0–3
高细节3D 扫描、物体细节1630输入分辨率的 1/2是0–15
机器人导航、障碍物检测1634输入分辨率的 1/2否0–15
快速精确通用3090输入分辨率否0–65
快速密度通用3090输入分辨率否0–65
快速密度无子像素通用50110输入分辨率否0–65
由于使用了抽取滤波器，输出分辨率可能会减半，这意味着如果输入分辨率为 1280x800 (800P)，则会减小到 640x400 (400P)。 对于某些深度预设，由于 使用了抽取滤波器，输出分辨率可能会有所不同。 默认情况下，所有配置文件预设都启用了子像素，这会产生更精细的深度细节 但会导致 FPS 降低。要获得高 FPS，请关闭子像素。 高细节和人脸配置文件预设默认启用了扩展视差。

深度配置

扩展视差

扩展视差模式允许检测给定基线内的更近距离物体。这将最大视差搜索范围从 96 增加到 191，意味着范围现在是：[0..190]。
  1. 在原始尺寸图像（例如 1280x720）上计算视差。
  2. 在 2 倍下采样图像（例如 640x360）上计算视差。
  3. 在 Shave 上组合两个级别的视差，有效覆盖总共 191 个像素的视差范围（相对于原始分辨率）。
您可以使用 debugExtDispLrCheckIt1 和 debugExtDispLrCheckIt2 调试输出来进行调试/微调。

用法：

Python
1stereo.setExtendedDisparity(True)
注意： 在 RVC2 上，companding (costMatching.enableCompanding) 是扩展视差的替代方案：使用 companding 时，立体块使用稀疏匹配，因此视差范围扩展到 176 个值，这意味着范围是 [0..175]。匹配是密集的（逐像素）用于范围的前部，并逐渐稀疏（每 2 个像素，然后每 4 个像素）用于更高的视差，并且只有深度输出使用此扩展范围—视差图本身保持在正常范围内。

子像素视差

子像素模式可提高精度，对于远距离测量尤其有用。它还有助于更好地估计表面法线。在此模式下，立体相机执行：94 个深度步长 * 8 个子像素深度步长 + 2（最小值/最大值）= 754 个深度步长。唯一深度值的数量取决于子像素小数位数设置：
子像素小数位数唯一值数量
3754
41506
53010

用法：

Python
1stereo.setSubpixel(True)
2stereo.initialConfig.setSubpixelFractionalBits(3)  # 3, 4 或 5

LR 检查

左右检查或 LR 检查用于消除由于物体边界（左摄像机和右摄像机视图略有不同）的遮挡而错误计算的视差像素。
  1. 通过在 R->L 方向上进行匹配来计算视差。
  2. 通过在 L->R 方向上进行匹配来计算视差。
  3. 组合步骤 1 和 2 的结果，在 Shave 上运行：每个像素 d = disparity_LR(x,y) 与 disparity_RL(x-d,y) 进行比较。如果差异超过阈值，则最终视差图中的像素 (x,y) 将被无效化。
您可以使用 debugDispLrCheckIt1 和 debugDispLrCheckIt2 调试输出来进行调试/微调。LR 检查阈值：当 LR 和 RL 视差之间的差异小于 LR 检查阈值时，将考虑输出视差。

用法：

Python
1stereo.setLeftRightCheck(True)
2stereo.initialConfig.setLeftRightCheckThreshold(4)  # 设置阈值

置信度阈值

置信度阈值：立体深度算法在 96 个视差级别上搜索右摄像头点到左图像的匹配特征。在此过程中，它会计算每个视差级别的成本，并选择两个视差之间的最小成本，然后用它来计算每个像素的置信度。立体声节点仅在深度置信度低于置信度阈值时输出视差/深度像素（置信度值越低，表示深度精度越高）。置信度分数是反转的：
  • 0 - 最大置信度，表示具有有效值
  • 255 - 最小置信度，因此值可能不正确的可能性更大

用法：

Python
1stereo.initialConfig.setConfidenceThreshold(200)  # 值越低 = 精度越高，填充率越低

中值滤波器

这是一个非边缘保留的中值滤波器，可用于减少噪声和使深度图平滑。中值滤波器在硬件中实现，因此它是最快的滤波器。注意：当子像素模式设置为 4 或 5 位时，中值滤波将被禁用。

用法：

Python
1stereo.initialConfig.setMedianFilter(dai.MedianFilter.KERNEL_7x7)  # 选项：MEDIAN_OFF, KERNEL_3x3, KERNEL_5x5, KERNEL_7x7

斑点滤波器

斑点滤波器用于减少斑点噪声。斑点噪声是相邻视差/深度像素之间存在巨大差异的区域，斑点滤波器会尝试过滤该区域。

用法：

Python
1stereo.initialConfig.postProcessing.speckleFilter.enable = True
2stereo.initialConfig.postProcessing.speckleFilter.speckleRange = 48

时间滤波器

时间滤波器旨在通过根据先前帧操纵每像素值来提高深度数据的持久性。该滤波器对数据执行单次传递，调整深度值，同时更新跟踪历史记录。在像素数据丢失或无效的情况下，滤波器会使用用户定义的持久性模式来决定是否应使用存储的数据来改进丢失的值。请注意，由于其依赖于历史数据，该滤波器可能会引入明显的运动模糊/拖尾伪影，因此最适合静态场景。

用法：

Python
1stereo.initialConfig.postProcessing.temporalFilter.enable = True
2stereo.initialConfig.postProcessing.temporalFilter.alpha = 0.4  # 当前帧的权重 (0-1)
3stereo.initialConfig.postProcessing.temporalFilter.delta = 3  # 有效深度变化的阈值

空间滤波器

空间边缘保留滤波器将使用有效的相邻深度像素填充无效的深度像素。它执行一系列一维水平和垂直传递或迭代，以增强重建数据的平滑度。它基于这篇研究论文。

用法：

Python
1stereo.initialConfig.postProcessing.spatialFilter.enable = True
2stereo.initialConfig.postProcessing.spatialFilter.alpha = 0.5  # 边缘保留强度
3stereo.initialConfig.postProcessing.spatialFilter.delta = 8  # 有效深度变化的阈值
4stereo.initialConfig.postProcessing.spatialFilter.holeFillingRadius = 2  # 填充孔的半径
5stereo.initialConfig.postProcessing.spatialFilter.numIterations = 1  # 迭代次数

