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themarpethemarpe
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Merge branch 'release_2.20.0' into main
2 parents 2025ce1 + 8e5b547 commit af8e15b

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‎.github/workflows/main.yml‎

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repository: luxonis/robothub-apps
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event-type: depthai-python-release
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client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}"}'
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notify_hil_workflow_linux_x86_64:
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needs: [build-linux-x86_64]
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runs-on: ubuntu-latest
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steps:
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- name: Repository Dispatch
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uses: peter-evans/repository-dispatch@v2
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with:
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token: ${{ secrets.HIL_CORE_DISPATCH_TOKEN }}
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repository: luxonis/depthai-core-hil-tests
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event-type: python-hil-event
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client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}"}'

‎.gitignore‎

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.venv
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env/
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venv/
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venv_*/
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ENV/
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env.bak/
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venv.bak/

‎CMakeLists.txt‎

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src/pipeline/node/XLinkInBindings.cpp
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src/pipeline/node/XLinkOutBindings.cpp
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src/pipeline/node/ColorCameraBindings.cpp
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src/pipeline/node/CameraBindings.cpp
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src/pipeline/node/MonoCameraBindings.cpp
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src/pipeline/node/StereoDepthBindings.cpp
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src/pipeline/node/NeuralNetworkBindings.cpp

‎depthai-core‎

Submodule depthai-core updated 39 files

‎examples/Camera/camera_isp.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 time
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# Connect to device and start pipeline
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with dai.Device() as device:
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# Device name
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print('Device name:', device.getDeviceName())
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# Bootloader version
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if device.getBootloaderVersion() is not None:
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print('Bootloader version:', device.getBootloaderVersion())
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# Print out usb speed
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print('Usb speed:', device.getUsbSpeed().name)
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# Connected cameras
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print('Connected cameras:', device.getConnectedCameraFeatures())
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# Create pipeline
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pipeline = dai.Pipeline()
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cams = device.getConnectedCameraFeatures()
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streams = []
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for cam in cams:
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print(str(cam), str(cam.socket), cam.socket)
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c = pipeline.create(dai.node.Camera)
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x = pipeline.create(dai.node.XLinkOut)
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c.isp.link(x.input)
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c.setBoardSocket(cam.socket)
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stream = str(cam.socket)
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if cam.name:
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stream = f'{cam.name} ({stream})'
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x.setStreamName(stream)
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streams.append(stream)
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# Start pipeline
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device.startPipeline(pipeline)
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fpsCounter = {}
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lastFpsCount = {}
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tfps = time.time()
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while not device.isClosed():
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queueNames = device.getQueueEvents(streams)
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for stream in queueNames:
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messages = device.getOutputQueue(stream).tryGetAll()
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fpsCounter[stream] = fpsCounter.get(stream, 0.0) + len(messages)
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for message in messages:
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# Display arrived frames
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if type(message) == dai.ImgFrame:
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# render fps
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fps = lastFpsCount.get(stream, 0)
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frame = message.getCvFrame()
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cv2.putText(frame, "Fps: {:.2f}".format(fps), (10, 10), cv2.FONT_HERSHEY_TRIPLEX, 0.4, (255,255,255))
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cv2.imshow(stream, frame)
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if time.time() - tfps >= 1.0:
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scale = time.time() - tfps
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for stream in fpsCounter.keys():
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lastFpsCount[stream] = fpsCounter[stream] / scale
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fpsCounter = {}
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tfps = time.time()
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if cv2.waitKey(1) == ord('q'):
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break

‎examples/Camera/camera_preview.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 time
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# Connect to device and start pipeline
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with dai.Device(dai.OpenVINO.DEFAULT_VERSION, dai.UsbSpeed.SUPER_PLUS) as device:
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# Device name
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print('Device name:', device.getDeviceName())
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# Bootloader version
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if device.getBootloaderVersion() is not None:
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print('Bootloader version:', device.getBootloaderVersion())
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# Print out usb speed
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print('Usb speed:', device.getUsbSpeed().name)
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# Connected cameras
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print('Connected cameras:', device.getConnectedCameraFeatures())
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# Create pipeline
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pipeline = dai.Pipeline()
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cams = device.getConnectedCameraFeatures()
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streams = []
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for cam in cams:
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print(str(cam), str(cam.socket), cam.socket)
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c = pipeline.create(dai.node.Camera)
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x = pipeline.create(dai.node.XLinkOut)
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c.preview.link(x.input)
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c.setBoardSocket(cam.socket)
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stream = str(cam.socket)
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if cam.name:
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stream = f'{cam.name} ({stream})'
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x.setStreamName(stream)
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streams.append(stream)
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# Start pipeline
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device.startPipeline(pipeline)
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fpsCounter = {}
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lastFpsCount = {}
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tfps = time.time()
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while not device.isClosed():
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queueNames = device.getQueueEvents(streams)
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for stream in queueNames:
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messages = device.getOutputQueue(stream).tryGetAll()
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fpsCounter[stream] = fpsCounter.get(stream, 0.0) + len(messages)
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for message in messages:
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# Display arrived frames
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if type(message) == dai.ImgFrame:
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# render fps
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fps = lastFpsCount.get(stream, 0)
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frame = message.getCvFrame()
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cv2.putText(frame, "Fps: {:.2f}".format(fps), (10, 10), cv2.FONT_HERSHEY_TRIPLEX, 0.4, (255,255,255))
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cv2.imshow(stream, frame)
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if time.time() - tfps >= 1.0:
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scale = time.time() - tfps
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for stream in fpsCounter.keys():
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lastFpsCount[stream] = fpsCounter[stream] / scale
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fpsCounter = {}
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tfps = time.time()
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if cv2.waitKey(1) == ord('q'):
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break

