# DepthAI C++ API DepthAI C++ API can be found on Github [luxonis/depthai-core](https://github.com/luxonis/depthai-core). Below is the reference documentation for the C++ API. ### dai Kind: namespace #### dai::bootloader Kind: namespace ##### dai::bootloader::request Kind: namespace ###### dai::bootloader::request::BaseRequest Kind: struct ###### Command cmd Kind: variable ###### BaseRequest(Command command) Kind: function ###### dai::bootloader::request::UsbRomBoot Kind: struct ###### UsbRomBoot() Kind: function ###### dai::bootloader::request::BootApplication Kind: struct ###### BootApplication() Kind: function ###### dai::bootloader::request::UpdateFlash Kind: struct ###### uint32_t Storage Kind: enum ###### SBR Kind: enum_value ###### BOOTLOADER Kind: enum_value ###### Storage storage Kind: variable ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### UpdateFlash() Kind: function ###### dai::bootloader::request::GetBootloaderVersion Kind: struct ###### GetBootloaderVersion() Kind: function ###### dai::bootloader::request::BootMemory Kind: struct ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### BootMemory() Kind: function ###### dai::bootloader::request::UpdateFlashEx Kind: struct ###### Memory memory Kind: variable ###### Section section Kind: variable ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### UpdateFlashEx() Kind: function ###### dai::bootloader::request::UpdateFlashEx2 Kind: struct ###### Memory memory Kind: variable ###### uint32_t offset Kind: variable ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### UpdateFlashEx2() Kind: function ###### dai::bootloader::request::GetBootloaderType Kind: struct ###### GetBootloaderType() Kind: function ###### dai::bootloader::request::SetBootloaderConfig Kind: struct ###### Memory memory Kind: variable ###### int64_t offset Kind: variable ###### uint32_t clearConfig Kind: variable ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### SetBootloaderConfig() Kind: function ###### dai::bootloader::request::GetBootloaderConfig Kind: struct ###### Memory memory Kind: variable ###### int64_t offset Kind: variable ###### uint32_t maxSize Kind: variable ###### GetBootloaderConfig() Kind: function ###### dai::bootloader::request::BootloaderMemory Kind: struct ###### BootloaderMemory() Kind: function ###### dai::bootloader::request::GetBootloaderCommit Kind: struct ###### GetBootloaderCommit() Kind: function ###### dai::bootloader::request::UpdateFlashBootHeader Kind: struct ###### int32_t Type Kind: enum ###### GPIO_MODE Kind: enum_value ###### USB_RECOVERY Kind: enum_value ###### NORMAL Kind: enum_value ###### FAST Kind: enum_value ###### Type type Kind: variable ###### int64_t offset Kind: variable ###### int64_t location Kind: variable ###### int32_t dummyCycles Kind: variable ###### int32_t frequency Kind: variable ###### int32_t gpioMode Kind: variable ###### UpdateFlashBootHeader() Kind: function ###### dai::bootloader::request::ReadFlash Kind: struct ###### Memory memory Kind: variable ###### uint32_t offset Kind: variable ###### uint32_t totalSize Kind: variable ###### ReadFlash() Kind: function ###### dai::bootloader::request::GetApplicationDetails Kind: struct ###### Memory memory Kind: variable ###### GetApplicationDetails() Kind: function ###### dai::bootloader::request::GetMemoryDetails Kind: struct ###### Memory memory Kind: variable ###### GetMemoryDetails() Kind: function ###### dai::bootloader::request::IsUserBootloader Kind: struct ###### IsUserBootloader() Kind: function ###### uint32_t Command Kind: enum ###### USB_ROM_BOOT Kind: enum_value ###### BOOT_APPLICATION Kind: enum_value ###### UPDATE_FLASH Kind: enum_value ###### GET_BOOTLOADER_VERSION Kind: enum_value ###### BOOT_MEMORY Kind: enum_value ###### UPDATE_FLASH_EX Kind: enum_value ###### UPDATE_FLASH_EX_2 Kind: enum_value ###### NO_OP Kind: enum_value ###### GET_BOOTLOADER_TYPE Kind: enum_value ###### SET_BOOTLOADER_CONFIG Kind: enum_value ###### GET_BOOTLOADER_CONFIG Kind: enum_value ###### BOOTLOADER_MEMORY Kind: enum_value ###### GET_BOOTLOADER_COMMIT Kind: enum_value ###### UPDATE_FLASH_BOOT_HEADER Kind: enum_value ###### READ_FLASH Kind: enum_value ###### GET_APPLICATION_DETAILS Kind: enum_value ###### GET_MEMORY_DETAILS Kind: enum_value ###### IS_USER_BOOTLOADER Kind: enum_value ##### dai::bootloader::response Kind: namespace ###### dai::bootloader::response::BaseResponse Kind: struct ###### Command cmd Kind: variable ###### BaseResponse(Command command) Kind: function ###### dai::bootloader::response::FlashComplete Kind: struct ###### uint32_t success Kind: variable ###### char errorMsg Kind: variable ###### FlashComplete() Kind: function ###### dai::bootloader::response::FlashStatusUpdate Kind: struct ###### float progress Kind: variable ###### FlashStatusUpdate() Kind: function ###### dai::bootloader::response::BootloaderVersion Kind: struct ###### uint32_t major Kind: variable ###### uint32_t minor Kind: variable ###### uint32_t patch Kind: variable ###### BootloaderVersion() Kind: function ###### dai::bootloader::response::BootloaderType Kind: struct ###### Type type Kind: variable ###### BootloaderType() Kind: function ###### dai::bootloader::response::GetBootloaderConfig Kind: struct ###### uint32_t success Kind: variable ###### char errorMsg Kind: variable ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### GetBootloaderConfig() Kind: function ###### dai::bootloader::response::BootloaderMemory Kind: struct ###### Memory memory Kind: variable ###### BootloaderMemory() Kind: function ###### dai::bootloader::response::BootApplication Kind: struct ###### uint32_t success Kind: variable ###### char errorMsg Kind: variable ###### BootApplication() Kind: function ###### dai::bootloader::response::BootloaderCommit Kind: struct ###### char commitStr Kind: variable ###### BootloaderCommit() Kind: function ###### dai::bootloader::response::ReadFlash Kind: struct ###### uint32_t success Kind: variable ###### char errorMsg Kind: variable ###### uint32_t totalSize Kind: variable ###### uint32_t numPackets Kind: variable ###### ReadFlash() Kind: function ###### dai::bootloader::response::ApplicationDetails Kind: struct ###### uint32_t success Kind: variable ###### char errorMsg Kind: variable ###### uint32_t hasApplication Kind: variable ###### uint32_t hasFirmwareVersion Kind: variable ###### uint32_t hasApplicationName Kind: variable ###### char firmwareVersionStr Kind: variable ###### char applicationNameStr Kind: variable ###### ApplicationDetails() Kind: function ###### dai::bootloader::response::MemoryDetails Kind: struct ###### uint32_t hasMemory Kind: variable ###### Memory memory Kind: variable ###### int64_t memorySize Kind: variable ###### char memoryInfo Kind: variable ###### MemoryDetails() Kind: function ###### dai::bootloader::response::IsUserBootloader Kind: struct ###### uint32_t isUserBootloader Kind: variable ###### IsUserBootloader() Kind: function ###### dai::bootloader::response::NoOp Kind: struct ###### uint32_t invalidOp Kind: variable ###### NoOp() Kind: function ###### uint32_t Command Kind: enum ###### FLASH_COMPLETE Kind: enum_value ###### FLASH_STATUS_UPDATE Kind: enum_value ###### BOOTLOADER_VERSION Kind: enum_value ###### BOOTLOADER_TYPE Kind: enum_value ###### GET_BOOTLOADER_CONFIG Kind: enum_value ###### BOOTLOADER_MEMORY Kind: enum_value ###### BOOT_APPLICATION Kind: enum_value ###### BOOTLOADER_COMMIT Kind: enum_value ###### READ_FLASH Kind: enum_value ###### APPLICATION_DETAILS Kind: enum_value ###### MEMORY_DETAILS Kind: enum_value ###### IS_USER_BOOTLOADER Kind: enum_value ###### NO_OP Kind: enum_value ##### dai::bootloader::NetworkConfig Kind: struct ###### int timeoutMs Kind: variable If timeout < 0 - waits forever if timeout == 0 - no timeout if timeout > 0 - waits timeout milliseconds ###### std::uint32_t ipv4 Kind: variable ###### std::uint32_t ipv4Mask Kind: variable ###### std::uint32_t ipv4Gateway Kind: variable ###### std::uint32_t ipv4Dns Kind: variable ###### std::uint32_t ipv4DnsAlt Kind: variable ###### bool staticIpv4 Kind: variable ###### std::array< uint32_t, 4 > ipv6 Kind: variable ###### std::uint32_t ipv6Prefix Kind: variable ###### std::array< uint32_t, 4 > ipv6Gateway Kind: variable ###### std::array< uint32_t, 4 > ipv6Dns Kind: variable ###### std::array< uint32_t, 4 > ipv6DnsAlt Kind: variable ###### bool staticIpv6 Kind: variable ###### std::array< uint8_t, 6 > mac Kind: variable ##### dai::bootloader::UsbConfig Kind: struct ###### int timeoutMs Kind: variable If timeout < 0 - waits forever if timeout == 0 - no timeout if timeout > 0 - waits timeout milliseconds ###### int maxUsbSpeed Kind: variable UNKNOWN = 0, LOW, FULL, HIGH, SUPER, SUPER_PLUS ###### uint16_t vid Kind: variable VID/PID pair used by bootloader. ###### uint16_t pid Kind: variable ##### dai::bootloader::Config Kind: struct ###### Memory appMem Kind: variable ###### UsbConfig usb Kind: variable ###### NetworkConfig network Kind: variable ###### uint32_t userBlSize Kind: variable ###### uint32_t userBlChecksum Kind: variable ##### dai::bootloader::Structure Kind: struct ###### std::map< Section, long > offset Kind: variable ###### std::map< Section, long > size Kind: variable ###### Structure() Kind: function ##### dai::bootloader::NetworkBootloaderStructure Kind: struct ###### NetworkBootloaderStructure() Kind: function ##### dai::bootloader::UsbBootloaderStructure Kind: struct ###### UsbBootloaderStructure() Kind: function ##### std::int32_t Memory Kind: enum ###### AUTO Kind: enum_value ###### FLASH Kind: enum_value ###### EMMC Kind: enum_value ##### std::int32_t Section Kind: enum ###### AUTO Kind: enum_value ###### HEADER Kind: enum_value ###### BOOTLOADER Kind: enum_value ###### BOOTLOADER_CONFIG Kind: enum_value ###### APPLICATION Kind: enum_value ###### USER_BOOTLOADER Kind: enum_value ##### std::int32_t Type Kind: enum ###### AUTO Kind: enum_value ###### USB Kind: enum_value ###### NETWORK Kind: enum_value ##### constexpr static const char * XLINK_CHANNEL_BOOTLOADER Kind: variable ##### constexpr static const char * XLINK_CHANNEL_WATCHDOG Kind: variable ##### constexpr static std::uint32_t XLINK_STREAM_MAX_SIZE Kind: variable ##### constexpr static const std::chrono::milliseconds XLINK_WATCHDOG_TIMEOUT Kind: variable ##### DEPTHAI_BOOTLOADER_NLOHMANN_DEFINE_TYPE_OPTIONAL_NON_INTRUSIVE(NetworkConfig, timeoutMs, ipv4, ipv4Mask, ipv4Gateway, ipv4Dns, ipv4DnsAlt, staticIpv4, ipv6, ipv6Prefix, ipv6Gateway, ipv6Dns, ipv6DnsAlt, staticIpv6, mac) Kind: function ##### DEPTHAI_BOOTLOADER_NLOHMANN_DEFINE_TYPE_OPTIONAL_NON_INTRUSIVE(UsbConfig, timeoutMs, maxUsbSpeed, vid, pid) Kind: function ##### DEPTHAI_BOOTLOADER_NLOHMANN_DEFINE_TYPE_OPTIONAL_NON_INTRUSIVE(Config, appMem, usb, network, userBlSize, userBlChecksum) Kind: function ##### const Structure getStructure(Type type) Kind: function #### dai::build Kind: namespace ##### constexpr static bool HAVE_OPENCV_SUPPORT Kind: variable ##### constexpr static bool HAVE_LIBUSB_SUPPORT Kind: variable #### dai::device Kind: namespace ##### constexpr static const char * XLINK_CHANNEL_PIPELINE_CONFIG Kind: variable ##### constexpr static const char * XLINK_CHANNEL_MAIN_RPC Kind: variable ##### constexpr static const char * XLINK_CHANNEL_TIMESYNC Kind: variable ##### constexpr static const char * XLINK_CHANNEL_LOG Kind: variable ##### constexpr static const char * XLINK_CHANNEL_WATCHDOG Kind: variable ##### constexpr static std::uint32_t XLINK_USB_BUFFER_MAX_SIZE Kind: variable ##### constexpr static const std::chrono::milliseconds XLINK_USB_WATCHDOG_TIMEOUT Kind: variable ##### constexpr static const std::chrono::milliseconds XLINK_TCP_WATCHDOG_TIMEOUT Kind: variable ##### constexpr static const int XLINK_MESSAGE_METADATA_MAX_SIZE Kind: variable #### dai::filters Kind: namespace ##### dai::filters::params Kind: namespace ###### dai::filters::params::SpatialFilter Kind: struct 1D edge-preserving spatial filter using high-order domain transform. ###### bool enable Kind: variable Whether to enable or disable the filter. ###### std::uint8_t holeFillingRadius Kind: variable An in-place heuristic symmetric hole-filling mode applied horizontally during the filter passes. Intended to rectify minor artefacts with minimal performance impact. Search radius for hole filling. ###### float alpha Kind: variable The Alpha factor in an exponential moving average with Alpha=1 - no filter. Alpha = 0 - infinite filter. Determines the amount of smoothing. ###### std::int32_t delta Kind: variable Step-size boundary. Establishes the threshold used to preserve "edges". If the disparity value between neighboring pixels exceed the disparity threshold set by this delta parameter, then filtering will be temporarily disabled. Default value 0 means auto: 3 disparity integer levels. In case of subpixel mode it's 3*number of subpixel levels. ###### std::int32_t numIterations Kind: variable Number of iterations over the image in both horizontal and vertical direction. ###### DEPTHAI_SERIALIZE(SpatialFilter, enable, holeFillingRadius, alpha, delta, numIterations) Kind: function ###### dai::filters::params::TemporalFilter Kind: struct Temporal filtering with optional persistence. ###### int32_t PersistencyMode Kind: enum Persistency algorithm type. ###### PERSISTENCY_OFF Kind: enum_value ###### VALID_8_OUT_OF_8 Kind: enum_value ###### VALID_2_IN_LAST_3 Kind: enum_value ###### VALID_2_IN_LAST_4 Kind: enum_value ###### VALID_2_OUT_OF_8 Kind: enum_value ###### VALID_1_IN_LAST_2 Kind: enum_value ###### VALID_1_IN_LAST_5 Kind: enum_value ###### VALID_1_IN_LAST_8 Kind: enum_value ###### PERSISTENCY_INDEFINITELY Kind: enum_value ###### bool enable Kind: variable Whether to enable or disable the filter. ###### PersistencyMode persistencyMode Kind: variable Persistency mode. If the current disparity/depth value is invalid, it will be replaced by an older value, based on persistency mode. ###### float alpha Kind: variable The Alpha factor in an exponential moving average with Alpha=1 - no filter. Alpha = 0 - infinite filter. Determines the extent of the temporal history that should be averaged. ###### std::int32_t delta Kind: variable Step-size boundary. Establishes the threshold used to preserve surfaces (edges). If the disparity value between neighboring pixels exceed the disparity threshold set by this delta parameter, then filtering will be temporarily disabled. Default value 0 means auto: 3 disparity integer levels. In case of subpixel mode it's 3*number of subpixel levels. ###### DEPTHAI_SERIALIZE(TemporalFilter, enable, persistencyMode, alpha, delta) Kind: function ###### dai::filters::params::SpeckleFilter Kind: struct Speckle filtering. Removes speckle noise. ###### bool enable Kind: variable Whether to enable or disable the filter. ###### std::uint32_t speckleRange Kind: variable Speckle search range. ###### std::uint32_t differenceThreshold Kind: variable Maximum difference between neighbor disparity pixels to put them into the same blob. Units in disparity integer levels. ###### DEPTHAI_SERIALIZE(SpeckleFilter, enable, speckleRange, differenceThreshold) Kind: function ###### int32_t MedianFilter Kind: enum ###### MEDIAN_OFF Kind: enum_value ###### KERNEL_3x3 Kind: enum_value ###### KERNEL_5x5 Kind: enum_value ###### KERNEL_7x7 Kind: enum_value #### dai::impl Kind: namespace ##### dai::impl::_ImageManipMemory Kind: class ###### _ImageManipMemory() Kind: function ###### _ImageManipMemory(size_t size) Kind: function ###### _ImageManipMemory(span< uint8_t > data) Kind: function ###### uint8_t * data() Kind: function ###### const uint8_t * data() Kind: function ###### size_t size() Kind: function ###### span< uint8_t > getData() Kind: function ###### span< const uint8_t > getData() Kind: function ###### size_t getMaxSize() Kind: function ###### size_t getOffset() Kind: function ###### void setSize(size_t size) Kind: function ###### void setOffset(size_t offset) Kind: function ###### void shallowCopyFrom(_ImageManipMemory & other) Kind: function ###### std::shared_ptr< _ImageManipMemory > offset(size_t offset) Kind: function ##### dai::impl::_ImageManipBuffer Kind: class ###### _ImageManipBuffer() Kind: function ###### _ImageManipBuffer(size_t size) Kind: function ###### T * data() Kind: function ###### const T * data() Kind: function ###### size_t size() Kind: function ###### span< T > getData() Kind: function ###### span< const T > getData() Kind: function ##### dai::impl::FrameSpecs Kind: struct ###### uint32_t width Kind: variable ###### uint32_t height Kind: variable ###### uint32_t p1Offset Kind: variable ###### uint32_t p2Offset Kind: variable ###### uint32_t p3Offset Kind: variable ###### uint32_t p1Stride Kind: variable ###### uint32_t p2Stride Kind: variable ###### uint32_t p3Stride Kind: variable ##### dai::impl::UndistortOpenCvImpl Kind: class ###### BuildStatus Kind: enum ###### ONE_SHOT Kind: enum_value ###### TWO_SHOT Kind: enum_value ###### NOT_USED Kind: enum_value ###### NOT_BUILT Kind: enum_value ###### ERROR Kind: enum_value ###### UndistortOpenCvImpl(std::shared_ptr< spdlog::async_logger > logger) Kind: function ###### BuildStatus build(std::array< float, 9 > cameraMatrix, std::array< float, 9 > newCameraMatrix, std::vector< float > distCoeffs, dai::ImgFrame::Type type, uint32_t srcWidth, uint32_t srcHeight, uint32_t dstWidth, uint32_t dstHeight) Kind: function ###### void undistort(cv::Mat & src, cv::Mat & dst) Kind: function ##### dai::impl::Warp Kind: class ###### std::array< std::array< float, 3 >, 3 > matrix Kind: variable ###### ImageManipOpsBase < Container >::Background background Kind: variable ###### uint32_t backgroundColor