亮度滤波器

亮度滤波器将过滤掉（通过设置为 0 使其无效）所有输入立体摄像头图像像素超出配置的最小/最大亮度阈值的所有深度像素。当您遇到高动态范围场景时（例如，白天户外，或立体摄像头对可以直接看到光源时），此滤波器非常有用。它还有助于校正“伪影”，尤其是在使用宽 FOV 镜头并应用 alpha 参数时。

用法：

Python
1stereo.initialConfig.postProcessing.brightnessFilter.enable = True
2stereo.initialConfig.postProcessing.brightnessFilter.minBrightness = 0  # 最小亮度阈值
3stereo.initialConfig.postProcessing.brightnessFilter.maxBrightness = 255  # 最大亮度阈值

阈值滤波器

阈值滤波器将过滤掉所有超出配置的最小/最大阈值的所有深度像素。在受控环境中，当您确切知道场景的距离时（例如，30 厘米 - 2 米），建议使用此滤波器。

用法：

Python
1stereo.initialConfig.postProcessing.thresholdFilter.minRange = 0  # 最小深度（厘米）
2stereo.initialConfig.postProcessing.thresholdFilter.maxRange = 200  # 最大深度（厘米）

降采样滤波器

降采样滤波器会抽取深度图的样本，这意味着它会降低深度场景的复杂度，并允许其他滤波器更快地运行。将 decimationFactor 设置为 2 会将 1280x800 的深度图缩小到 640x400。我们可以选择像素跳过、中值或平均降采样模式，后两种模式也有助于滤波。decimationFactor 1 会禁用该滤波器。

用法：

Python
1stereo.initialConfig.postProcessing.decimationFilter.decimationFactor = 2  # 1 = 禁用, 2 = 2 倍缩小, 等等。

滤波顺序

滤波器的顺序很重要，因为一个滤波器的输出是下一个滤波器的输入。滤波器的顺序是可自定义的：用法：
Python
1config.postProcessing.filteringOrder = [
2    dai.RawStereoDepthConfig.PostProcessing.Filter.TEMPORAL,
3    dai.RawStereoDepthConfig.PostProcessing.Filter.SPECKLE,
4    dai.RawStereoDepthConfig.PostProcessing.Filter.SPATIAL,
5    dai.RawStereoDepthConfig.PostProcessing.Filter.MEDIAN,
6    dai.RawStereoDepthConfig.PostProcessing.Filter.DECIMATION
7]
8stereo.initialConfig.set(config)

限制

  • 当子像素模式设置为 4 位或 5 位时，中值滤波将被禁用。
  • 对于 RGB-深度对齐，RGB 摄像头必须与立体摄像头对放置在同一水平线上。
  • 使用视差偏移时，RGB-深度对齐将不起作用。

RVC4

StereoDepth 节点内部框图

StereoDepth 内部框图 (RVC4)

深度预设

我们提供了一些深度预设，可用于针对不同场景快速设置 StereoDepth 节点，而无需手动设置所有参数。有关包含所有参数值的详细预设规范，请参阅 配置立体深度。
立体深度预设用途FPS @800PFPS @400P输出分辨率运动模糊范围（米）
快速精确通用6060输入分辨率否0–65
快速稠密通用3660输入分辨率否0–65

深度配置

扩展视差

扩展视差模式允许检测给定基线下的更近/更远物体。这会将最大视差搜索范围从 64 增加到 128，意味着范围现在是：[0..127]。
  1. 在原始尺寸图像（例如 1280x800）上计算视差。
  2. 在 2 倍下采样图像（例如 640x400）上计算视差。
  3. 合并两个级别的视差。

用法：

Python
1stereo.setExtendedDisparity(True)

亚像素视差

亚像素模式提高了视差精度，对于远距离深度测量尤其有用。 它还可以更准确地估计表面法线。在 RVC4 上，亚像素处理默认启用，并且无法禁用，因为它已在硬件中固定。 该实现使用 4 个小数位。

LR 检查

左右检查（LR-Check）用于消除由于物体边界遮挡（左右摄像头视图略有不同）而错误计算的视差像素。在 RVC4 上，LR 检查纯粹在 CPU 上通过软件运行。左右检查阈值：像素之间允许的最大视差差异。值越小，深度越稀疏（更多像素无效）。

用法：

Python
1stereo.initialConfig.algorithmControl.enableSwLeftRightCheck = True
2stereo.initialConfig.algorithmControl.leftRightCheckThreshold = 10  # 设置阈值
注意：RVC4 具有不同的内部机制，该机制基本上执行 LR 检查功能 - 这就是遮挡置信度权重（请参阅下面的置信度指标部分）。遮挡置信度权重比较了从左到右和从右到左搜索所产生的视差差异，这本质上就是 LR 检查所做的。

软件置信度

软件置信度过滤器获取视差和置信度图（来自立体硬件块的每像素 8 位置信度），并应用阈值来过滤掉低置信度像素。 此过滤在 CPU 上完成，并在硬件块生成视差后应用。此过滤在 CPU 上执行，并在硬件块生成视差后应用。 启用左右（LR）检查时，使用相同的阈值使 L→R 和 R→L 的视差（及其相应的置信度图）无效。值：
  • 有限过滤：50-100
  • 中度过滤：200
  • 重度过滤：>200（高度场景特定）

用法：

Python
1stereo.initialConfig.costMatching.enableSwConfidenceThresholding = True
2stereo.initialConfig.costMatching.confidenceThreshold = 200  # 根据所需的过滤级别进行调整

