Stereo Depth from host

This example shows depth map from host using stereo images. There are 3 depth modes which you can select inside the code:

  1. lr_check: used for better occlusion handling. For more information click here

  2. extended_disparity: suitable for short range objects. For more information click here

  3. subpixel: suitable for long range. For more information click here

Otherwise a median with kernel_7x7 is activated.

Similar samples:

Setup

Please run the install script to download all required dependencies. Please note that this script must be ran from git context, so you have to download the depthai-python repository first and then run the script

git clone https://github.com/luxonis/depthai-python.git
cd depthai-python/examples
python3 install_requirements.py

For additional information, please follow installation guide

This example also requires dataset folder - you can download it from here

Source code

Also available on GitHub

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#!/usr/bin/env python3

import cv2
import numpy as np
import depthai as dai
from time import sleep
import datetime
import argparse
from pathlib import Path
import math

datasetDefault = str((Path(__file__).parent / Path('../models/dataset')).resolve().absolute())
parser = argparse.ArgumentParser()
parser.add_argument('-dataset', nargs='?', help="Path to recorded frames", default=datasetDefault)
parser.add_argument('-debug', "--debug", action="store_true", help="Enable debug outputs.")
parser.add_argument('-dumpdispcost', "--dumpdisparitycostvalues", action="store_true", help="Dumps the disparity cost values for each disparity range. 96 byte for each pixel.")
args = parser.parse_args()

if not Path(datasetDefault).exists():
    import sys
    raise FileNotFoundError(f'Required file/s not found, please run "{sys.executable} install_requirements.py"')



class StereoConfigHandler:

    class Trackbar:
        def __init__(self, trackbarName, windowName, minValue, maxValue, defaultValue, handler):
            self.min = minValue
            self.max = maxValue
            self.windowName = windowName
            self.trackbarName = trackbarName
            cv2.createTrackbar(trackbarName, windowName, minValue, maxValue, handler)
            cv2.setTrackbarPos(trackbarName, windowName, defaultValue)

        def set(self, value):
            if value < self.min:
                value = self.min
                print(f'{self.trackbarName} min value is {self.min}')
            if value > self.max:
                value = self.max
                print(f'{self.trackbarName} max value is {self.max}')
            cv2.setTrackbarPos(self.trackbarName, self.windowName, value)

    class CensusMaskHandler:

        stateColor = [(0, 0, 0), (255, 255, 255)]
        gridHeight = 50
        gridWidth = 50

        def fillRectangle(self, row, col):
            src = self.gridList[row][col]["topLeft"]
            dst = self.gridList[row][col]["bottomRight"]

            stateColor = self.stateColor[1] if self.gridList[row][col]["state"] else self.stateColor[0]
            self.changed = True

            cv2.rectangle(self.gridImage, src, dst, stateColor, -1)
            cv2.imshow(self.windowName, self.gridImage)


        def clickCallback(self, event, x, y, flags, param):
            if event == cv2.EVENT_LBUTTONDOWN:
                col = x * (self.gridSize[1]) // self.width
                row = y * (self.gridSize[0]) // self.height
                self.gridList[row][col]["state"] = not self.gridList[row][col]["state"]
                self.fillRectangle(row, col)


        def __init__(self, windowName, gridSize):
            self.gridSize = gridSize
            self.windowName = windowName
            self.changed = False

            cv2.namedWindow(self.windowName)

            self.width = StereoConfigHandler.CensusMaskHandler.gridWidth * self.gridSize[1]
            self.height = StereoConfigHandler.CensusMaskHandler.gridHeight * self.gridSize[0]

            self.gridImage = np.zeros((self.height + 50, self.width, 3), np.uint8)

            cv2.putText(self.gridImage, "Click on grid to change mask!", (0, self.height+20), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255, 255, 255))
            cv2.putText(self.gridImage, "White: ON   |   Black: OFF", (0, self.height+40), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255, 255, 255))

            self.gridList = [[dict() for _ in range(self.gridSize[1])] for _ in range(self.gridSize[0])]

            for row in range(self.gridSize[0]):
                rowFactor = self.height // self.gridSize[0]
                srcY = row*rowFactor + 1
                dstY = (row+1)*rowFactor - 1
                for col in range(self.gridSize[1]):
                    colFactor = self.width // self.gridSize[1]
                    srcX = col*colFactor + 1
                    dstX = (col+1)*colFactor - 1
                    src = (srcX, srcY)
                    dst = (dstX, dstY)
                    self.gridList[row][col]["topLeft"] = src
                    self.gridList[row][col]["bottomRight"] = dst
                    self.gridList[row][col]["state"] = False
                    self.fillRectangle(row, col)

