DepthAI OAK Luxonis - RGB depth alignment with 12MP color stream

rgb-depth-align-12mp-depth.py

#!/usr/bin/env python3

import cv2
import numpy as np
import depthai as dai

# Weights to use when blending depth/rgb image (should equal 1.0)
rgbWeight = 0.4
depthWeight = 0.6


def updateBlendWeights(percent_rgb):
    """
    Update the rgb and depth weights used to blend depth/rgb image
    @param[in] percent_rgb The rgb weight expressed as a percentage (0..100)
    """
    global depthWeight
    global rgbWeight
    rgbWeight = float(percent_rgb)/100.0
    depthWeight = 1.0 - rgbWeight


# Optional. If set (True), the ColorCamera is downscaled from 1080p to 720p.
# Otherwise (False), the aligned depth is automatically upscaled to 1080p
downscaleColor = True
fps = 10
# The disparity is computed at this resolution, then upscaled to RGB resolution
monoResolution = dai.MonoCameraProperties.SensorResolution.THE_800_P

# Create pipeline
pipeline = dai.Pipeline()
device = dai.Device()

# Define sources and outputs
camRgb = pipeline.create(dai.node.ColorCamera)
left = pipeline.create(dai.node.MonoCamera)
right = pipeline.create(dai.node.MonoCamera)
stereo = pipeline.create(dai.node.StereoDepth)

rgbOut = pipeline.create(dai.node.XLinkOut)
depthOut = pipeline.create(dai.node.XLinkOut)

rgbOut.setStreamName("rgb")
depthOut.setStreamName("depth")

#Properties
camRgb.setBoardSocket(dai.CameraBoardSocket.RGB)
camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_12_MP) # 4056x3040

try:
    calibData = device.readCalibration2()
    lensPosition = calibData.getLensPosition(dai.CameraBoardSocket.RGB)
    if lensPosition:
        camRgb.initialControl.setManualFocus(lensPosition)
except:
    raise
left.setResolution(monoResolution)
left.setBoardSocket(dai.CameraBoardSocket.LEFT)
left.setFps(fps)
right.setResolution(monoResolution)
right.setBoardSocket(dai.CameraBoardSocket.RIGHT)
right.setFps(fps)

stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
# LR-check is required for depth alignment
stereo.setLeftRightCheck(True)
stereo.setDepthAlign(dai.CameraBoardSocket.RGB)
# # 4056x3040
stereo.setOutputSize(1248, 936)

# Linking
camRgb.isp.link(rgbOut.input)
left.out.link(stereo.left)
right.out.link(stereo.right)
stereo.depth.link(depthOut.input)

# Connect to device and start pipeline
with device:
    device.startPipeline(pipeline)

    frameRgb = None
    depthFrame = None

    # Configure windows; trackbar adjusts blending ratio of rgb/depth
    rgbWindowName = "rgb"
    depthWindowName = "depth"
    blendedWindowName = "rgb-depth"
    cv2.namedWindow(rgbWindowName)
    cv2.namedWindow(depthWindowName)
    cv2.namedWindow(blendedWindowName)
    cv2.createTrackbar('RGB Weight %', blendedWindowName, int(rgbWeight*100), 100, updateBlendWeights)

    while True:
        latestPacket = {}
        latestPacket["rgb"] = None
        latestPacket["depth"] = None

        queueEvents = device.getQueueEvents(("rgb", "depth"))
        for queueName in queueEvents:
            packets = device.getOutputQueue(queueName).tryGetAll()
            if len(packets) > 0:
                latestPacket[queueName] = packets[-1]

        if latestPacket["rgb"] is not None:
            frameRgb = latestPacket["rgb"].getCvFrame()
            frameRgb = cv2.resize(frameRgb, (1248, 936), interpolation=cv2.INTER_NEAREST)
            cv2.imshow(rgbWindowName, frameRgb)

        if latestPacket["depth"] is not None:
            depthFrame = latestPacket["depth"].getFrame()
            depthFrame = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
            depthFrame = cv2.equalizeHist(depthFrame)
            depthFrame = cv2.applyColorMap(depthFrame, cv2.COLORMAP_HOT)
            cv2.imshow(depthWindowName, depthFrame)

        # Blend when both received
        if frameRgb is not None and depthFrame is not None:
            # Need to have both frames in BGR format before blending
            if len(depthFrame.shape) < 3:
                depthFrame = cv2.cvtColor(depthFrame, cv2.COLOR_GRAY2BGR)
            blended = cv2.addWeighted(frameRgb, rgbWeight, depthFrame, depthWeight, 0)
            cv2.imshow(blendedWindowName, blended)
            frameRgb = None
            depthFrame = None

