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Merge branch 'release_2.17.4.0' into main
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‎CMakeLists.txt

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# Pybindings project
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set(TARGET_NAME depthai)
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project(depthai VERSION "1") # revision of bindings [depthai-core].[rev]
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project(depthai VERSION "0") # revision of bindings [depthai-core].[rev]
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# Set default build type depending on context
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set(default_build_type "Release")

‎depthai-core

Submodule depthai-core updated 26 files

‎docs/source/samples/SpatialDetection/spatial_calculator_multi_roi.rst

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Spatial Calculator Multi-ROI
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============================
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This example shows how one can use multiple ROIs with a single :ref:`SpatailLocationCalculator` node. A similar logic could be used as a simple depth line
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scanning camera for mobile robots.
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.. rubric:: Similar samples:
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- :ref:`Spatial location calculator`
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Demo
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####
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.. image:: https://user-images.githubusercontent.com/18037362/190861621-b57fd1e3-5a3d-4d79-b1a7-d17a0b78c63e.gif
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Setup
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#####
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.. include:: /includes/install_from_pypi.rst
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Source code
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###########
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.. tabs::
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.. tab:: Python
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Also `available on GitHub <https://github.com/luxonis/depthai-python/blob/main/examples/SpatialDetection/spatial_calculator_multi_roi.py>`__
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.. literalinclude:: ../../../../examples/SpatialDetection/spatial_calculator_multi_roi.py
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:language: python
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:linenos:
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.. tab:: C++
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Also `available on GitHub <https://github.com/luxonis/depthai-core/blob/main/examples/SpatialDetection/spatial_calculator_multi_roi.cpp>`__
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.. literalinclude:: ../../../../depthai-core/examples/SpatialDetection/spatial_calculator_multi_roi.cpp
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:language: cpp
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:linenos:
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.. include:: /includes/footer-short.rst

‎docs/source/samples/host_side/device_information.rst

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Device information
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==================
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This example shows how you can query device information.
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The first part of the code queries all available devices without actually booting any device. For each found device, it prints the following information:
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- **Device name**: Either IP, in case of OAK PoE cameras, or USB path in case of OAK USB cameras
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- **MxId**: Unique Mx (chip) identification code
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- **State**: State of the device. Note that OAK PoE cameras have bootloader flashed which initializes the network stack
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Afterwards, the example boots into the first found device and prints available camera sensors, and reads calibration and eeprom data which stores product and
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board names.
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Demo
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####
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.. code-block::
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Searching for all available devices...
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Found device '1.3', MxId: '18443010D116631200', State: 'UNBOOTED'
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Found device '192.168.33.201', MxId: '184430102163DB0F00', State: 'BOOTLOADER'
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Found device '192.168.33.192', MxId: '1844301011F4C51200', State: 'BOOTLOADER'
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Booting the first available camera (1.3)...
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Available camera sensors: {<CameraBoardSocket.RIGHT: 2>: 'OV9282', <CameraBoardSocket.RGB: 0>: 'IMX378', <CameraBoardSocket.LEFT: 1>: 'OV9282'}
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Product name: OAK-D Pro AF, board name DM9098
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Setup
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#####
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.. include:: /includes/install_from_pypi.rst
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Source code
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###########
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.. tabs::
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.. tab:: Python
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Also `available on GitHub <https://github.com/luxonis/depthai-python/blob/main/examples/host_side/device_information.py>`__
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.. literalinclude:: ../../../../examples/host_side/device_information.py
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:language: python
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:linenos:
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.. tab:: C++
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Also `available on GitHub <https://github.com/luxonis/depthai-core/blob/main/examples/host_side/device_information.cpp>`__
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.. literalinclude:: ../../../../depthai-core/examples/host_side/device_information.cpp
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:language: cpp
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:linenos:
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.. include:: /includes/footer-short.rst

‎examples/CMakeLists.txt

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## Script
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add_python_example(script_camera_control Script/script_camera_control.py)
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add_python_example(script_json_communication Script/script_json_communication.py)
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add_python_example(script_get_device_info Script/script_get_device_info.py)
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## SpatialDetection
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add_python_example(spatial_tiny_yolo_v3 SpatialDetection/spatial_tiny_yolo.py yolo3)

‎examples/Script/script_get_device_info.py

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#!/usr/bin/env python3
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import depthai as dai
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import json
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# Start defining a pipeline
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pipeline = dai.Pipeline()
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# Script node
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script = pipeline.create(dai.node.Script)
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script.setScript("""
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import json
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data = json.dumps({
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'deviceId': __device_id__,
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'fwVersion': __version__
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}).encode('utf-8')
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b = Buffer(len(data))
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b.setData(data)
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node.io['info'].send(b)
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""")
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xout = pipeline.create(dai.node.XLinkOut)
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xout.setStreamName('info')
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script.outputs['info'].link(xout.input)
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# Connect to device with pipeline
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with dai.Device(pipeline) as device:
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msg = device.getOutputQueue("info").get() # Wait for the "end" msg
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data = json.loads(msg.getData().tobytes().decode('utf-8'))
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print(json.dumps(data, indent=4))