            cv2.setMouseCallback(self.windowName, self.clickCallback)
            cv2.imshow(self.windowName, self.gridImage)

        def getMask(self) -> np.uint64:
            mask = np.uint64(0)
            for row in range(self.gridSize[0]):
                for col in range(self.gridSize[1]):
                    if self.gridList[row][col]["state"]:
                        pos = row*self.gridSize[1] + col
                        mask = np.bitwise_or(mask, np.uint64(1) << np.uint64(pos))

            return mask

        def setMask(self, _mask: np.uint64):
            mask = np.uint64(_mask)
            for row in range(self.gridSize[0]):
                for col in range(self.gridSize[1]):
                    pos = row*self.gridSize[1] + col
                    if np.bitwise_and(mask, np.uint64(1) << np.uint64(pos)):
                        self.gridList[row][col]["state"] = True
                    else:
                        self.gridList[row][col]["state"] = False

                    self.fillRectangle(row, col)

        def isChanged(self):
            changed = self.changed
            self.changed = False
            return changed

        def destroyWindow(self):
            cv2.destroyWindow(self.windowName)


    censusMaskHandler = None
    newConfig = False
    config = None
    trSigma = list()
    trConfidence = list()
    trLrCheck = list()
    trFractionalBits = list()
    trLineqAlpha = list()
    trLineqBeta = list()
    trLineqThreshold = list()
    trCostAggregationP1 = list()
    trCostAggregationP2 = list()
    trTemporalAlpha = list()
    trTemporalDelta = list()
    trThresholdMinRange = list()
    trThresholdMaxRange = list()
    trSpeckleRange = list()
    trSpatialAlpha = list()
    trSpatialDelta = list()
    trSpatialHoleFilling = list()
    trSpatialNumIterations = list()
    trDecimationFactor = list()

    def trackbarSigma(value):
        StereoConfigHandler.config.postProcessing.bilateralSigmaValue = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trSigma:
            tr.set(value)

    def trackbarConfidence(value):
        StereoConfigHandler.config.costMatching.confidenceThreshold = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trConfidence:
            tr.set(value)

    def trackbarLrCheckThreshold(value):
        StereoConfigHandler.config.algorithmControl.leftRightCheckThreshold = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trLrCheck:
            tr.set(value)

    def trackbarFractionalBits(value):
        StereoConfigHandler.config.algorithmControl.subpixelFractionalBits = value
        for tr in StereoConfigHandler.trFractionalBits:
            tr.set(value)

    def trackbarLineqAlpha(value):
        StereoConfigHandler.config.costMatching.linearEquationParameters.alpha = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trLineqAlpha:
            tr.set(value)

    def trackbarLineqBeta(value):
        StereoConfigHandler.config.costMatching.linearEquationParameters.beta = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trLineqBeta:
            tr.set(value)

    def trackbarLineqThreshold(value):
        StereoConfigHandler.config.costMatching.linearEquationParameters.threshold = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trLineqThreshold:
            tr.set(value)

    def trackbarCostAggregationP1(value):
        StereoConfigHandler.config.costAggregation.horizontalPenaltyCostP1 = value
        StereoConfigHandler.config.costAggregation.verticalPenaltyCostP1 = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trCostAggregationP1:
            tr.set(value)

    def trackbarCostAggregationP2(value):
        StereoConfigHandler.config.costAggregation.horizontalPenaltyCostP2 = value
        StereoConfigHandler.config.costAggregation.verticalPenaltyCostP2 = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trCostAggregationP2:
            tr.set(value)

    def trackbarTemporalFilterAlpha(value):
        StereoConfigHandler.config.postProcessing.temporalFilter.alpha = value / 100.
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trTemporalAlpha:
            tr.set(value)

    def trackbarTemporalFilterDelta(value):
        StereoConfigHandler.config.postProcessing.temporalFilter.delta = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trTemporalDelta:
            tr.set(value)

    def trackbarSpatialFilterAlpha(value):
        StereoConfigHandler.config.postProcessing.spatialFilter.alpha = value / 100.
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trSpatialAlpha:
            tr.set(value)

    def trackbarSpatialFilterDelta(value):
        StereoConfigHandler.config.postProcessing.spatialFilter.delta = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trSpatialDelta:
            tr.set(value)

    def trackbarSpatialFilterHoleFillingRadius(value):
        StereoConfigHandler.config.postProcessing.spatialFilter.holeFillingRadius = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trSpatialHoleFilling:
            tr.set(value)