置信度指标（遮挡、运动矢量、平坦度）

三个不同的指标用于计算置信度图，这些图会合并成一个最终的置信度图。
  • 遮挡置信度权重
    • 基本执行 LR 检查。比较从左到右和从右到左搜索所产生的视差差异（前向/后向运动矢量一致性）。
  • 运动矢量 (MV) 置信度权重
    • MV 方差计算每个像素周围局部边缘感知窗口中的方差；给定一个约束以确保同一对象内的深度平滑且一致。
    • MV 置信度阈值：MV 方差的阈值偏移量。有效范围 [0,3]。值为 0 允许最大方差。
  • 平坦度置信度权重
    • 平坦度考虑输入图像纹理，并屏蔽掉纹理相似度过高的低纹理区域。可以通过平坦度阈值调整所需的最小纹理量。
    • 平坦度阈值：用于平坦区域检查的阈值。值越高，像素根据 census 特征比较被检测为平坦区域的可能性越大。用于缺乏足够匹配特征的低纹理区域。
    • 平坦度覆盖：如果像素被检测为平坦，则将置信度设置为零。

用法：

Python
1# 置信度指标权重（RVC4 必须加起来等于 32）
2stereo.initialConfig.confidenceMetrics.occlusionConfidenceWeight = 12
3stereo.initialConfig.confidenceMetrics.motionVectorConfidenceWeight = 10
4stereo.initialConfig.confidenceMetrics.flatnessConfidenceWeight = 10
5
6# 阈值
7stereo.initialConfig.confidenceMetrics.motionVectorConfidenceThreshold = 1  # 有效范围 [0,3]
8stereo.initialConfig.confidenceMetrics.flatnessConfidenceThreshold = 5
9stereo.initialConfig.confidenceMetrics.flatnessOverride = True  # 如果是平坦的，则将置信度设置为零
注意：置信度指标权重必须加起来等于 32 才能用于 RVC4。

自适应中值滤波

自适应中值滤波仅将滤波应用于低于指定阈值的不确定性像素。自适应中值滤波阈值：仅将滤波应用于低于此值的低置信度像素。此阈值应小于“空洞填充”中的“填充置信度阈值”。

用法：

Python
1stereo.initialConfig.postProcessing.adaptiveMedianFilter.enable = True
2stereo.initialConfig.postProcessing.adaptiveMedianFilter.confidenceThreshold = 200  # 应小于 hole filling fillConfidenceThreshold

空洞填充

空洞填充是一种后处理滤波器，通过将像素分组为超像素（六边形区域）来填充深度图中的空隙，并根据这些区域内的高置信度像素计算视差值。此滤波器会修改置信度图以标记已填充的区域。该滤波器的工作原理如下：
  1. 将像素分组为超像素（六边形区域）
  2. 使用置信度高于高置信度阈值的像素为每个超像素计算视差值
  3. 根据填充置信度阈值和最小有效视差要求填充空洞
参数：
  • 高置信度阈值 - 置信度高于此阈值的像素用于为每个超像素计算视差值。如果设置为最大值（255），则不应形成任何超像素。
  • 填充置信度阈值 - 置信度低于此值的像素将被过滤掉（如果 invalidateDisparities 设置为 True）或成为超像素计算的一部分。
  • 最小有效视差 - 决定区域中需要有多少比例的像素置信度高于高置信度阈值才能包含在超像素的视差计算中。值：1（50%）、2（25%）或 3（12.5%）。最小有效视差值越高，超像素越大（六边形越多）。
  • 无效化视差 - 如果设置为 True，则最终视差图将过滤掉低于填充置信度阈值的像素。

用法：

Python
1stereo.initialConfig.postProcessing.holeFilling.enable = True
2stereo.initialConfig.postProcessing.holeFilling.highConfidenceThreshold = 200
3stereo.initialConfig.postProcessing.holeFilling.fillConfidenceThreshold = 210
4stereo.initialConfig.postProcessing.holeFilling.minValidDisparity = 1  # 1, 2, 或 3
5stereo.initialConfig.postProcessing.holeFilling.invalidateDisparities = True

中值滤波

这是一种非边缘保持中值滤波器，可用于减少噪声和使深度图平滑。在 RVC4 上：中值滤波器在软件（CPU）中实现，并且仅支持 3x3 或 5x5 的内核大小。如果请求 7x7，它会自动降级为 5x5。

用法：

Python
1stereo.initialConfig.setMedianFilter(dai.MedianFilter.KERNEL_3x3)  # 选项：MEDIAN_OFF, KERNEL_3x3, KERNEL_5x5

斑点滤波

斑点滤波用于减少斑点噪声。斑点噪声是相邻视差/深度像素之间存在巨大差异的区域，斑点滤波器会尝试过滤该区域。

用法：

Python
1stereo.initialConfig.postProcessing.speckleFilter.enable = True
2stereo.initialConfig.postProcessing.speckleFilter.speckleRange = 48

时间滤波

时间滤波旨在通过根据先前帧操纵每像素值来提高深度数据的持久性。该滤波器对数据执行单次传递，调整深度值，同时更新跟踪历史记录。在像素数据缺失或无效的情况下，滤波器会使用用户定义的持久性模式来决定是否应使用存储的数据来改进缺失的值。请注意，由于其依赖于历史数据，该滤波器可能会引入可见的运动模糊/拖尾伪影，因此最适合静态场景。

用法：

Python
1stereo.initialConfig.postProcessing.temporalFilter.enable = True
2stereo.initialConfig.postProcessing.temporalFilter.alpha = 0.4  # 当前帧的权重（0-1）
3stereo.initialConfig.postProcessing.temporalFilter.delta = 3  # 有效深度变化的阈值

空间滤波

空间边缘保持滤波器将用有效的相邻深度像素填充无效的深度像素。它执行一系列一维水平和垂直传递或迭代，以增强重建数据的平滑度。它基于这篇研究论文。

用法：

Python
1stereo.initialConfig.postProcessing.spatialFilter.enable = True
2stereo.initialConfig.postProcessing.spatialFilter.alpha = 0.5  # 边缘保持强度
3stereo.initialConfig.postProcessing.spatialFilter.delta = 8  # 有效深度变化的阈值
4stereo.initialConfig.postProcessing.spatialFilter.holeFillingRadius = 2  # 填充空洞的半径
5stereo.initialConfig.postProcessing.spatialFilter.numIterations = 1  # 迭代次数