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

rgb-depth-align-12mp-disparity.py

#!/usr/bin/env python3

import cv2
import numpy as np
import depthai as dai

# Weights to use when blending depth/rgb image (should equal 1.0)
rgbWeight = 0.4
depthWeight = 0.6


def updateBlendWeights(percent_rgb):
    """
    Update the rgb and depth weights used to blend depth/rgb image

    @param[in] percent_rgb The rgb weight expressed as a percentage (0..100)
    """
    global depthWeight
    global rgbWeight
    rgbWeight = float(percent_rgb)/100.0
    depthWeight = 1.0 - rgbWeight


# Optional. If set (True), the ColorCamera is downscaled from 1080p to 720p.
# Otherwise (False), the aligned depth is automatically upscaled to 1080p
downscaleColor = True
fps = 10
# The disparity is computed at this resolution, then upscaled to RGB resolution
monoResolution = dai.MonoCameraProperties.SensorResolution.THE_800_P

# Create pipeline
pipeline = dai.Pipeline()
device = dai.Device()
queueNames = []

# Define sources and outputs
camRgb = pipeline.create(dai.node.ColorCamera)
left = pipeline.create(dai.node.MonoCamera)
right = pipeline.create(dai.node.MonoCamera)
stereo = pipeline.create(dai.node.StereoDepth)

rgbOut = pipeline.create(dai.node.XLinkOut)
disparityOut = pipeline.create(dai.node.XLinkOut)

rgbOut.setStreamName("rgb")
queueNames.append("rgb")
disparityOut.setStreamName("disp")
queueNames.append("disp")

#Properties
camRgb.setBoardSocket(dai.CameraBoardSocket.RGB)
camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_12_MP) # 4056x3040

try:
    calibData = device.readCalibration2()
    lensPosition = calibData.getLensPosition(dai.CameraBoardSocket.RGB)
    if lensPosition:
        camRgb.initialControl.setManualFocus(lensPosition)
except:
    raise
left.setResolution(monoResolution)
left.setBoardSocket(dai.CameraBoardSocket.LEFT)
left.setFps(fps)
right.setResolution(monoResolution)
right.setBoardSocket(dai.CameraBoardSocket.RIGHT)
right.setFps(fps)

stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
# LR-check is required for depth alignment
stereo.setLeftRightCheck(True)
stereo.setDepthAlign(dai.CameraBoardSocket.RGB)
# # 4056x3040
stereo.setOutputSize(1248, 936)

# Linking
camRgb.isp.link(rgbOut.input)
left.out.link(stereo.left)
right.out.link(stereo.right)
stereo.disparity.link(disparityOut.input)

# Connect to device and start pipeline
with device:
    device.startPipeline(pipeline)

    frameRgb = None
    frameDisp = None

    # Configure windows; trackbar adjusts blending ratio of rgb/depth
    rgbWindowName = "rgb"
    depthWindowName = "depth"
    blendedWindowName = "rgb-depth"
    cv2.namedWindow(rgbWindowName)
    cv2.namedWindow(depthWindowName)
    cv2.namedWindow(blendedWindowName)
    cv2.createTrackbar('RGB Weight %', blendedWindowName, int(rgbWeight*100), 100, updateBlendWeights)

    while True:
        latestPacket = {}
        latestPacket["rgb"] = None
        latestPacket["disp"] = None

        queueEvents = device.getQueueEvents(("rgb", "disp"))
        for queueName in queueEvents:
            packets = device.getOutputQueue(queueName).tryGetAll()
            if len(packets) > 0:
                latestPacket[queueName] = packets[-1]

        if latestPacket["rgb"] is not None:
            frameRgb = latestPacket["rgb"].getCvFrame()
            frameRgb = cv2.resize(frameRgb, (1248, 936), interpolation=cv2.INTER_NEAREST)
            cv2.imshow(rgbWindowName, frameRgb)

        if latestPacket["disp"] is not None:
            frameDisp = latestPacket["disp"].getFrame()
            maxDisparity = stereo.initialConfig.getMaxDisparity()
            # Optional, extend range 0..95 -> 0..255, for a better visualisation
            if 1: frameDisp = (frameDisp * 255. / maxDisparity).astype(np.uint8)
            # Optional, apply false colorization
            if 1: frameDisp = cv2.applyColorMap(frameDisp, cv2.COLORMAP_HOT)
            frameDisp = np.ascontiguousarray(frameDisp)
            cv2.imshow(depthWindowName, frameDisp)

        # Blend when both received
        if frameRgb is not None and frameDisp is not None:
            # Need to have both frames in BGR format before blending
            if len(frameDisp.shape) < 3:
                frameDisp = cv2.cvtColor(frameDisp, cv2.COLOR_GRAY2BGR)
            blended = cv2.addWeighted(frameRgb, rgbWeight, frameDisp, depthWeight, 0)
            cv2.imshow(blendedWindowName, blended)
            frameRgb = None
            frameDisp = None

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

@mamoonik I just updated the gist so it contains both depth and disparity options.