    def trackbarSpatialFilterNumIterations(value):
        StereoConfigHandler.config.postProcessing.spatialFilter.numIterations = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trSpatialNumIterations:
            tr.set(value)

    def trackbarThresholdMinRange(value):
        StereoConfigHandler.config.postProcessing.thresholdFilter.minRange = value * 1000
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trThresholdMinRange:
            tr.set(value)

    def trackbarThresholdMaxRange(value):
        StereoConfigHandler.config.postProcessing.thresholdFilter.maxRange = value * 1000
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trThresholdMaxRange:
            tr.set(value)

    def trackbarSpeckleRange(value):
        StereoConfigHandler.config.postProcessing.speckleFilter.speckleRange = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trSpeckleRange:
            tr.set(value)

    def trackbarDecimationFactor(value):
        StereoConfigHandler.config.postProcessing.decimationFilter.decimationFactor = value
        StereoConfigHandler.newConfig = True
        for tr in StereoConfigHandler.trDecimationFactor:
            tr.set(value)

    def handleKeypress(key, stereoDepthConfigInQueue):
        if key == ord('m'):
            StereoConfigHandler.newConfig = True
            medianSettings = [dai.MedianFilter.MEDIAN_OFF, dai.MedianFilter.KERNEL_3x3, dai.MedianFilter.KERNEL_5x5, dai.MedianFilter.KERNEL_7x7]
            currentMedian = StereoConfigHandler.config.postProcessing.median
            nextMedian = medianSettings[(medianSettings.index(currentMedian)+1) % len(medianSettings)]
            print(f"Changing median to {nextMedian.name} from {currentMedian.name}")
            StereoConfigHandler.config.postProcessing.median = nextMedian
        if key == ord('w'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.postProcessing.spatialFilter.enable = not StereoConfigHandler.config.postProcessing.spatialFilter.enable
            state = "on" if StereoConfigHandler.config.postProcessing.spatialFilter.enable else "off"
            print(f"Spatial filter {state}")
        if key == ord('t'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.postProcessing.temporalFilter.enable = not StereoConfigHandler.config.postProcessing.temporalFilter.enable
            state = "on" if StereoConfigHandler.config.postProcessing.temporalFilter.enable else "off"
            print(f"Temporal filter {state}")
        if key == ord('s'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.postProcessing.speckleFilter.enable = not StereoConfigHandler.config.postProcessing.speckleFilter.enable
            state = "on" if StereoConfigHandler.config.postProcessing.speckleFilter.enable else "off"
            print(f"Speckle filter {state}")
        if key == ord('r'):
            StereoConfigHandler.newConfig = True
            temporalSettings = [dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.PERSISTENCY_OFF,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_8_OUT_OF_8,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_2_IN_LAST_3,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_2_IN_LAST_4,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_2_OUT_OF_8,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_1_IN_LAST_2,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_1_IN_LAST_5,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.VALID_1_IN_LAST_8,
            dai.StereoDepthConfig.PostProcessing.TemporalFilter.PersistencyMode.PERSISTENCY_INDEFINITELY,
            ]
            currentTemporal = StereoConfigHandler.config.postProcessing.temporalFilter.persistencyMode
            nextTemporal = temporalSettings[(temporalSettings.index(currentTemporal)+1) % len(temporalSettings)]
            print(f"Changing temporal persistency to {nextTemporal.name} from {currentTemporal.name}")
            StereoConfigHandler.config.postProcessing.temporalFilter.persistencyMode = nextTemporal
        if key == ord('n'):
            StereoConfigHandler.newConfig = True
            decimationSettings = [dai.StereoDepthConfig.PostProcessing.DecimationFilter.DecimationMode.PIXEL_SKIPPING,
            dai.StereoDepthConfig.PostProcessing.DecimationFilter.DecimationMode.NON_ZERO_MEDIAN,
            dai.StereoDepthConfig.PostProcessing.DecimationFilter.DecimationMode.NON_ZERO_MEAN,
            ]
            currentDecimation = StereoConfigHandler.config.postProcessing.decimationFilter.decimationMode
            nextDecimation = decimationSettings[(decimationSettings.index(currentDecimation)+1) % len(decimationSettings)]
            print(f"Changing decimation mode to {nextDecimation.name} from {currentDecimation.name}")
            StereoConfigHandler.config.postProcessing.decimationFilter.decimationMode = nextDecimation
        if key == ord('a'):