Kind: variable ###### bool enableUndistort Kind: variable ###### bool undistortOneShot Kind: variable ###### ImgFrame::Type type Kind: variable ###### FrameSpecs srcSpecs Kind: variable ###### FrameSpecs dstSpecs Kind: variable ###### size_t sourceMinX Kind: variable ###### size_t sourceMinY Kind: variable ###### size_t sourceMaxX Kind: variable ###### size_t sourceMaxY Kind: variable ###### Warp() Kind: function ###### Warp(std::shared_ptr< spdlog::async_logger > logger) Kind: function ###### ~Warp() Kind: function ###### void init(ImageManipProperties &) Kind: function ###### void build(const FrameSpecs srcFrameSpecs, const FrameSpecs dstFrameSpecs, const ImgFrame::Type type, const std::array< std::array< float, 3 >, 3 > matrix, std::vector< std::array< std::array< float, 2 >, 4 >> srcCorners) Kind: function ###### void buildUndistort(bool enable, const std::array< float, 9 > & cameraMatrix, const std::array< float, 9 > & newCameraMatrix, const std::vector< float > & distCoeffs, const ImgFrame::Type type, const uint32_t srcWidth, const uint32_t srcHeight, const uint32_t dstWidth, const uint32_t dstHeight) Kind: function ###### void apply(const std::shared_ptr< ImageManipData > src, std::shared_ptr< ImageManipData > dst) Kind: function ###### void setLogger(std::shared_ptr< spdlog::async_logger > logger) Kind: function ###### Warp & setBackgroundColor(uint32_t r, uint32_t g, uint32_t b) Kind: function ##### dai::impl::WarpH Kind: class ###### void build(const FrameSpecs srcFrameSpecs, const FrameSpecs dstFrameSpecs, const ImgFrame::Type type, const std::array< std::array< float, 3 >, 3 > matrix, std::vector< std::array< std::array< float, 2 >, 4 >> srcCorners) Kind: function ###### void buildUndistort(bool enable, const std::array< float, 9 > & cameraMatrix, const std::array< float, 9 > & newCameraMatrix, const std::vector< float > & distCoeffs, const ImgFrame::Type type, const uint32_t srcWidth, const uint32_t srcHeight, const uint32_t dstWidth, const uint32_t dstHeight) Kind: function ###### void apply(const std::shared_ptr< ImageManipData > src, std::shared_ptr< ImageManipData > dst) Kind: function ##### dai::impl::ColorChange Kind: class ###### ColorChange() Kind: function ###### ColorChange(std::shared_ptr< spdlog::async_logger > logger) Kind: function ###### void setLogger(std::shared_ptr< spdlog::async_logger > logger) Kind: function ###### void build(const FrameSpecs srcFrameSpecs, const FrameSpecs dstFrameSpecs, const ImgFrame::Type typeFrom, const ImgFrame::Type typeTo) Kind: function ###### void apply(const std::shared_ptr< ImageManipData > src, std::shared_ptr< ImageManipData > dst) Kind: function ##### dai::impl::ImageManipOperations Kind: class ###### ImageManipOperations(ImageManipProperties props, std::shared_ptr< spdlog::async_logger > logger) Kind: function ###### ImageManipOperations & build(const ImageManipOpsBase < Container > & base, ImgFrame::Type outputFrameType, FrameSpecs srcFrameSpecs, ImgFrame::Type type) Kind: function ###### ImageManipOperations & buildUndistort(bool enable, const std::array< float, 9 > & cameraMatrix, const std::array< float, 9 > & newCameraMatrix, const std::vector< float > & distCoeffs, const ImgFrame::Type type, const uint32_t srcWidth, const uint32_t srcHeight, const uint32_t dstWidth, const uint32_t dstHeight) Kind: function ###### bool apply(const std::shared_ptr< ImageManipData > src, std::shared_ptr< ImageManipData > dst) Kind: function ###### size_t getOutputPlaneSize(uint8_t plane) Kind: function ###### size_t getOutputSize() Kind: function ###### size_t getOutputWidth() Kind: function ###### size_t getOutputHeight() Kind: function ###### size_t getOutputStride(uint8_t plane) Kind: function ###### FrameSpecs getOutputFrameSpecs(ImgFrame::Type type) Kind: function ###### ImgFrame::Type getOutputFrameType() Kind: function ###### std::vector< RotatedRect > getSrcCrops() Kind: function ###### std::array< std::array< float, 3 >, 3 > getMatrix() Kind: function ###### bool undistortEnabled() Kind: function ###### std::string toString() Kind: function ##### dai::impl::overloaded Kind: struct ##### constexpr ImgFrame::Type VALID_TYPE_COLOR Kind: variable ##### constexpr ImgFrame::Type VALID_TYPE_GRAY Kind: variable ##### void loop(N & node, const ImageManipConfig & initialConfig, std::shared_ptr< spdlog::async_logger > logger, std::function< size_t(const ImageManipConfig &, const ImgFrame &)> build, std::function< bool(std::shared_ptr< Memory > &, std::shared_ptr< ImageManipData >)> apply, std::function< void(const ImgFrame &, ImgFrame &)> getFrame) Kind: function ##### FrameSpecs getSrcFrameSpecs(dai::ImgFrame::Specs srcSpecs) Kind: function ##### size_t getAlignedOutputFrameSize(ImgFrame::Type type, size_t width, size_t height) Kind: function ##### constexpr T ALIGN_UP(T value, std::size_t alignment) Kind: function ##### FrameSpecs getCcDstFrameSpecs(FrameSpecs srcSpecs, dai::ImgFrame::Type from, dai::ImgFrame::Type to) Kind: function ##### FrameSpecs getDstFrameSpecs(size_t width, size_t height, dai::ImgFrame::Type type) Kind: function ##### void transformOpenCV(const uint8_t * src, uint8_t * dst, const size_t srcWidth, const size_t srcHeight, const size_t srcStride, const size_t dstWidth, const size_t dstHeight, const size_t dstStride, const uint16_t numChannels, const uint16_t bpp, const std::array< std::array< float, 3 >, 3 > matrix, const std::vector< uint32_t > & background, const FrameSpecs & srcImgSpecs, const size_t sourceMinX, const size_t sourceMinY, const size_t sourceMaxX, const size_t sourceMaxY) Kind: function ##### void transformFastCV(const uint8_t * src, uint8_t * dst, const size_t srcWidth, const size_t srcHeight, const size_t srcStride, const size_t dstWidth, const size_t dstHeight, const size_t dstStride, const uint16_t numChannels, const uint16_t bpp, const std::array< std::array< float, 3 >, 3 > matrix, const