亮度过滤器

亮度过滤器将过滤掉（通过设置为 0 使之无效）输入立体摄像头图像像素亮度超出配置的最小/最大阈值的所有深度像素。当您遇到高动态范围场景时，例如白天室外，或者立体摄像头对可以直接看到光源时，此过滤器非常有用。它还有助于处理校正“伪影”，尤其是在使用宽视场镜头并应用 alpha 参数时。

用法：

Python
1stereo.initialConfig.postProcessing.brightnessFilter.enable = True
2stereo.initialConfig.postProcessing.brightnessFilter.minBrightness = 0  # 最小亮度阈值
3stereo.initialConfig.postProcessing.brightnessFilter.maxBrightness = 255  # 最大亮度阈值

阈值过滤器

阈值过滤器将过滤掉超出配置的最小/最大阈值的所有深度像素。在受控环境中，当您确切知道场景的距离范围时（例如，30 厘米 - 2 米），建议使用此过滤器。

用法：

Python
1stereo.initialConfig.postProcessing.thresholdFilter.minRange = 0  # 最小深度（厘米）
2stereo.initialConfig.postProcessing.thresholdFilter.maxRange = 200  # 最大深度（厘米）

抽取过滤器

抽取过滤器将对深度图进行子采样，这意味着它会降低深度场景的复杂性，并允许其他过滤器运行得更快。将 decimationFactor 设置为 2 会将 1280x800 的深度图缩小到 640x400。我们可以选择像素跳过、中值或平均抽取模式，后两种模式也有助于过滤。decimationFactor 为 1 时禁用该过滤器。

用法：

Python
1stereo.initialConfig.postProcessing.decimationFilter.decimationFactor = 2  # 1 = 禁用，2 = 2 倍缩小，依此类推

过滤顺序

过滤器的顺序很重要，因为一个过滤器的输出是下一个过滤器的输入。过滤器的顺序是可自定义的：

用法：

Python
1config.postProcessing.filteringOrder = [
2    dai.RawStereoDepthConfig.PostProcessing.Filter.TEMPORAL,
3    dai.RawStereoDepthConfig.PostProcessing.Filter.SPECKLE,
4    dai.RawStereoDepthConfig.PostProcessing.Filter.SPATIAL,
5    dai.RawStereoDepthConfig.PostProcessing.Filter.MEDIAN,
6    dai.RawStereoDepthConfig.PostProcessing.Filter.DECIMATION
7]
8stereo.initialConfig.set(config)

限制

  • 中值过滤器：在 RVC4 上，中值过滤器在软件（CPU）中实现，并且仅支持 3x3 或 5x5 的内核大小。如果请求 7x7，它会自动降级为 5x5。
  • 亚像素：在 RVC4 上固定为 4 位（无法更改为 3 位或 5 位）。
  • 左右检查：在 RVC4 上纯粹在软件（CPU）上运行（不像 RVC2 那样硬件加速）。