            StereoConfigHandler.newConfig = True
            alignmentSettings = [dai.StereoDepthConfig.AlgorithmControl.DepthAlign.RECTIFIED_RIGHT,
            dai.StereoDepthConfig.AlgorithmControl.DepthAlign.RECTIFIED_LEFT,
            dai.StereoDepthConfig.AlgorithmControl.DepthAlign.CENTER,
            ]
            currentAlignment = StereoConfigHandler.config.algorithmControl.depthAlign
            nextAlignment = alignmentSettings[(alignmentSettings.index(currentAlignment)+1) % len(alignmentSettings)]
            print(f"Changing alignment mode to {nextAlignment.name} from {currentAlignment.name}")
            StereoConfigHandler.config.algorithmControl.depthAlign = nextAlignment
        elif key == ord('c'):
            StereoConfigHandler.newConfig = True
            censusSettings = [dai.StereoDepthConfig.CensusTransform.KernelSize.AUTO, dai.StereoDepthConfig.CensusTransform.KernelSize.KERNEL_5x5, dai.StereoDepthConfig.CensusTransform.KernelSize.KERNEL_7x7, dai.StereoDepthConfig.CensusTransform.KernelSize.KERNEL_7x9]
            currentCensus = StereoConfigHandler.config.censusTransform.kernelSize
            nextCensus = censusSettings[(censusSettings.index(currentCensus)+1) % len(censusSettings)]
            if nextCensus != dai.StereoDepthConfig.CensusTransform.KernelSize.AUTO:
                censusGridSize = [(5,5), (7,7), (7,9)]
                censusDefaultMask = [np.uint64(0XA82415), np.uint64(0XAA02A8154055), np.uint64(0X2AA00AA805540155)]
                censusGrid = censusGridSize[nextCensus]
                censusMask = censusDefaultMask[nextCensus]
                StereoConfigHandler.censusMaskHandler = StereoConfigHandler.CensusMaskHandler("Census mask", censusGrid)
                StereoConfigHandler.censusMaskHandler.setMask(censusMask)
            else:
                print("Census mask config is not available in AUTO census kernel mode. Change using the 'c' key")
                StereoConfigHandler.config.censusTransform.kernelMask = 0
                StereoConfigHandler.censusMaskHandler.destroyWindow()
            print(f"Changing census transform to {nextCensus.name} from {currentCensus.name}")
            StereoConfigHandler.config.censusTransform.kernelSize = nextCensus
        elif key == ord('d'):
            StereoConfigHandler.newConfig = True
            dispRangeSettings = [dai.StereoDepthConfig.CostMatching.DisparityWidth.DISPARITY_64, dai.StereoDepthConfig.CostMatching.DisparityWidth.DISPARITY_96]
            currentDispRange = StereoConfigHandler.config.costMatching.disparityWidth
            nextDispRange = dispRangeSettings[(dispRangeSettings.index(currentDispRange)+1) % len(dispRangeSettings)]
            print(f"Changing disparity range to {nextDispRange.name} from {currentDispRange.name}")
            StereoConfigHandler.config.costMatching.disparityWidth = nextDispRange
        elif key == ord('f'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.costMatching.enableCompanding = not StereoConfigHandler.config.costMatching.enableCompanding
            state = "on" if StereoConfigHandler.config.costMatching.enableCompanding else "off"
            print(f"Companding {state}")
        elif key == ord('v'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.censusTransform.enableMeanMode = not StereoConfigHandler.config.censusTransform.enableMeanMode
            state = "on" if StereoConfigHandler.config.censusTransform.enableMeanMode else "off"
            print(f"Census transform mean mode {state}")
        elif key == ord('1'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.algorithmControl.enableLeftRightCheck = not StereoConfigHandler.config.algorithmControl.enableLeftRightCheck
            state = "on" if StereoConfigHandler.config.algorithmControl.enableLeftRightCheck else "off"
            print(f"LR-check {state}")
        elif key == ord('2'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.algorithmControl.enableSubpixel = not StereoConfigHandler.config.algorithmControl.enableSubpixel
            state = "on" if StereoConfigHandler.config.algorithmControl.enableSubpixel else "off"
            print(f"Subpixel {state}")
        elif key == ord('3'):
            StereoConfigHandler.newConfig = True
            StereoConfigHandler.config.algorithmControl.enableExtended = not StereoConfigHandler.config.algorithmControl.enableExtended
            state = "on" if StereoConfigHandler.config.algorithmControl.enableExtended else "off"
            print(f"Extended {state}")

        censusMaskChanged = False
        if StereoConfigHandler.censusMaskHandler is not None:
            censusMaskChanged = StereoConfigHandler.censusMaskHandler.isChanged()
        if censusMaskChanged:
            StereoConfigHandler.config.censusTransform.kernelMask = StereoConfigHandler.censusMaskHandler.getMask()
            StereoConfigHandler.newConfig = True

