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Merge remote-tracking branch 'origin/release_v2.23.0.0' into main
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‎.github/workflows/main.yml

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run: |
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python -m pip install --upgrade pip
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sudo apt install libusb-1.0-0-dev
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python -m pip install clang==14.0 --force-reinstall
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python -m pip install -r docs/requirements_mkdoc.txt
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- name: Configure project
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run: cmake -S . -B build -DDEPTHAI_PYTHON_FORCE_DOCSTRINGS=ON -DDEPTHAI_PYTHON_DOCSTRINGS_OUTPUT="$PWD/docstrings/depthai_python_docstring.hpp"
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run: echo "BUILD_COMMIT_HASH=${{github.sha}}" >> $GITHUB_ENV
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- name: Building wheel
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run: python3 -m pip wheel . -w ./wheelhouse/ --verbose
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- name: Auditing wheel
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run: for whl in wheelhouse/*.whl; do auditwheel repair "$whl" --plat linux_armv7l -w wheelhouse/audited/; done
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- name: Auditing wheels and adding armv6l tag (Running on RPi, binaries compiled as armv6l)
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run: |
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python3 -m pip install -U wheel auditwheel
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for whl in wheelhouse/*.whl; do auditwheel repair "$whl" --plat linux_armv7l -w wheelhouse/preaudited/; done
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for whl in wheelhouse/preaudited/*.whl; do python3 -m wheel tags --platform-tag +linux_armv6l "$whl"; done
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mkdir -p wheelhouse/audited/
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for whl in wheelhouse/preaudited/*linux_armv6l*.whl; do cp "$whl" wheelhouse/audited/$(basename $whl); done
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- name: Archive wheel artifacts
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uses: actions/upload-artifact@v3
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with:
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uses: codex-/return-dispatch@v1
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id: return_dispatch
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with:
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token: ${{ secrets.HIL_CORE_DISPATCH_TOKEN }} # Note this is NOT GITHUB_TOKEN but a PAT
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token: ${{ secrets.HIL_CORE_DISPATCH_TOKEN }} # Note this is NOT GITHUB_TOKEN but a PAT
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ref: main # or refs/heads/target_branch
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repo: depthai-core-hil-tests
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owner: luxonis
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workflow: regression_test.yml
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workflow_inputs: '{"commit": "${{ github.ref }}", "sha": "${{ github.sha }}", "parent_url": "https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}"}'
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workflow_timeout_seconds: 120 # Default: 300
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workflow_inputs: '{"commit": "${{ github.ref }}", "parent_url": "https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}"}'
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workflow_timeout_seconds: 300 # was 120 Default: 300
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- name: Release
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run: echo "https://github.com/luxonis/depthai-core-hil-tests/actions/runs/${{steps.return_dispatch.outputs.run_id}}" >> $GITHUB_STEP_SUMMARY

‎CMakeLists.txt

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set(depthai_dll_libraries "$<TARGET_RUNTIME_DLLS:${TARGET_NAME}>")
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endif()
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add_custom_command(TARGET ${TARGET_NAME} POST_BUILD COMMAND
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${CMAKE_COMMAND} -E copy ${depthai_dll_libraries} $<TARGET_FILE_DIR:${TARGET_NAME}>
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"$<$<BOOL:${depthai_dll_libraries}>:${CMAKE_COMMAND};-E;copy_if_different;${depthai_dll_libraries};$<TARGET_FILE_DIR:${TARGET_NAME}>>"
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COMMAND_EXPAND_LISTS
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VERBATIM
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)
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# Disable "d" postfix, so python can import the library as is

‎cmake/pybind11-mkdoc.cmake

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# Execute module pybind11_mkdoc to check if present
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message(STATUS "Checking for pybind11_mkdoc")
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execute_process(COMMAND ${PYTHON_EXECUTABLE} -m ${PYBIND11_MKDOC_MODULE_NAME} RESULT_VARIABLE error OUTPUT_QUIET ERROR_QUIET)
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execute_process(COMMAND ${PYTHON_EXECUTABLE} -m ${PYBIND11_MKDOC_MODULE_NAME} --help RESULT_VARIABLE error OUTPUT_QUIET ERROR_QUIET)
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if(error)
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set(message "Checking for pybind11_mkdoc - not found, docstrings not available")
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if(NOT enforce)

‎depthai-core

Submodule depthai-core updated 55 files

‎docs/requirements_mkdoc.txt

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git+https://github.com/luxonis/pybind11_mkdoc.git@59746f8d1645c9f00ebfb534186334d0154b5bd6
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git+https://github.com/luxonis/pybind11_mkdoc.git@da6c64251a0ebbc3ffc007477a0b9c9f20cac165
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libclang==16.0.6