参考

class

dai::node::StereoDepth

#include StereoDepth.hpp
variable
std::shared_ptr< StereoDepthConfig > initialConfig
Initial config to use for StereoDepth.
variable
Input inputConfig
Input StereoDepthConfig message with ability to modify parameters in runtime.
variable
Input inputAlignTo
Input align to message. Default queue is non-blocking with size 1.
variable
Input left
Input for left ImgFrame of left-right pair
variable
Input right
Input for right ImgFrame of left-right pair
variable
Output depth
Outputs ImgFrame message that carries RAW16 encoded (0..65535) depth data in depth units (millimeter by default).Non-determined / invalid depth values are set to 0
variable
Output disparity
Outputs ImgFrame message that carries RAW8 / RAW16 encoded disparity data: RAW8 encoded (0..95) for standard mode; RAW8 encoded (0..190) for extended disparity mode; RAW16 encoded for subpixel disparity mode:
  • 0..760 for 3 fractional bits (by default)
  • 0..1520 for 4 fractional bits
  • 0..3040 for 5 fractional bits
variable
Output syncedLeft
Passthrough ImgFrame message from 'left' Input.
variable
Output syncedRight
Passthrough ImgFrame message from 'right' Input.
variable
Output rectifiedLeft
Outputs ImgFrame message that carries RAW8 encoded (grayscale) rectified frame data.
variable
Output rectifiedRight
Outputs ImgFrame message that carries RAW8 encoded (grayscale) rectified frame data.
variable
Output outConfig
Outputs StereoDepthConfig message that contains current stereo configuration.
variable
Output debugDispLrCheckIt1
Outputs ImgFrame message that carries left-right check first iteration (before combining with second iteration) disparity map. Useful for debugging/fine tuning.
variable
Output debugDispLrCheckIt2
Outputs ImgFrame message that carries left-right check second iteration (before combining with first iteration) disparity map. Useful for debugging/fine tuning.
variable
Output debugExtDispLrCheckIt1
Outputs ImgFrame message that carries extended left-right check first iteration (downscaled frame, before combining with second iteration) disparity map. Useful for debugging/fine tuning.
variable
Output debugExtDispLrCheckIt2
Outputs ImgFrame message that carries extended left-right check second iteration (downscaled frame, before combining with first iteration) disparity map. Useful for debugging/fine tuning.
variable
Output debugDispCostDump
Outputs ImgFrame message that carries cost dump of disparity map. Useful for debugging/fine tuning.
variable
Output confidenceMap
Outputs ImgFrame message that carries RAW8 confidence map. Lower values mean lower confidence of the calculated disparity value. RGB alignment, left-right check or any postprocessing (e.g., median filter) is not performed on confidence map.
function
StereoDepth()
inline function
std::shared_ptr< StereoDepth > build(Node::Output & left, Node::Output & right, PresetMode presetMode)
function
std::shared_ptr< StereoDepth > build(bool autoCreateCameras, PresetMode presetMode, std::pair< int, int > size, std::optional< float > fps)
Create StereoDepth node. Note that this API is global and if used autocreated cameras can't be reused.
Parameters
  • autoCreateCameras: If true, will create left and right nodes if they don't exist
  • presetMode: Preset mode for stereo depth
function
void loadMeshFiles(const std::filesystem::path & pathLeft, const std::filesystem::path & pathRight)
Specify local filesystem paths to the mesh calibration files for 'left' and 'right' inputs.When a mesh calibration is set, it overrides the camera intrinsics/extrinsics matrices. Overrides useHomographyRectification behavior. Mesh format: a sequence of (y,x) points as 'float' with coordinates from the input image to be mapped in the output. The mesh can be subsampled, configured by With a 1280x800 resolution and the default (16,16) step, the required mesh size is:width: 1280 / 16 + 1 = 81height: 800 / 16 + 1 = 51
function
void loadMeshData(const std::vector< std::uint8_t > & dataLeft, const std::vector< std::uint8_t > & dataRight)
Specify mesh calibration data for 'left' and 'right' inputs, as vectors of bytes. Overrides useHomographyRectification behavior. See
function
void setMeshStep(int width, int height)
Set the distance between mesh points. Default: (16, 16)
function
void setInputResolution(int width, int height)
Specify input resolution sizeOptional if MonoCamera exists, otherwise necessary
function
void setInputResolution(std::tuple< int, int > resolution)
Specify input resolution sizeOptional if MonoCamera exists, otherwise necessary
function
void setOutputSize(int width, int height)
Specify disparity/depth output resolution size, implemented by scaling.Currently only applicable when aligning to RGB camera
function
void setOutputKeepAspectRatio(bool keep)
Specifies whether the frames resized by
function
void setDepthAlign(Properties::DepthAlign align)
Parameters
  • align: Set the disparity/depth alignment: centered (between the 'left' and 'right' inputs), or from the perspective of a rectified output stream
function
void setDepthAlign(CameraBoardSocket camera)
Parameters
  • camera: Set the camera from whose perspective the disparity/depth will be aligned
function
void setRectification(bool enable)
Rectify input images or not.
function
void setLeftRightCheck(bool enable)
Computes and combines disparities in both L-R and R-L directions, and combine them.For better occlusion handling, discarding invalid disparity values
function
void setSubpixel(bool enable)
Computes disparity with sub-pixel interpolation (3 fractional bits by default).Suitable for long range. Currently incompatible with extended disparity
function
void setSubpixelFractionalBits(int subpixelFractionalBits)
Number of fractional bits for subpixel mode. Default value: 3. Valid values: 3,4,5. Defines the number of fractional disparities: 2^x. Median filter postprocessing is supported only for 3 fractional bits.
function
void setExtendedDisparity(bool enable)
Disparity range increased from 0-95 to 0-190, combined from full resolution and downscaled images.Suitable for short range objects. Currently incompatible with sub-pixel disparity
function
void setRectifyEdgeFillColor(int color)
Fill color for missing data at frame edges
Parameters
  • color: Grayscale 0..255, or -1 to replicate pixels
function
void setRuntimeModeSwitch(bool enable)
Enable runtime stereo mode switch, e.g. from standard to LR-check. Note: when enabled resources allocated for worst case to enable switching to any mode.
function
void setNumFramesPool(int numFramesPool)
Specify number of frames in pool.
Parameters
  • numFramesPool: How many frames should the pool have
function
void setPostProcessingHardwareResources(int numShaves, int numMemorySlices)
Specify allocated hardware resources for stereo depth. Suitable only to increase post processing runtime.
Parameters
  • numShaves: Number of shaves.
  • numMemorySlices: Number of memory slices.
function
void setDefaultProfilePreset(PresetMode mode)
Sets a default preset based on specified option.
Parameters
  • mode: Stereo depth preset mode
function
void useHomographyRectification(bool useHomographyRectification)
Use 3x3 homography matrix for stereo rectification instead of sparse mesh generated on device. Default behaviour is AUTO, for lenses with FOV over 85 degrees sparse mesh is used, otherwise 3x3 homography. If custom mesh data is provided through loadMeshData or loadMeshFiles this option is ignored.
Parameters
  • useHomographyRectification: true: 3x3 homography matrix generated from calibration data is used for stereo rectification, can't correct lens distortion. false: sparse mesh is generated on-device from calibration data with mesh step specified with setMeshStep (Default: (16, 16)), can correct lens distortion. Implementation for generating the mesh is same as opencv's initUndistortRectifyMap function. Only the first 8 distortion coefficients are used from calibration data.
function
void enableDistortionCorrection(bool enableDistortionCorrection)
Equivalent to useHomographyRectification(!enableDistortionCorrection)
function
void setFrameSync(bool enableFrameSync)
Whether to enable frame syncing inside stereo node or not. Suitable if inputs are known to be synced.
function
void setBaseline(float baseline)
Override baseline from calibration. Used only in disparity to depth conversion. Units are centimeters.
function
void setFocalLength(float focalLength)
Override focal length from calibration. Used only in disparity to depth conversion. Units are pixels.
function
void setDisparityToDepthUseSpecTranslation(bool specTranslation)
Use baseline information for disparity to depth conversion from specs (design data) or from calibration. Default: true
function
void setRectificationUseSpecTranslation(bool specTranslation)
Obtain rectification matrices using spec translation (design data) or from calibration in calculations. Should be used only for debugging. Default: false
function
void setDepthAlignmentUseSpecTranslation(bool specTranslation)
Use baseline information for depth alignment from specs (design data) or from calibration. Default: true
function
void setAlphaScaling(float alpha)
Free scaling parameter between 0 (when all the pixels in the undistorted image are valid) and 1 (when all the source image pixels are retained in the undistorted image). On some high distortion lenses, and/or due to rectification (image rotated) invalid areas may appear even with alpha=0, in these cases alpha < 0.0 helps removing invalid areas. See getOptimalNewCameraMatrix from opencv for more details.
enum