std::vector< uint32_t > & background, const FrameSpecs & srcImgSpecs, const size_t sourceMinX, const size_t sourceMinY, const size_t sourceMaxX, const size_t sourceMaxY, uint32_t * fastCvBorder) Kind: function ##### int clampi(int val, int minv, int maxv) Kind: function ##### float clampf(float val, float minv, float maxv) Kind: function ##### bool isTypeSupported(dai::ImgFrame::Type type) Kind: function ##### bool getFrameTypeInfo(dai::ImgFrame::Type outFrameType, int & outNumPlanes, float & outBpp) Kind: function ##### void YUVfromRGB(float & Y, float & U, float & V, const float R, const float G, const float B) Kind: function ##### void RGBfromYUV(float & R, float & G, float & B, float Y, float U, float V) Kind: function ##### overloaded(Ts...) Kind: function ##### bool floatEq(float a, float b) Kind: function ##### bool isSingleChannelu8(const std::shared_ptr< dai::ImgFrame > img) Kind: function ##### bool isSingleChannelu8(const dai::ImgFrame::Type type) Kind: function ##### bool isSingleChannel(const dai::ImgFrame::Type type) Kind: function ##### std::string getOpStr(const T & op) Kind: function ##### std::string getConfigString(const dai::ImageManipOpsBase < C > & ops) Kind: function ##### std::array< std::array< float, 3 >, 3 > matmul(std::array< std::array< float, 3 >, 3 > A, std::array< std::array< float, 3 >, 3 > B) Kind: function ##### std::array< float, 2 > matvecmul(std::array< std::array< float, 3 >, 3 > M, std::array< float, 2 > vec) Kind: function ##### std::array< float, 2 > matvecmul(std::array< std::array< float, 2 >, 2 > M, std::array< float, 2 > vec) Kind: function ##### std::tuple< float, float, float, float > getOuterRect(const std::vector< std::array< float, 2 >> points) Kind: function ##### std::vector< std::array< float, 2 > > getHull(const std::vector< std::array< float, 2 >> points) Kind: function ##### dai::RotatedRect getOuterRotatedRect(const std::vector< std::array< float, 2 >> & points) Kind: function ##### std::array< std::array< float, 3 >, 3 > getResizeMat(Resize o, float width, float height, uint32_t outputWidth, uint32_t outputHeight) Kind: function ##### void getTransformImpl(const ManipOp & op, std::array< std::array< float, 3 >, 3 > & transform, std::array< std::array< float, 2 >, 4 > & imageCorners, std::vector< std::array< std::array< float, 2 >, 4 >> & srcCorners, uint32_t & outputWidth, uint32_t & outputHeight) Kind: function ##### std::tuple< std::array< std::array< float, 3 >, 3 >, std::array< std::array< float, 2 >, 4 >, std::vector< std::array< std::array< float, 2 >, 4 > > > getTransform(const C & ops, uint32_t inputWidth, uint32_t inputHeight, uint32_t outputWidth, uint32_t outputHeight) Kind: function ##### void getOutputSizeFromCorners(const std::array< std::array< float, 2 >, 4 > & corners, const bool center, const std::array< std::array< float, 3 >, 3 > transformInv, const uint32_t srcWidth, const uint32_t srcHeight, uint32_t & outputWidth, uint32_t & outputHeight) Kind: function ##### std::tuple< std::array< std::array< float, 3 >, 3 >, std::array< std::array< float, 2 >, 4 >, std::vector< std::array< std::array< float, 2 >, 4 > > > getFullTransform(dai::ImageManipOpsBase < C > & base, size_t inputWidth, size_t inputHeight, dai::ImgFrame::Type type, dai::ImgFrame::Type outputFrameType, C & outputOps) Kind: function ##### dai::ImgFrame::Type getValidType(dai::ImgFrame::Type type) Kind: function ##### size_t getFrameSize(const ImgFrame::Type type, const FrameSpecs & specs) Kind: function ##### void printSpecs(spdlog::async_logger & logger, FrameSpecs specs) Kind: function #### dai::internal Kind: namespace ##### dai::internal::VariantSwitch Kind: struct ###### void operator()(int index, json const & value, Variant & v) Kind: function ##### dai::internal::VariantSwitch< 0 > Kind: struct ###### void operator()(int index, json const & value, Variant & v) Kind: function ##### dai::internal::VariantReadNop Kind: struct ###### void operator()(int index, Reader * reader, Variant & v) Kind: function ##### dai::internal::VariantReadNop< 0 > Kind: struct ###### void operator()(int index, Reader * reader, Variant & v) Kind: function ##### dai::internal::XLinkInProperties Kind: struct Specify properties for XLinkIn such as stream name, ... ###### std::string streamName Kind: variable Name of stream ###### std::uint32_t maxDataSize Kind: variable Maximum input data size: NV12 --> 1.5 = (3/2) bytes per pixel, roughly 17.6MB for a 4032x3056 frame ###### std::uint32_t numFrames Kind: variable Number of frames in pool ###### ~XLinkInProperties() Kind: function ##### dai::internal::XLinkOutProperties Kind: struct Specify properties for XLinkOut such as stream name, ... ###### float maxFpsLimit Kind: variable Set a limit to how many packets will be sent further to host ###### std::string streamName Kind: variable Name of stream ###### bool metadataOnly Kind: variable Whether to transfer data or only object attributes ###### int packetSize Kind: variable Max bytes per packet (-1 = unlimited) ###### int bytesPerSecondLimit Kind: variable Maximal bytes per second (-1 = unlimited) ###### ~XLinkOutProperties() Kind: function ##### DEPTHAI_SERIALIZE_EXT(XLinkInProperties, streamName, maxDataSize, numFrames) Kind: function ##### DEPTHAI_SERIALIZE_EXT(XLinkOutProperties, maxFpsLimit, streamName, metadataOnly, packetSize, bytesPerSecondLimit) Kind: function #### dai::matrix Kind: namespace ##### constexpr float MATRIX_EQ_EPSILON Kind: variable ##### std::array< std::array< float, 3 >, 3 > matMul(const std::array< std::array< float, 3 >, 3 > & A, const std::array< std::array< float, 3 >, 3 > & B) Kind: function ##### std::vector< std::vector< float > > matMul(const std::vector< std::vector< float >> & A, const std::vector< std::vector< float >> & B) Kind: function ##### std::array< std::array< float, 4 >, 4 > matMul(const std::array< std::array< float, 