‎docs/source/components/nodes/camera.rst

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Camera
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======
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Camera node is a source of :ref:`image frames <ImgFrame>`. You can control in at runtime with the :code:`InputControl` and :code:`InputConfig`.
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It aims to unify the :ref:`ColorCamera` and :ref:`MonoCamera` into one node.
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Compared to :ref:`ColorCamera` node, Camera node:
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- Supports **cam.setSize()**, which replaces both ``cam.setResolution()`` and ``cam.setIspScale()``. Camera node will automatically find resolution that fits best, and apply correct scaling to achieve user-selected size
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- Supports **cam.setCalibrationAlpha()**, example here: :ref:`Undistort camera stream`
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- Supports **cam.loadMeshData()** and **cam.setMeshStep()**, which can be used for custom image warping (undistortion, perspective correction, etc.)
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Besides points above, compared to :ref:`MonoCamera` node, Camera node:
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- Doesn't have ``out`` output, as it has the same outputs as :ref:`ColorCamera` (``raw``, ``isp``, ``still``, ``preview``, ``video``). This means that ``preview`` will output 3 planes of the same grayscale frame (3x overhead), and ``isp`` / ``video`` / ``still`` will output luma (useful grayscale information) + chroma (all values are 128), which will result in 1.5x bandwidth overhead
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How to place it
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###############
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.. tabs::
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.. code-tab:: py
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pipeline = dai.Pipeline()
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cam = pipeline.create(dai.node.Camera)
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.. code-tab:: c++
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dai::Pipeline pipeline;
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auto cam = pipeline.create<dai::node::Camera>();
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Inputs and Outputs
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##################
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.. code-block::
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Camera node
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┌──────────────────────────────┐
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│ ┌─────────────┐ │
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│ │ Image │ raw │ raw
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│ │ Sensor │---┬--------├────────►
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│ └────▲────────┘ | │
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│ │ ┌--------┘ │
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│ ┌─┴───▼─┐ │ isp
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inputControl │ │ │-------┬-------├────────►
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──────────────►│------│ ISP │ ┌─────▼────┐ │ video
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│ │ │ | |--├────────►
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│ └───────┘ │ Image │ │ still
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inputConfig │ │ Post- │--├────────►
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──────────────►│----------------|Processing│ │ preview
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│ │ │--├────────►
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│ └──────────┘ │
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└──────────────────────────────┘
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**Message types**
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- :code:`inputConfig` - :ref:`ImageManipConfig`
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- :code:`inputControl` - :ref:`CameraControl`
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- :code:`raw` - :ref:`ImgFrame` - RAW10 bayer data. Demo code for unpacking `here <https://github.com/luxonis/depthai-experiments/blob/3f1b2b2/gen2-color-isp-raw/main.py#L13-L32>`__
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- :code:`isp` - :ref:`ImgFrame` - YUV420 planar (same as YU12/IYUV/I420)
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- :code:`still` - :ref:`ImgFrame` - NV12, suitable for bigger size frames. The image gets created when a capture event is sent to the Camera, so it's like taking a photo
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- :code:`preview` - :ref:`ImgFrame` - RGB (or BGR planar/interleaved if configured), mostly suited for small size previews and to feed the image into :ref:`NeuralNetwork`
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- :code:`video` - :ref:`ImgFrame` - NV12, suitable for bigger size frames
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**ISP** (image signal processor) is used for bayer transformation, demosaicing, noise reduction, and other image enhancements.
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It interacts with the 3A algorithms: **auto-focus**, **auto-exposure**, and **auto-white-balance**, which are handling image sensor
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adjustments such as exposure time, sensitivity (ISO), and lens position (if the camera module has a motorized lens) at runtime.
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Click `here <https://en.wikipedia.org/wiki/Image_processor>`__ for more information.
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**Image Post-Processing** converts YUV420 planar frames from the **ISP** into :code:`video`/:code:`preview`/:code:`still` frames.
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``still`` (when a capture is triggered) and ``isp`` work at the max camera resolution, while ``video`` and ``preview`` are
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limited to max 4K (3840 x 2160) resolution, which is cropped from ``isp``.
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For IMX378 (12MP), the **post-processing** works like this:
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.. code-block::
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┌─────┐ Cropping to ┌─────────┐ Downscaling ┌──────────┐
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│ ISP ├────────────────►│ video ├───────────────►│ preview │
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└─────┘ max 3840x2160 └─────────┘ and cropping └──────────┘
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.. image:: /_static/images/tutorials/isp.jpg
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The image above is the ``isp`` output from the Camera (12MP resolution from IMX378). If you aren't downscaling ISP,
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the ``video`` output is cropped to 4k (max 3840x2160 due to the limitation of the ``video`` output) as represented by
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the blue rectangle. The Yellow rectangle represents a cropped ``preview`` output when the preview size is set to a 1:1 aspect
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ratio (eg. when using a 300x300 preview size for the MobileNet-SSD NN model) because the ``preview`` output is derived from
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the ``video`` output.
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Usage
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#####
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.. tabs::
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.. code-tab:: py
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pipeline = dai.Pipeline()
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cam = pipeline.create(dai.node.Camera)
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cam.setPreviewSize(300, 300)
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cam.setBoardSocket(dai.CameraBoardSocket.CAM_A)
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# Instead of setting the resolution, user can specify size, which will set
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# sensor resolution to best fit, and also apply scaling
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cam.setSize(1280, 720)
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.. code-tab:: c++
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dai::Pipeline pipeline;
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auto cam = pipeline.create<dai::node::Camera>();
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cam->setPreviewSize(300, 300);
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cam->setBoardSocket(dai::CameraBoardSocket::CAM_A);
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// Instead of setting the resolution, user can specify size, which will set
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// sensor resolution to best fit, and also apply scaling
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cam->setSize(1280, 720);
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Limitations
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###########
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Here are known camera limitations for the `RVC2 <https://docs.luxonis.com/projects/hardware/en/latest/pages/rvc/rvc2.html#rvc2>`__:
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- **ISP can process about 600 MP/s**, and about **500 MP/s** when the pipeline is also running NNs and video encoder in parallel
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- **3A algorithms** can process about **200..250 FPS overall** (for all camera streams). This is a current limitation of our implementation, and we have plans for a workaround to run 3A algorithms on every Xth frame, no ETA yet
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Examples of functionality
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#########################
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- :ref:`Undistort camera stream`
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Reference
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#########
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.. tabs::
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.. tab:: Python
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.. autoclass:: depthai.node.Camera
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:members:
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:inherited-members:
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:noindex:
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.. tab:: C++
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.. doxygenclass:: dai::node::Camera
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:project: depthai-core
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:members:
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:private-members:
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:undoc-members:
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.. include:: ../../includes/footer-short.rst