std::uint32_t PresetMode

Preset modes for stereo depth.
enumerator
FAST_ACCURACY
enumerator
FAST_DENSITY
enumerator
DEFAULT
enumerator
FACE
enumerator
HIGH_DETAIL
enumerator
ROBOTICS
enumerator
DENSITY
enumerator
ACCURACY
enum

dai::StereoDepthConfig::MedianFilter MedianFilter

class

dai::StereoDepthConfig

#include StereoDepthConfig.hpp
variable
AlgorithmControl algorithmControl
Controls the flow of stereo algorithm - left-right check, subpixel etc.
variable
PostProcessing postProcessing
Controls the postprocessing of disparity and/or depth map.
variable
CensusTransform censusTransform
Census transform settings.
variable
CostMatching costMatching
Cost matching settings.
variable
CostAggregation costAggregation
Cost aggregation settings.
variable
ConfidenceMetrics confidenceMetrics
Confidence metrics settings.
variable
dai::ProcessorType filtersBackend
function
StereoDepthConfig()
Construct StereoDepthConfig message.
function
~StereoDepthConfig()
function
StereoDepthConfig & setDepthAlign(AlgorithmControl::DepthAlign align)
Parameters
  • align: Set the disparity/depth alignment: centered (between the 'left' and 'right' inputs), or from the perspective of a rectified output stream
function
StereoDepthConfig & setConfidenceThreshold(int confThr)
Confidence threshold for disparity calculation
Parameters
  • confThr: Confidence threshold value 0..255
function
int getConfidenceThreshold()
Get confidence threshold for disparity calculation
function
StereoDepthConfig & setMedianFilter(MedianFilter median)
Parameters
  • median: Set kernel size for disparity/depth median filtering, or disable
function
MedianFilter getMedianFilter()
Get median filter setting
function
StereoDepthConfig & setBilateralFilterSigma(uint16_t sigma)
A larger value of the parameter means that farther colors within the pixel neighborhood will be mixed together, resulting in larger areas of semi-equal color.
Parameters
  • sigma: Set sigma value for 5x5 bilateral filter. 0..65535
function
uint16_t getBilateralFilterSigma()
Get sigma value for 5x5 bilateral filter
function
StereoDepthConfig & setLeftRightCheckThreshold(int threshold)
Parameters
  • threshold: Set threshold for left-right, right-left disparity map combine, 0..255
function
int getLeftRightCheckThreshold()
Get threshold for left-right check combine
function
StereoDepthConfig & setLeftRightCheck(bool enable)
Computes and combines disparities in both L-R and R-L directions, and combine them.For better occlusion handling, discarding invalid disparity values
function
bool getLeftRightCheck()
Get left-right check setting
function
StereoDepthConfig & setExtendedDisparity(bool enable)
Disparity range increased from 95 to 190, combined from full resolution and downscaled images. Suitable for short range objects
function
bool getExtendedDisparity()
Get extended disparity setting
function
StereoDepthConfig & setSubpixel(bool enable)
Computes disparity with sub-pixel interpolation (3 fractional bits by default).Suitable for long range. Currently incompatible with extended disparity
function
bool getSubpixel()
Get subpixel setting
function
StereoDepthConfig & setSubpixelFractionalBits(int subpixelFractionalBits)
Number of fractional bits for subpixel mode. Default value: 3. Valid values: 3,4,5. Defines the number of fractional disparities: 2^x. Median filter postprocessing is supported only for 3 fractional bits.
function
int getSubpixelFractionalBits()
Get number of fractional bits for subpixel mode
function
StereoDepthConfig & setDepthUnit(AlgorithmControl::DepthUnit depthUnit)
Set depth unit of depth map.Meter, centimeter, millimeter, inch, foot or custom unit is available.
function
AlgorithmControl::DepthUnit getDepthUnit()
Get depth unit of depth map.
function
StereoDepthConfig & setCustomDepthUnitMultiplier(float multiplier)
Set custom depth unit multiplier relative to 1 meter.
function
float getCustomDepthUnitMultiplier()
Get custom depth unit multiplier relative to 1 meter.
function
StereoDepthConfig & setDisparityShift(int disparityShift)
Shift input frame by a number of pixels to increase minimum depth. For example shifting by 48 will change effective disparity search range from (0,95] to [48,143]. An alternative approach to reducing the minZ. We normally only recommend doing this when it is known that there will be no objects farther away than MaxZ, such as having a depth camera mounted above a table pointing down at the table surface.
function
StereoDepthConfig & setNumInvalidateEdgePixels(int32_t numInvalidateEdgePixels)
Invalidate X amount of pixels at the edge of disparity frame. For right and center alignment X pixels will be invalidated from the right edge, for left alignment from the left edge.
function
StereoDepthConfig & setFiltersComputeBackend(dai::ProcessorType filtersBackend)
Set filters compute backend
function
dai::ProcessorType getFiltersComputeBackend()
Get filters compute backend
function
float getMaxDisparity()
Useful for normalization of the disparity map.
Returns
Maximum disparity value that the node can return
function
void serialize(std::vector< std::uint8_t > & metadata, DatatypeEnum & datatype)
inline function
DatatypeEnum getDatatype()
function
struct