        StereoConfigHandler.sendConfig(stereoDepthConfigInQueue)

    def sendConfig(stereoDepthConfigInQueue):
        if StereoConfigHandler.newConfig:
            StereoConfigHandler.newConfig = False
            configMessage = dai.StereoDepthConfig()
            configMessage.set(StereoConfigHandler.config)
            stereoDepthConfigInQueue.send(configMessage)

    def updateDefaultConfig(config):
        StereoConfigHandler.config = config

    def registerWindow(stream):
        cv2.namedWindow(stream, cv2.WINDOW_NORMAL)

        StereoConfigHandler.trConfidence.append(StereoConfigHandler.Trackbar('Disparity confidence', stream, 0, 255, StereoConfigHandler.config.costMatching.confidenceThreshold, StereoConfigHandler.trackbarConfidence))
        StereoConfigHandler.trSigma.append(StereoConfigHandler.Trackbar('Bilateral sigma', stream, 0, 100, StereoConfigHandler.config.postProcessing.bilateralSigmaValue, StereoConfigHandler.trackbarSigma))
        StereoConfigHandler.trLrCheck.append(StereoConfigHandler.Trackbar('LR-check threshold', stream, 0, 16, StereoConfigHandler.config.algorithmControl.leftRightCheckThreshold, StereoConfigHandler.trackbarLrCheckThreshold))
        StereoConfigHandler.trFractionalBits.append(StereoConfigHandler.Trackbar('Subpixel fractional bits', stream, 3, 5, StereoConfigHandler.config.algorithmControl.subpixelFractionalBits, StereoConfigHandler.trackbarFractionalBits))
        StereoConfigHandler.trLineqAlpha.append(StereoConfigHandler.Trackbar('Linear equation alpha', stream, 0, 15, StereoConfigHandler.config.costMatching.linearEquationParameters.alpha, StereoConfigHandler.trackbarLineqAlpha))
        StereoConfigHandler.trLineqBeta.append(StereoConfigHandler.Trackbar('Linear equation beta', stream, 0, 15, StereoConfigHandler.config.costMatching.linearEquationParameters.beta, StereoConfigHandler.trackbarLineqBeta))
        StereoConfigHandler.trLineqThreshold.append(StereoConfigHandler.Trackbar('Linear equation threshold', stream, 0, 255, StereoConfigHandler.config.costMatching.linearEquationParameters.threshold, StereoConfigHandler.trackbarLineqThreshold))
        StereoConfigHandler.trCostAggregationP1.append(StereoConfigHandler.Trackbar('Cost aggregation P1', stream, 0, 500, StereoConfigHandler.config.costAggregation.horizontalPenaltyCostP1, StereoConfigHandler.trackbarCostAggregationP1))
        StereoConfigHandler.trCostAggregationP2.append(StereoConfigHandler.Trackbar('Cost aggregation P2', stream, 0, 500, StereoConfigHandler.config.costAggregation.horizontalPenaltyCostP2, StereoConfigHandler.trackbarCostAggregationP2))
        StereoConfigHandler.trTemporalAlpha.append(StereoConfigHandler.Trackbar('Temporal filter alpha', stream, 0, 100, int(StereoConfigHandler.config.postProcessing.temporalFilter.alpha*100), StereoConfigHandler.trackbarTemporalFilterAlpha))
        StereoConfigHandler.trTemporalDelta.append(StereoConfigHandler.Trackbar('Temporal filter delta', stream, 0, 100, StereoConfigHandler.config.postProcessing.temporalFilter.delta, StereoConfigHandler.trackbarTemporalFilterDelta))
        StereoConfigHandler.trSpatialAlpha.append(StereoConfigHandler.Trackbar('Spatial filter alpha', stream, 0, 100, int(StereoConfigHandler.config.postProcessing.spatialFilter.alpha*100), StereoConfigHandler.trackbarSpatialFilterAlpha))
        StereoConfigHandler.trSpatialDelta.append(StereoConfigHandler.Trackbar('Spatial filter delta', stream, 0, 100, StereoConfigHandler.config.postProcessing.spatialFilter.delta, StereoConfigHandler.trackbarSpatialFilterDelta))
        StereoConfigHandler.trSpatialHoleFilling.append(StereoConfigHandler.Trackbar('Spatial filter hole filling radius', stream, 0, 16, StereoConfigHandler.config.postProcessing.spatialFilter.holeFillingRadius, StereoConfigHandler.trackbarSpatialFilterHoleFillingRadius))
        StereoConfigHandler.trSpatialNumIterations.append(StereoConfigHandler.Trackbar('Spatial filter number of iterations', stream, 0, 4, StereoConfigHandler.config.postProcessing.spatialFilter.numIterations, StereoConfigHandler.trackbarSpatialFilterNumIterations))
        StereoConfigHandler.trThresholdMinRange.append(StereoConfigHandler.Trackbar('Threshold filter min range', stream, 0, 65, StereoConfigHandler.config.postProcessing.thresholdFilter.minRange, StereoConfigHandler.trackbarThresholdMinRange))
        StereoConfigHandler.trThresholdMaxRange.append(StereoConfigHandler.Trackbar('Threshold filter max range', stream, 0, 65, StereoConfigHandler.config.postProcessing.thresholdFilter.maxRange, StereoConfigHandler.trackbarThresholdMaxRange))
        StereoConfigHandler.trSpeckleRange.append(StereoConfigHandler.Trackbar('Speckle filter range', stream, 0, 240, StereoConfigHandler.config.postProcessing.speckleFilter.speckleRange, StereoConfigHandler.trackbarSpeckleRange))
        StereoConfigHandler.trDecimationFactor.append(StereoConfigHandler.Trackbar('Decimation factor', stream, 1, 4, StereoConfigHandler.config.postProcessing.decimationFilter.decimationFactor, StereoConfigHandler.trackbarDecimationFactor))