‎docs/source/components/nodes/warp.rst

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# Warp engines to be used (0,1,2)
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warp.setHwIds([1])
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# Warp interpolation mode, choose between BILINEAR, BICUBIC, BYPASS
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warp.setInterpolation(dai.node.Warp.Properties.Interpolation.BYPASS)
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warp.setInterpolation(dai.Interpolation.NEAREST_NEIGHBOR)
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.. code-tab:: c++
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‎docs/source/samples/Camera/camera_undistort.rst

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Undistort camera stream
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=======================
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This example shows how you can use :ref:`Camera` node to undistort wide FOV camera stream. :ref:`Camera` node will automatically undistort ``still``, ``video`` and ``preview`` streams, while ``isp`` stream will be left as is.
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Demo
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####
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.. figure:: https://github.com/luxonis/depthai-python/assets/18037362/936b9ad7-179b-42a5-a6cb-25efdbdf73d9
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Left: Camera.isp output. Right: Camera.video (undistorted) output
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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/Camera/camera_undistort.py>`__
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.. literalinclude:: ../../../../examples/Camera/camera_undistort.py
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:language: python
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:linenos:
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.. tab:: C++
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Work in progress.
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..
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Also `available on GitHub <https://github.com/luxonis/depthai-core/blob/main/examples/Camera/camera_undistort.cpp>`__
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.. literalinclude:: ../../../../depthai-core/examples/Camera/camera_undistort.cpp
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:language: cpp
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:linenos:
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.. include:: /includes/footer-short.rst

‎docs/source/tutorials/code_samples.rst

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../samples/bootloader/*
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../samples/calibration/*
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../samples/Camera/*
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../samples/ColorCamera/*
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../samples/crash_report/*
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../samples/EdgeDetector/*
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- :ref:`Calibration Reader` - Reads calibration data stored on device over XLink
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- :ref:`Calibration Load` - Loads and uses calibration data of version 6 (gen2 calibration data) in a pipeline
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.. rubric:: Camera
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- :ref:`Undistort camera stream` - Showcases how Camera node undistorts camera streams
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.. rubric:: ColorCamera
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- :ref:`Auto Exposure on ROI` - Demonstrates how to use auto exposure based on the selected ROI

‎examples/Camera/camera_undistort.py

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import depthai as dai
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import cv2
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pipeline = dai.Pipeline()
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# Define sources and outputs
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camRgb: dai.node.Camera = pipeline.create(dai.node.Camera)
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#Properties
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camRgb.setBoardSocket(dai.CameraBoardSocket.CAM_A)
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camRgb.setSize((1280, 800))
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# Linking
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videoOut = pipeline.create(dai.node.XLinkOut)
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videoOut.setStreamName("video")
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camRgb.video.link(videoOut.input)
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ispOut = pipeline.create(dai.node.XLinkOut)
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ispOut.setStreamName("isp")
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camRgb.isp.link(ispOut.input)
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with dai.Device(pipeline) as device:
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video = device.getOutputQueue(name="video", maxSize=1, blocking=False)
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isp = device.getOutputQueue(name="isp", maxSize=1, blocking=False)
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while True:
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if video.has():
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cv2.imshow("video", video.get().getCvFrame())
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if isp.has():
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cv2.imshow("isp", isp.get().getCvFrame())
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if cv2.waitKey(1) == ord('q'):
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break

‎examples/ColorCamera/rgb_preview.py

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if device.getBootloaderVersion() is not None:
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print('Bootloader version:', device.getBootloaderVersion())
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print('Device name:', device.getDeviceName())
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print('Device name:', device.getDeviceName(), ' Product name:', device.getProductName())
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# Output queue will be used to get the rgb frames from the output defined above
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qRgb = device.getOutputQueue(name="rgb", maxSize=4, blocking=False)

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