4 >, 4 > & A, const std::array< std::array< float, 4 >, 4 > & B) Kind: function ##### std::vector< float > matVecMul(const std::vector< std::vector< float >> & matrix, const std::vector< float > & vec) Kind: function ##### std::array< float, 3 > matVecMul(const std::array< std::array< float, 3 >, 3 > & matrix, const std::array< float, 3 > & vec) Kind: function ##### bool mateq(const std::vector< std::vector< float >> & A, const std::vector< std::vector< float >> & B, float epsilon) Kind: function ##### bool mateq(const std::array< std::array< float, 3 >, 3 > & A, const std::array< std::array< float, 3 >, 3 > & B, float epsilon) Kind: function ##### bool matInv(std::vector< std::vector< float >> & A, std::vector< std::vector< float >> & inverse) Kind: function ##### std::array< std::array< float, 2 >, 2 > getMatrixInverse(const std::array< std::array< float, 2 >, 2 > & matrix) Kind: function ##### std::array< std::array< float, 3 >, 3 > getMatrixInverse(const std::array< std::array< float, 3 >, 3 > & matrix) Kind: function ##### std::array< std::array< float, 3 >, 3 > getHomographyMatrix(const std::array< dai::Point2f , 4 > & srcPoints, const std::array< dai::Point2f , 4 > & dstPoints) Kind: function ##### std::vector< std::vector< float > > createRotationMatrix(float theta) Kind: function ##### std::vector< std::vector< float > > createScalingMatrix(float scaleX, float scaleY) Kind: function ##### std::vector< std::vector< float > > createTranslationMatrix(float dx, float dy) Kind: function ##### std::array< std::array< float, 4 >, 4 > createTransformationMatrix(const std::vector< std::vector< float >> & rotation, const dai::Point3f & translation) Kind: function ##### std::array< std::array< float, 4 >, 4 > createTransformationMatrix(const std::array< std::array< float, 3 >, 3 > & rotation, const dai::Point3f & translation) Kind: function ##### dai::Point3f transformPoint3f(const std::array< std::array< float, 4 >, 4 > & matrix, const dai::Point3f & point) Kind: function ##### std::array< float, 4 > dehomogenizePoint4(const std::array< float, 4 > & point) Kind: function ##### std::array< float, 3 > dehomogenizePoint3(const std::array< float, 3 > & point) Kind: function ##### std::vector< float > matrixToVector(const std::vector< std::vector< float >> & R) Kind: function ##### std::vector< float > matrix3x3ToVector(const std::array< std::array< float, 3 >, 3 > & R) Kind: function ##### std::vector< float > rotationMatrixToVector(const std::vector< std::vector< float >> & R) Kind: function ##### std::vector< std::vector< float > > matrix3x3ToVectorMatrix(const std::array< std::array< float, 3 >, 3 > & R) Kind: function ##### std::array< std::array< float, 3 >, 3 > vectorMatrixToMatrix3x3(const std::vector< std::vector< float >> & R) Kind: function ##### std::array< std::array< float, 3 >, 3 > getRotationMatrixFromProjection4x4(const std::array< std::array< float, 4 >, 4 > & projection) Kind: function ##### std::vector< std::vector< float > > rvecToRotationMatrix(const double rvec) Kind: function ##### void invertSe3Matrix4x4InPlace(std::vector< std::vector< float >> & mat) Kind: function ##### std::array< std::array< float, 4 >, 4 > invertSe3Matrix4x4(const std::array< std::array< float, 4 >, 4 > & matrix) Kind: function ##### void printMatrix(std::vector< std::vector< float >> & matrix) Kind: function ##### std::vector< std::vector< float > > toVecMatrix4x4(const std::array< std::array< float, 4 >, 4 > & m) Kind: function ##### bool isIdentity4x4(const std::vector< std::vector< float >> & m, float epsilon) Kind: function ##### std::array< std::array< float, 3 >, 3 > cvMatToMatrix3x3(const cv::Mat & cvMat) Kind: function ##### std::array< std::array< float, 4 >, 4 > cvMatToMatrix4x4(const cv::Mat & cvMat) Kind: function ##### cv::Mat matrix3x3ToCvMat(const std::array< std::array< float, 3 >, 3 > & matrix) Kind: function ##### cv::Mat matrix4x4ToCvMat(const std::array< std::array< float, 4 >, 4 > & matrix) Kind: function #### dai::model Kind: namespace ##### ModelType Kind: enum Neural network model type. ###### BLOB Kind: enum_value ###### SUPERBLOB Kind: enum_value ###### DLC Kind: enum_value ###### NNARCHIVE Kind: enum_value ###### OTHER Kind: enum_value ##### ModelType readModelType(const std::filesystem::path & modelPath) Kind: function Read model type from model path. parameters: modelPath: Path to model return: ModelType #### dai::modelzoo Kind: namespace ##### void setHealthEndpoint(const std::string & endpoint) Kind: function Set the health endpoint (for internet check) parameters: endpoint: ##### void setDownloadEndpoint(const std::string & endpoint) Kind: function Set the download endpoint (for model querying) parameters: endpoint: ##### void setDefaultCachePath(const fs::path & path) Kind: function Set the default cache path (where models are cached) parameters: path: ##### void setDefaultModelsPath(const fs::path & path) Kind: function Set the default models path (where yaml files are stored) parameters: path: ##### std::string getHealthEndpoint() Kind: function Get the health endpoint (for internet check) ##### std::string getDownloadEndpoint() Kind: function Get the download endpoint (for model querying) ##### fs::path getDefaultCachePath() Kind: function Get the default cache path (where models are cached) ##### fs::path getDefaultModelsPath() Kind: function Get the default models path (where yaml files are stored) #### dai::nn_archive Kind: namespace ##### dai::nn_archive::v1 Kind: namespace ###### dai::nn_archive::v1::Config Kind: struct The main class of the multi/single-stage model config scheme (multi- stage models consists of interconnected single-stage models). @type config_version: str @ivar config_version: String representing config schema version in format 'x.y' where x is major version and y is minor version @type model: Model @ivar model: A Model object