    def __init__(self, config):
        print("Control median filter using the 'm' key.")
        print("Control census transform kernel size using the 'c' key.")
        print("Control disparity search range using the 'd' key.")
        print("Control disparity companding using the 'f' key.")
        print("Control census transform mean mode using the 'v' key.")
        print("Control depth alignment using the 'a' key.")
        print("Control decimation algorithm using the 'a' key.")
        print("Control temporal persistency mode using the 'r' key.")
        print("Control spatial filter using the 'w' key.")
        print("Control temporal filter using the 't' key.")
        print("Control speckle filter using the 's' key.")
        print("Control left-right check mode using the '1' key.")
        print("Control subpixel mode using the '2' key.")
        print("Control extended mode using the '3' key.")

        StereoConfigHandler.config = config

        if StereoConfigHandler.config.censusTransform.kernelSize != dai.StereoDepthConfig.CensusTransform.KernelSize.AUTO:
            censusMask = StereoConfigHandler.config.censusTransform.kernelMask
            censusGridSize = [(5,5), (7,7), (7,9)]
            censusGrid = censusGridSize[StereoConfigHandler.config.censusTransform.kernelSize]
            if StereoConfigHandler.config.censusTransform.kernelMask == 0:
                censusDefaultMask = [np.uint64(0xA82415), np.uint64(0xAA02A8154055), np.uint64(0x2AA00AA805540155)]
                censusMask = censusDefaultMask[StereoConfigHandler.config.censusTransform.kernelSize]
            StereoConfigHandler.censusMaskHandler = StereoConfigHandler.CensusMaskHandler("Census mask", censusGrid)
            StereoConfigHandler.censusMaskHandler.setMask(censusMask)
        else:
            print("Census mask config is not available in AUTO Census kernel mode. Change using the 'c' key")


# StereoDepth initial config options.
outDepth = True  # Disparity by default
outConfidenceMap = True  # Output disparity confidence map
outRectified = True   # Output and display rectified streams
lrcheck = True   # Better handling for occlusions
extended = False  # Closer-in minimum depth, disparity range is doubled. Unsupported for now.
subpixel = True   # Better accuracy for longer distance, fractional disparity 32-levels

width = 1280
height = 800

xoutStereoCfg = None

# Create pipeline
pipeline = dai.Pipeline()

# Define sources and outputs
stereo = pipeline.create(dai.node.StereoDepth)

monoLeft = pipeline.create(dai.node.XLinkIn)
monoRight = pipeline.create(dai.node.XLinkIn)
xinStereoDepthConfig = pipeline.create(dai.node.XLinkIn)