‎examples/Script/script_get_ip.py

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#!/usr/bin/env python3
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import depthai as dai
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# MAKE SURE U HAVE LATEST BOOTLOADER KTNXBAI
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# Start defining a pipeline
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pipeline = dai.Pipeline()
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ip = get_ip_address('re0') # '192.168.0.110'
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node.warn(f'IP of the device: {ip}')
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node.io['end'].send(Buffer())
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node.io['end'].send(Buffer(32))
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""")
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xout = pipeline.create(dai.node.XLinkOut)

‎examples/Script/script_http_client.py

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data1 = r1.read()
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node.warn(f'Public IP: {data1}')
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node.io['end'].send(Buffer())
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node.io['end'].send(Buffer(32))
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""")
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xout = pipeline.create(dai.node.XLinkOut)

‎examples/SpatialDetection/spatial_calculator_multi_roi.py

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#!/usr/bin/env python3
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import cv2
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import depthai as dai
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import math
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# Create pipeline
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pipeline = dai.Pipeline()
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# Define sources and outputs
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monoLeft = pipeline.create(dai.node.MonoCamera)
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monoRight = pipeline.create(dai.node.MonoCamera)
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stereo = pipeline.create(dai.node.StereoDepth)
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spatialLocationCalculator = pipeline.create(dai.node.SpatialLocationCalculator)
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xoutDepth = pipeline.create(dai.node.XLinkOut)
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xoutSpatialData = pipeline.create(dai.node.XLinkOut)
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xinSpatialCalcConfig = pipeline.create(dai.node.XLinkIn)
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xoutDepth.setStreamName("depth")
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xoutSpatialData.setStreamName("spatialData")
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xinSpatialCalcConfig.setStreamName("spatialCalcConfig")
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# Properties
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monoLeft.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)
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monoLeft.setBoardSocket(dai.CameraBoardSocket.LEFT)
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monoRight.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)
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monoRight.setBoardSocket(dai.CameraBoardSocket.RIGHT)
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stereo.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
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stereo.setLeftRightCheck(True)
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stereo.setExtendedDisparity(True)
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spatialLocationCalculator.inputConfig.setWaitForMessage(False)
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# Create 10 ROIs
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for i in range(10):
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config = dai.SpatialLocationCalculatorConfigData()
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config.depthThresholds.lowerThreshold = 200
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config.depthThresholds.upperThreshold = 10000
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config.roi = dai.Rect(dai.Point2f(i*0.1, 0.45), dai.Point2f((i+1)*0.1, 0.55))
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spatialLocationCalculator.initialConfig.addROI(config)
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# Linking
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monoLeft.out.link(stereo.left)
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monoRight.out.link(stereo.right)
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spatialLocationCalculator.passthroughDepth.link(xoutDepth.input)
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stereo.depth.link(spatialLocationCalculator.inputDepth)
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spatialLocationCalculator.out.link(xoutSpatialData.input)
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xinSpatialCalcConfig.out.link(spatialLocationCalculator.inputConfig)
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# Connect to device and start pipeline
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with dai.Device(pipeline) as device:
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device.setIrLaserDotProjectorBrightness(1000)
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# Output queue will be used to get the depth frames from the outputs defined above
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depthQueue = device.getOutputQueue(name="depth", maxSize=4, blocking=False)
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spatialCalcQueue = device.getOutputQueue(name="spatialData", maxSize=4, blocking=False)
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color = (0,200,40)
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fontType = cv2.FONT_HERSHEY_TRIPLEX
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while True:
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inDepth = depthQueue.get() # Blocking call, will wait until a new data has arrived
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depthFrame = inDepth.getFrame() # depthFrame values are in millimeters
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depthFrameColor = cv2.normalize(depthFrame, None, 255, 0, cv2.NORM_INF, cv2.CV_8UC1)
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depthFrameColor = cv2.equalizeHist(depthFrameColor)
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depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_HOT)
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spatialData = spatialCalcQueue.get().getSpatialLocations()
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for depthData in spatialData:
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roi = depthData.config.roi
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roi = roi.denormalize(width=depthFrameColor.shape[1], height=depthFrameColor.shape[0])
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xmin = int(roi.topLeft().x)
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ymin = int(roi.topLeft().y)
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xmax = int(roi.bottomRight().x)
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ymax = int(roi.bottomRight().y)
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coords = depthData.spatialCoordinates
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distance = math.sqrt(coords.x ** 2 + coords.y ** 2 + coords.z ** 2)
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cv2.rectangle(depthFrameColor, (xmin, ymin), (xmax, ymax), color, thickness=2)
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cv2.putText(depthFrameColor, "{:.1f}m".format(distance/1000), (xmin + 10, ymin + 20), fontType, 0.6, color)
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# Show the frame
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cv2.imshow("depth", depthFrameColor)
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if cv2.waitKey(1) == ord('q'):
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break

‎examples/calibration/calibration_dump.py

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