dai::StereoDepthConfig::AlgorithmControl

variable
DepthAlign depthAlign
Set the disparity/depth alignment to the perspective of a rectified output, or center it
variable
DepthUnit depthUnit
Measurement unit for depth data. Depth data is integer value, multiple of depth unit.
variable
float customDepthUnitMultiplier
Custom depth unit multiplier, if custom depth unit is enabled, relative to 1 meter. A multiplier of 1000 effectively means depth unit in millimeter.
variable
bool enableLeftRightCheck
Computes and combines disparities in both L-R and R-L directions, and combine them. For better occlusion handling
variable
bool enableSwLeftRightCheck
Enables software left right check. Applicable to RVC4 only.
variable
bool enableExtended
Disparity range increased from 95 to 190, combined from full resolution and downscaled images. Suitable for short range objects
variable
bool enableSubpixel
Computes disparity with sub-pixel interpolation (5 fractional bits), suitable for long range
variable
std::int32_t leftRightCheckThreshold
Left-right check threshold for left-right, right-left disparity map combine, 0..128 Used only when left-right check mode is enabled. Defines the maximum difference between the confidence of pixels from left-right and right-left confidence maps
variable
std::int32_t subpixelFractionalBits
Number of fractional bits for subpixel modeValid values: 3,4,5Defines the number of fractional disparities: 2^xMedian filter postprocessing is supported only for 3 fractional bits
variable
std::int32_t disparityShift
Shift input frame by a number of pixels to increase minimum depth. For example shifting by 48 will change effective disparity search range from (0,95] to [48,143]. An alternative approach to reducing the minZ. We normally only recommend doing this when it is known that there will be no objects farther away than MaxZ, such as having a depth camera mounted above a table pointing down at the table surface.
variable
std::optional< float > centerAlignmentShiftFactor
variable
std::int32_t numInvalidateEdgePixels
Invalidate X amount of pixels at the edge of disparity frame. For right and center alignment X pixels will be invalidated from the right edge, for left alignment from the left edge.
function
enum

int32_t DepthAlign

Align the disparity/depth to the perspective of a rectified output, or center it
enumerator
AUTO
enumerator
RECTIFIED_RIGHT
enumerator
RECTIFIED_LEFT
enumerator
CENTER
enumerator
RIGHT
enumerator
LEFT
enum

dai::DepthUnit DepthUnit

struct

dai::StereoDepthConfig::CensusTransform

#include StereoDepthConfig.hpp
variable
KernelSize kernelSize
Census transform kernel size.
variable
uint64_t kernelMask
Census transform mask, default - auto, mask is set based on resolution and kernel size. Disabled for 400p input resolution. Enabled for 720p. 0XA82415 for 5x5 census transform kernel. 0XAA02A8154055 for 7x7 census transform kernel. 0X2AA00AA805540155 for 7x9 census transform kernel. Empirical values.
variable
bool enableMeanMode
If enabled, each pixel in the window is compared with the mean window value instead of the central pixel.
variable
uint32_t threshold
Census transform comparison threshold value.
variable
int8_t noiseThresholdOffset
Used to reduce small fixed levels of noise across all luminance values in the current image. Valid range is [0,127]. Default value is 0.
variable
int8_t noiseThresholdScale
Used to reduce noise values that increase with luminance in the current image. Valid range is [-128,127]. Default value is 0.
function
enum

std::int32_t KernelSize

Census transform kernel size possible values.
enumerator
AUTO
enumerator
KERNEL_5x5
enumerator
KERNEL_7x7
enumerator
KERNEL_7x9
struct

dai::StereoDepthConfig::ConfidenceMetrics

variable
uint8_t occlusionConfidenceWeight
Weight used with occlusion estimation to generate final confidence map. Valid range is [0,32]
variable
uint8_t motionVectorConfidenceWeight
Weight used with local neighborhood motion vector variance estimation to generate final confidence map. Valid range is [0,32].
variable
uint8_t motionVectorConfidenceThreshold
Threshold offset for MV variance in confidence generation. A value of 0 allows most variance. Valid range is [0,3].
variable
uint8_t flatnessConfidenceWeight
Weight used with flatness estimation to generate final confidence map. Valid range is [0,32].
variable
uint8_t flatnessConfidenceThreshold
Threshold for flatness check in SGM block. Valid range is [1,7].
variable
bool flatnessOverride
Flag to indicate whether final confidence value will be overidden by flatness value. Valid range is {true,false}.
function
struct

dai::StereoDepthConfig::CostAggregation

#include StereoDepthConfig.hpp
variable
uint8_t divisionFactor
Cost calculation linear equation parameters.
variable
uint16_t horizontalPenaltyCostP1
Horizontal P1 penalty cost parameter.
variable
uint16_t horizontalPenaltyCostP2
Horizontal P2 penalty cost parameter.
variable
uint16_t verticalPenaltyCostP1
Vertical P1 penalty cost parameter.
variable
uint16_t verticalPenaltyCostP2
Vertical P2 penalty cost parameter.
variable
P1Config p1Config
variable
P2Config p2Config
function
struct

dai::StereoDepthConfig::CostAggregation::P1Config

#include StereoDepthConfig.hpp
variable
bool enableAdaptive
Used to disable/enable adaptive penalty.
variable
uint8_t defaultValue
Used as the default penalty value when nAdapEnable is disabled. A bigger value enforces higher smoothness and reduced noise at the cost of lower edge accuracy. This value must be smaller than P2 default penalty. Valid range is [10,50].
variable
uint8_t edgeValue
Penalty value on edges when nAdapEnable is enabled. A smaller penalty value permits higher change in disparity. This value must be smaller than or equal to P2 edge penalty. Valid range is [10,50].
variable
uint8_t smoothValue
Penalty value on low texture regions when nAdapEnable is enabled. A smaller penalty value permits higher change in disparity. This value must be smaller than or equal to P2 smoothness penalty. Valid range is [10,50].
variable
uint8_t edgeThreshold
Threshold value on edges when nAdapEnable is enabled. A bigger value permits higher neighboring feature dissimilarity tolerance. This value is shared with P2 penalty configuration. Valid range is [8,16].
variable
uint8_t smoothThreshold
Threshold value on low texture regions when nAdapEnable is enabled. A bigger value permits higher neighboring feature dissimilarity tolerance. This value is shared with P2 penalty configuration. Valid range is [2,12].
function
struct

dai::StereoDepthConfig::CostAggregation::P2Config

#include StereoDepthConfig.hpp
variable
bool enableAdaptive
Used to disable/enable adaptive penalty.
variable
uint8_t defaultValue
Used as the default penalty value when nAdapEnable is disabled. A bigger value enforces higher smoothness and reduced noise at the cost of lower edge accuracy. This value must be larger than P1 default penalty. Valid range is [20,100].
variable
uint8_t edgeValue
Penalty value on edges when nAdapEnable is enabled. A smaller penalty value permits higher change in disparity. This value must be larger than or equal to P1 edge penalty. Valid range is [20,100].
variable
uint8_t smoothValue
Penalty value on low texture regions when nAdapEnable is enabled. A smaller penalty value permits higher change in disparity. This value must be larger than or equal to P1 smoothness penalty. Valid range is [20,100].
function
struct