xoutLeft = pipeline.create(dai.node.XLinkOut)
xoutRight = pipeline.create(dai.node.XLinkOut)
xoutDepth = pipeline.create(dai.node.XLinkOut)
xoutConfMap = pipeline.create(dai.node.XLinkOut)
xoutDisparity = pipeline.create(dai.node.XLinkOut)
xoutRectifLeft = pipeline.create(dai.node.XLinkOut)
xoutRectifRight = pipeline.create(dai.node.XLinkOut)
xoutStereoCfg = pipeline.create(dai.node.XLinkOut)
if args.debug:
    xoutDebugLrCheckIt1 = pipeline.create(dai.node.XLinkOut)
    xoutDebugLrCheckIt2 = pipeline.create(dai.node.XLinkOut)
    xoutDebugExtLrCheckIt1 = pipeline.create(dai.node.XLinkOut)
    xoutDebugExtLrCheckIt2 = pipeline.create(dai.node.XLinkOut)
if args.dumpdisparitycostvalues:
    xoutDebugCostDump = pipeline.create(dai.node.XLinkOut)

xinStereoDepthConfig.setStreamName("stereoDepthConfig")
monoLeft.setStreamName('in_left')
monoRight.setStreamName('in_right')

xoutLeft.setStreamName('left')
xoutRight.setStreamName('right')
xoutDepth.setStreamName('depth')
xoutConfMap.setStreamName('confidence_map')
xoutDisparity.setStreamName('disparity')
xoutRectifLeft.setStreamName('rectified_left')
xoutRectifRight.setStreamName('rectified_right')
xoutStereoCfg.setStreamName('stereo_cfg')
if args.debug:
    xoutDebugLrCheckIt1.setStreamName('disparity_lr_check_iteration1')
    xoutDebugLrCheckIt2.setStreamName('disparity_lr_check_iteration2')
    xoutDebugExtLrCheckIt1.setStreamName('disparity_ext_lr_check_iteration1')
    xoutDebugExtLrCheckIt2.setStreamName('disparity_ext_lr_check_iteration2')
if args.dumpdisparitycostvalues:
    xoutDebugCostDump.setStreamName('disparity_cost_dump')

# Properties
stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
stereo.setRectifyEdgeFillColor(0) # Black, to better see the cutout
stereo.setLeftRightCheck(lrcheck)
stereo.setExtendedDisparity(extended)
stereo.setSubpixel(subpixel)
# allocates resources for worst case scenario
# allowing runtime switch of stereo modes
stereo.setRuntimeModeSwitch(True)

# Linking
monoLeft.out.link(stereo.left)
monoRight.out.link(stereo.right)
xinStereoDepthConfig.out.link(stereo.inputConfig)
stereo.syncedLeft.link(xoutLeft.input)
stereo.syncedRight.link(xoutRight.input)
if outDepth:
    stereo.depth.link(xoutDepth.input)
if outConfidenceMap:
    stereo.confidenceMap.link(xoutConfMap.input)
stereo.disparity.link(xoutDisparity.input)
if outRectified:
    stereo.rectifiedLeft.link(xoutRectifLeft.input)
    stereo.rectifiedRight.link(xoutRectifRight.input)
stereo.outConfig.link(xoutStereoCfg.input)
if args.debug:
    stereo.debugDispLrCheckIt1.link(xoutDebugLrCheckIt1.input)
    stereo.debugDispLrCheckIt2.link(xoutDebugLrCheckIt2.input)
    stereo.debugExtDispLrCheckIt1.link(xoutDebugExtLrCheckIt1.input)
    stereo.debugExtDispLrCheckIt2.link(xoutDebugExtLrCheckIt2.input)
if args.dumpdisparitycostvalues:
    stereo.debugDispCostDump.link(xoutDebugCostDump.input)

StereoConfigHandler(stereo.initialConfig.get())
StereoConfigHandler.registerWindow('Stereo control panel')

# stereo.setPostProcessingHardwareResources(3, 3)

stereo.setInputResolution(width, height)
stereo.setRectification(False)
baseline = 75
fov = 71.86
focal = width / (2 * math.tan(fov / 2 / 180 * math.pi))

streams = ['left', 'right']
if outRectified:
    streams.extend(['rectified_left', 'rectified_right'])
streams.append('disparity')
if outDepth:
    streams.append('depth')
if outConfidenceMap:
    streams.append('confidence_map')
debugStreams = []
if args.debug:
    debugStreams.extend(['disparity_lr_check_iteration1', 'disparity_lr_check_iteration2'])
    debugStreams.extend(['disparity_ext_lr_check_iteration1', 'disparity_ext_lr_check_iteration2'])
if args.dumpdisparitycostvalues:
    debugStreams.append('disparity_cost_dump')

def convertToCv2Frame(name, image, config):

    maxDisp = config.getMaxDisparity()
    subpixelLevels = pow(2, config.get().algorithmControl.subpixelFractionalBits)
    subpixel = config.get().algorithmControl.enableSubpixel
    dispIntegerLevels = maxDisp if not subpixel else maxDisp / subpixelLevels

    frame = image.getFrame()