‎examples/ColorCamera/rgb_preview.py‎

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# Connect to device and start pipeline
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with dai.Device(pipeline) as device:
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print('Connected cameras:', device.getConnectedCameras())
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print('Connected cameras:', device.getConnectedCameraFeatures())
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# Print out usb speed
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print('Usb speed:', device.getUsbSpeed().name)
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# Bootloader version

‎examples/ImageManip/image_manip_warp_mesh.py‎

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maxFrameSize = camRgb.getPreviewWidth() * camRgb.getPreviewHeight() * 3
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# Warp preview frame 1
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manip1 = pipeline.create(dai.node.Warp)
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manip1 = pipeline.create(dai.node.ImageManip)
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# Create a custom warp mesh
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tl = dai.Point2f(20, 20)
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tr = dai.Point2f(460, 20)

‎examples/StereoDepth/depth_colormap.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 numpy as np
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# Closer-in minimum depth, disparity range is doubled (from 95 to 190):
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extended_disparity = False
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# Better accuracy for longer distance, fractional disparity 32-levels:
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subpixel = False
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# Better handling for occlusions:
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lr_check = True
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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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depth = pipeline.create(dai.node.StereoDepth)
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xout = pipeline.create(dai.node.XLinkOut)
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xout.setStreamName("disparity")
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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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# Create a node that will produce the depth map (using disparity output as it's easier to visualize depth this way)
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depth.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
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# Options: MEDIAN_OFF, KERNEL_3x3, KERNEL_5x5, KERNEL_7x7 (default)
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depth.initialConfig.setMedianFilter(dai.MedianFilter.KERNEL_7x7)
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depth.setLeftRightCheck(lr_check)
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depth.setExtendedDisparity(extended_disparity)
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depth.setSubpixel(subpixel)
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# Create a colormap
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colormap = pipeline.create(dai.node.ImageManip)
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colormap.initialConfig.setColormap(dai.Colormap.STEREO_TURBO, depth.initialConfig.getMaxDisparity())
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colormap.initialConfig.setFrameType(dai.ImgFrame.Type.NV12)
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# Linking
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monoLeft.out.link(depth.left)
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monoRight.out.link(depth.right)
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depth.disparity.link(colormap.inputImage)
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colormap.out.link(xout.input)
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# Connect to device and start pipeline
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with dai.Device(pipeline) as device:
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# Output queue will be used to get the disparity frames from the outputs defined above
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q = device.getOutputQueue(name="disparity", maxSize=4, blocking=False)
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while True:
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inDisparity = q.get() # blocking call, will wait until a new data has arrived
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frame = inDisparity.getCvFrame()
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cv2.imshow("disparity", frame)
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if cv2.waitKey(1) == ord('q'):
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break

‎examples/StereoDepth/depth_preview_lr.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 numpy as np
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# Closer-in minimum depth, disparity range is doubled (from 95 to 190):
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extended_disparity = True
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# Better accuracy for longer distance, fractional disparity 32-levels:
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subpixel = True
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# Better handling for occlusions:
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lr_check = True
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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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left = pipeline.create(dai.node.ColorCamera)
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right = pipeline.create(dai.node.ColorCamera)
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depth = pipeline.create(dai.node.StereoDepth)
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xout = pipeline.create(dai.node.XLinkOut)
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xoutl = pipeline.create(dai.node.XLinkOut)
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xoutr = pipeline.create(dai.node.XLinkOut)
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xout.setStreamName("disparity")
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xoutl.setStreamName("rectifiedLeft")
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xoutr.setStreamName("rectifiedRight")
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# Properties
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left.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1200_P)
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left.setBoardSocket(dai.CameraBoardSocket.LEFT)
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right.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1200_P)
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right.setBoardSocket(dai.CameraBoardSocket.RIGHT)
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right.setIspScale(2, 3)
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left.setIspScale(2, 3)
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# Create a node that will produce the depth map (using disparity output as it's easier to visualize depth this way)
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depth.setDefaultProfilePreset(dai.node.StereoDepth.PresetMode.HIGH_DENSITY)
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# Options: MEDIAN_OFF, KERNEL_3x3, KERNEL_5x5, KERNEL_7x7 (default)
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depth.initialConfig.setMedianFilter(dai.MedianFilter.KERNEL_7x7)
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depth.setInputResolution(1280, 800)
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depth.setLeftRightCheck(lr_check)
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depth.setExtendedDisparity(extended_disparity)
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depth.setSubpixel(subpixel)
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depth.setInputResolution(1280, 800)
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# Linking
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left.isp.link(depth.left)
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right.isp.link(depth.right)
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depth.disparity.link(xout.input)
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depth.rectifiedLeft.link(xoutl.input)
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depth.rectifiedRight.link(xoutr.input)
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# Connect to device and start pipeline
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with dai.Device(pipeline) as device:
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while not device.isClosed():
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queueNames = device.getQueueEvents()
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for q in queueNames:
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message = device.getOutputQueue(q).get()
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# Display arrived frames
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if type(message) == dai.ImgFrame:
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frame = message.getCvFrame()
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if 'disparity' in q:
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maxDisp = depth.initialConfig.getMaxDisparity()
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disp = (frame * (255.0 / maxDisp)).astype(np.uint8)
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disp = cv2.applyColorMap(disp, cv2.COLORMAP_JET)
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cv2.imshow(q, disp)
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else:
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cv2.imshow(q, frame)
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if cv2.waitKey(1) == ord('q'):
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break

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