representing the neural network used in the archive. The main class of the multi/single-stage model config scheme (multi- stage models consists of interconnected single-stage models). @type config_version: str @ivar config_version: String representing config schema version in format 'x.y' where x is major version and y is minor version @type model: Model @ivar model: A Model object representing the neural network used in the archive. ###### std::optional< std::string > configVersion Kind: variable String representing config schema version in format 'x.y' where x is major version and y is minor version. ###### Model model Kind: variable A Model object representing the neural network used in the archive. ###### dai::nn_archive::v1::Head Kind: struct Represents head of a model. @type name: str | None @ivar name: Optional name of the head. @type parser: str @ivar parser: Name of the parser responsible for processing the models output. @type outputs: List[str] | None @ivar outputs: Specify which outputs are fed into the parser. If None, all outputs are fed. @type metadata: C{HeadMetadata} | C{HeadObjectDetectionMetadata} | C{HeadClassificationMetadata} | C{HeadObjectDetectionSSDMetadata} | C{HeadSegmentationMetadata} | C{HeadYOLOMetadata} @ivar metadata: Metadata of the parser. Represents head of a model. @type name: str | None @ivar name: Optional name of the head. @type parser: str @ivar parser: Name of the parser responsible for processing the models output. @type outputs: List[str] | None @ivar outputs: Specify which outputs are fed into the parser. If None, all outputs are fed. @type metadata: C{HeadMetadata} | C{HeadObjectDetectionMetadata} | C{HeadClassificationMetadata} | C{HeadObjectDetectionSSDMetadata} | C{HeadSegmentationMetadata} | C{HeadYOLOMetadata} @ivar metadata: Metadata of the parser. ###### Metadata metadata Kind: variable Metadata of the parser. ###### std::optional< std::string > name Kind: variable Optional name of the head. ###### std::optional< std::vector< std::string > > outputs Kind: variable Specify which outputs are fed into the parser. If None, all outputs are fed. ###### std::string parser Kind: variable Name of the parser responsible for processing the models output. ###### dai::nn_archive::v1::Input Kind: struct Represents input stream of a model. @type name: str @ivar name: Name of the input layer. @type dtype: DataType @ivar dtype: Data type of the input data (e.g., 'float32'). @type input_type: InputType @ivar input_type: Type of input data (e.g., 'image'). @type shape: list @ivar shape: Shape of the input data as a list of integers (e.g. [H,W], [H,W,C], [N,H,W,C], ...). @type layout: str @ivar layout: Lettercode interpretation of the input data dimensions (e.g., 'NCHW'). @type preprocessing: PreprocessingBlock @ivar preprocessing: Preprocessing steps applied to the input data. Represents input stream of a model. @type name: str @ivar name: Name of the input layer. @type dtype: DataType @ivar dtype: Data type of the input data (e.g., 'float32'). @type input_type: InputType @ivar input_type: Type of input data (e.g., 'image'). @type shape: list @ivar shape: Shape of the input data as a list of integers (e.g. [H,W], [H,W,C], [N,H,W,C], ...). @type layout: str @ivar layout: Lettercode interpretation of the input data dimensions (e.g., 'NCHW'). @type preprocessing: PreprocessingBlock @ivar preprocessing: Preprocessing steps applied to the input data. ###### DataType dtype Kind: variable Data type of the input data (e.g., 'float32'). ###### InputType inputType Kind: variable Type of input data (e.g., 'image'). ###### std::optional< std::string > layout Kind: variable Lettercode interpretation of the input data dimensions (e.g., 'NCHW') ###### std::string name Kind: variable Name of the input layer. ###### PreprocessingBlock preprocessing Kind: variable Preprocessing steps applied to the input data. ###### std::vector< int64_t > shape Kind: variable Shape of the input data as a list of integers (e.g. [H,W], [H,W,C], [N,H,W,C], ...). ###### dai::nn_archive::v1::Metadata Kind: struct Metadata of the parser. Metadata for the object detection head. @type classes: list @ivar classes: Names of object classes detected by the model. @type n_classes: int @ivar n_classes: Number of object classes detected by the model. @type iou_threshold: float @ivar iou_threshold: Non-max supression threshold limiting boxes intersection. @type conf_threshold: float @ivar conf_threshold: Confidence score threshold above which a detected object is considered valid. @type max_det: int @ivar max_det: Maximum detections per image. @type anchors: list @ivar anchors: Predefined bounding boxes of different sizes and aspect ratios. The innermost lists are length 2 tuples of box sizes. The middle lists are anchors for each output. The outmost lists go from smallest to largest output. Metadata for the classification head. @type classes: list @ivar classes: Names of object classes classified by the model. @type n_classes: int @ivar n_classes: Number of object classes classified by the model. @type is_softmax: bool @ivar is_softmax: True, if output is already softmaxed Metadata for the SSD object detection head. @type boxes_outputs: str @ivar boxes_outputs: Output name corresponding to predicted bounding box coordinates. @type scores_outputs: str @ivar scores_outputs: Output name corresponding to predicted bounding box confidence scores. Metadata for the segmentation head. @type classes: list @ivar classes: Names of object classes segmented by the model. @type n_classes: int @ivar n_classes: Number of object classes segmented by the model. @type is_softmax: bool @ivar is_softmax: True, if output is already softmaxed Metadata for the YOLO head. @type yolo_outputs: list @ivar yolo_outputs: A list of output names for each of the different YOLO grid sizes. @type mask_outputs: list | None @ivar