dai::StereoDepthConfig::CostMatching

#include StereoDepthConfig.hpp
variable
DisparityWidth disparityWidth
Disparity search range, default 96 pixels.
variable
bool enableCompanding
Disparity companding using sparse matching. Matching pixel by pixel for N disparities. Matching every 2nd pixel for M disparitites. Matching every 4th pixel for T disparities. In case of 96 disparities: N=48, M=32, T=16. This way the search range is extended to 176 disparities, by sparse matching. Note: when enabling this flag only depth map will be affected, disparity map is not.
variable
uint8_t invalidDisparityValue
Used only for debug purposes, SW postprocessing handled only invalid value of 0 properly.
variable
uint8_t confidenceThreshold
Disparities with confidence value over this threshold are accepted.
variable
bool enableSwConfidenceThresholding
Enable software confidence thresholding. Applicable to RVC4 only.
variable
LinearEquationParameters linearEquationParameters
Cost calculation linear equation parameters.
function
struct

dai::StereoDepthConfig::CostMatching::LinearEquationParameters

#include StereoDepthConfig.hpp
variable
uint8_t alpha
variable
uint8_t beta
variable
uint8_t threshold
function
DEPTHAI_SERIALIZE(LinearEquationParameters, alpha, beta, threshold)
enum

std::uint32_t DisparityWidth

Disparity search range: 64 or 96 pixels are supported by the HW.
enumerator
DISPARITY_64
enumerator
DISPARITY_96
struct

dai::StereoDepthConfig::PostProcessing

#include StereoDepthConfig.hpp
variable
std::array< Filter, 5 > filteringOrder
Order of filters to be applied if filtering is enabled.
variable
MedianFilter median
Set kernel size for disparity/depth median filtering, or disable
variable
std::int16_t bilateralSigmaValue
Sigma value for bilateral filter. 0 means disabled. A larger value of the parameter means that farther colors within the pixel neighborhood will be mixed together.
variable
SpatialFilter spatialFilter
Edge-preserving filtering: This type of filter will smooth the depth noise while attempting to preserve edges.
variable
TemporalFilter temporalFilter
Temporal filtering with optional persistence.
variable
ThresholdFilter thresholdFilter
Threshold filtering. Filters out distances outside of a given interval.
variable
BrightnessFilter brightnessFilter
Brightness filtering. If input frame pixel is too dark or too bright, disparity will be invalidated. The idea is that for too dark/too bright pixels we have low confidence, since that area was under/over exposed and details were lost.
variable
SpeckleFilter speckleFilter
Speckle filtering. Removes speckle noise.
variable
DecimationFilter decimationFilter
Decimation filter. Reduces disparity/depth map x/y complexity, reducing runtime complexity for other filters.
variable
HoleFilling holeFilling
variable
AdaptiveMedianFilter adaptiveMedianFilter
function
struct

dai::StereoDepthConfig::PostProcessing::AdaptiveMedianFilter

variable
bool enable
Flag to enable adaptive median filtering for a final pass of filtering on low confidence pixels.
variable
uint8_t confidenceThreshold
Confidence threshold for adaptive median filtering. Should be less than nFillConfThresh value used in evaDfsHoleFillConfig. Valid range is [0,255].
function
struct

dai::StereoDepthConfig::PostProcessing::BrightnessFilter

#include StereoDepthConfig.hpp
variable
std::int32_t minBrightness
Minimum pixel brightness. If input pixel is less or equal than this value the depth value is invalidated.
variable
std::int32_t maxBrightness
Maximum range in depth units. If input pixel is less or equal than this value the depth value is invalidated.
function
struct

dai::StereoDepthConfig::PostProcessing::DecimationFilter

#include StereoDepthConfig.hpp
variable
std::uint32_t decimationFactor
Decimation factor. Valid values are 1,2,3,4. Disparity/depth map x/y resolution will be decimated with this value.
variable
DecimationMode decimationMode
Decimation algorithm type.
function
enum

int32_t DecimationMode

Decimation algorithm type.
enumerator
PIXEL_SKIPPING
enumerator
NON_ZERO_MEDIAN
enumerator
NON_ZERO_MEAN
struct

dai::StereoDepthConfig::PostProcessing::HoleFilling

variable
bool enable
Flag to enable post-processing hole-filling.
variable
uint8_t highConfidenceThreshold
Pixels with confidence higher than this value are used to calculate an average disparity per superpixel. Valid range is [1,255]
variable
uint8_t fillConfidenceThreshold
Pixels with confidence below this value will be filled with the average disparity of their corresponding superpixel. Valid range is [1,255].
variable
uint8_t minValidDisparity
Represents the required percentange of pixels with confidence value above nHighConfThresh that are used to calculate average disparity per superpixel, where 1 means 50% or half, 2 means 25% or a quarter and 3 means 12.5% or an eighth. If the required number of pixels are not found, the holes will not be filled.
variable
bool invalidateDisparities
If enabled, sets to 0 the disparity of pixels with confidence below nFillConfThresh, which did not pass nMinValidPixels criteria. Valid range is {true, false}.
function
struct

dai::StereoDepthConfig::PostProcessing::ThresholdFilter

#include StereoDepthConfig.hpp
variable
std::int32_t minRange
Minimum range in depth units. Depth values under this value are invalidated.
variable
std::int32_t maxRange
Maximum range in depth units. Depth values over this value are invalidated.
function
DEPTHAI_SERIALIZE(ThresholdFilter, minRange, maxRange)
enum

int32_t Filter

enumerator
NONE
enumerator
DECIMATION
enumerator
SPECKLE
enumerator
MEDIAN
enumerator
SPATIAL
enumerator
TEMPORAL
enumerator
FILTER_COUNT
enum

enum

enum

enum

filters::params::MedianFilter MedianFilter

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