    # frame.tofile(name+".raw")

    if name == 'depth':
        dispScaleFactor = baseline * focal
        with np.errstate(divide='ignore'):
            frame = dispScaleFactor / frame

        frame = (frame * 255. / dispIntegerLevels).astype(np.uint8)
        frame = cv2.applyColorMap(frame, cv2.COLORMAP_HOT)
    elif 'confidence_map' in name:
        pass
    elif name == 'disparity_cost_dump':
        # frame.tofile(name+'.raw')
        pass
    elif 'disparity' in name:
        if 1: # Optionally, extend disparity range to better visualize it
            frame = (frame * 255. / maxDisp).astype(np.uint8)

        # if 1: # Optionally, apply a color map
        #     frame = cv2.applyColorMap(frame, cv2.COLORMAP_HOT)

    return frame

print("Connecting and starting the pipeline")
# Connect to device and start pipeline
with dai.Device(pipeline) as device:

    stereoDepthConfigInQueue = device.getInputQueue("stereoDepthConfig")
    inStreams = ['in_right', 'in_left']
    inStreamsCameraID = [dai.CameraBoardSocket.RIGHT, dai.CameraBoardSocket.LEFT]
    in_q_list = []
    for s in inStreams:
        q = device.getInputQueue(s)
        in_q_list.append(q)

    # Create a receive queue for each stream
    q_list = []
    for s in streams:
        q = device.getOutputQueue(s, 8, blocking=False)
        q_list.append(q)


    inCfg = device.getOutputQueue("stereo_cfg", 8, blocking=False)

    # Need to set a timestamp for input frames, for the sync stage in Stereo node
    timestamp_ms = 0
    index = 0
    prevQueues = q_list.copy()
    while True:
        # Handle input streams, if any
        if in_q_list:
            dataset_size = 1  # Number of image pairs
            frame_interval_ms = 50
            for i, q in enumerate(in_q_list):
                path = args.dataset + '/' + str(index) + '/' + q.getName() + '.png'
                data = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
                data = cv2.resize(data, (width, height), interpolation = cv2.INTER_AREA)
                data = data.reshape(height*width)
                tstamp = datetime.timedelta(seconds = timestamp_ms // 1000,
                                            milliseconds = timestamp_ms % 1000)
                img = dai.ImgFrame()
                img.setData(data)
                img.setTimestamp(tstamp)
                img.setInstanceNum(inStreamsCameraID[i])
                img.setType(dai.ImgFrame.Type.RAW8)
                img.setWidth(width)
                img.setHeight(height)
                q.send(img)
                if timestamp_ms == 0:  # Send twice for first iteration
                    q.send(img)
                # print("Sent frame: {:25s}".format(path), 'timestamp_ms:', timestamp_ms)
            timestamp_ms += frame_interval_ms
            index = (index + 1) % dataset_size
            sleep(frame_interval_ms / 1000)

        # Handle output streams
        currentConfig = inCfg.get()

        lrCheckEnabled = currentConfig.get().algorithmControl.enableLeftRightCheck
        extendedEnabled = currentConfig.get().algorithmControl.enableExtended
        queues = q_list.copy()

        if args.dumpdisparitycostvalues:
            q = device.getOutputQueue('disparity_cost_dump', 8, blocking=False)
            queues.append(q)

        if args.debug:
            q_list_debug = []

            activeDebugStreams = []
            if lrCheckEnabled:
                activeDebugStreams.extend(['disparity_lr_check_iteration1', 'disparity_lr_check_iteration2'])
            if extendedEnabled:
                activeDebugStreams.extend(['disparity_ext_lr_check_iteration1'])
                if lrCheckEnabled:
                    activeDebugStreams.extend(['disparity_ext_lr_check_iteration2'])

            for s in activeDebugStreams:
                q = device.getOutputQueue(s, 8, blocking=False)
                q_list_debug.append(q)

            queues.extend(q_list_debug)

        def ListDiff(li1, li2):
            return list(set(li1) - set(li2)) + list(set(li2) - set(li1))

        diff = ListDiff(prevQueues, queues)
        for s in diff:
            name = s.getName()
            cv2.destroyWindow(name)
        prevQueues = queues.copy()

        for q in queues:
            if q.getName() in ['left', 'right']: continue
            data = q.get()
            frame = convertToCv2Frame(q.getName(), data, currentConfig)
            cv2.imshow(q.getName(), frame)

        key = cv2.waitKey(1)
        if key == ord('q'):
            break

        StereoConfigHandler.handleKeypress(key, stereoDepthConfigInQueue)

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