mask_outputs: A list of output names for each mask output. @type protos_outputs: str | None @ivar protos_outputs: Output name for the protos. @type keypoints_outputs: list | None @ivar keypoints_outputs: A list of output names for the keypoints. @type angles_outputs: list | None @ivar angles_outputs: A list of output names for the angles. @type subtype: str @ivar subtype: YOLO family decoding subtype (e.g. yolov5, yolov6, yolov7 etc.) @type n_prototypes: int | None @ivar n_prototypes: Number of prototypes per bbox in YOLO instance segmnetation. @type n_keypoints: int | None @ivar n_keypoints: Number of keypoints per bbox in YOLO keypoint detection. @type is_softmax: bool | None @ivar is_softmax: True, if output is already softmaxed in YOLO instance segmentation Metadata for the basic head. It allows you to specify additional fields. @type postprocessor_path: str | None @ivar postprocessor_path: Path to the postprocessor. Metadata of the parser. Metadata for the object detection head. @type classes: list @ivar classes: Names of object classes detected by the model. @type n_classes: int @ivar n_classes: Number of object classes detected by the model. @type iou_threshold: float @ivar iou_threshold: Non-max supression threshold limiting boxes intersection. @type conf_threshold: float @ivar conf_threshold: Confidence score threshold above which a detected object is considered valid. @type max_det: int @ivar max_det: Maximum detections per image. @type anchors: list @ivar anchors: Predefined bounding boxes of different sizes and aspect ratios. The innermost lists are length 2 tuples of box sizes. The middle lists are anchors for each output. The outmost lists go from smallest to largest output. Metadata for the classification head. @type classes: list @ivar classes: Names of object classes classified by the model. @type n_classes: int @ivar n_classes: Number of object classes classified by the model. @type is_softmax: bool @ivar is_softmax: True, if output is already softmaxed Metadata for the SSD object detection head. @type boxes_outputs: str @ivar boxes_outputs: Output name corresponding to predicted bounding box coordinates. @type scores_outputs: str @ivar scores_outputs: Output name corresponding to predicted bounding box confidence scores. Metadata for the segmentation head. @type classes: list @ivar classes: Names of object classes segmented by the model. @type n_classes: int @ivar n_classes: Number of object classes segmented by the model. @type is_softmax: bool @ivar is_softmax: True, if output is already softmaxed Metadata for the YOLO head. @type yolo_outputs: list @ivar yolo_outputs: A list of output names for each of the different YOLO grid sizes. @type mask_outputs: list | None @ivar mask_outputs: A list of output names for each mask output. @type protos_outputs: str | None @ivar protos_outputs: Output name for the protos. @type keypoints_outputs: list | None @ivar keypoints_outputs: A list of output names for the keypoints. @type angles_outputs: list | None @ivar angles_outputs: A list of output names for the angles. @type subtype: str @ivar subtype: YOLO family decoding subtype (e.g. yolov5, yolov6, yolov7 etc.) @type n_prototypes: int | None @ivar n_prototypes: Number of prototypes per bbox in YOLO instance segmnetation. @type n_keypoints: int | None @ivar n_keypoints: Number of keypoints per bbox in YOLO keypoint detection. @type is_softmax: bool | None @ivar is_softmax: True, if output is already softmaxed in YOLO instance segmentation Metadata for the basic head. It allows you to specify additional fields. @type postprocessor_path: str | None @ivar postprocessor_path: Path to the postprocessor. ###### std::optional< std::vector< std::vector< std::vector< double > > > > anchors Kind: variable Predefined bounding boxes of different sizes and aspect ratios. The innermost lists are length 2 tuples of box sizes. The middle lists are anchors for each output. The outmost lists go from smallest to largest output. ###### std::optional< std::vector< std::string > > classes Kind: variable Names of object classes recognized by the model. ###### std::optional< double > confThreshold Kind: variable Confidence score threshold above which a detected object is considered valid. ###### std::optional< double > iouThreshold Kind: variable Non-max supression threshold limiting boxes intersection. ###### std::optional< int64_t > maxDet Kind: variable Maximum detections per image. ###### std::optional< int64_t > nClasses Kind: variable Number of object classes recognized by the model. ###### std::optional< std::string > postprocessorPath Kind: variable Path to the postprocessor. ###### std::optional< bool > isSoftmax Kind: variable True, if output is already softmaxed. True, if output is already softmaxed in YOLO instance segmentation. ###### std::optional< std::string > boxesOutputs Kind: variable Output name corresponding to predicted bounding box coordinates. ###### std::optional< std::string > scoresOutputs Kind: variable Output name corresponding to predicted bounding box confidence scores. ###### std::optional< std::vector< std::string > > anglesOutputs Kind: variable A list of output names for the angles. ###### std::optional< std::vector< std::string > > keypointsOutputs Kind: variable A list of output names for the keypoints. ###### std::optional< std::vector< std::string > > maskOutputs Kind: variable A list of output names for each mask output. ###### std::optional< int64_t > nKeypoints Kind: variable Number of keypoints per bbox in YOLO keypoint detection. ###### std::optional< int64_t > nPrototypes Kind: variable Number of prototypes per bbox in YOLO instance segmnetation. ###### std::optional< std::string > protosOutputs Kind: variable Output name for the protos. ###### std::optional< std::string > subtype Kind: variable YOLO family decoding subtype (e.g. yolov5, yolov6, yolov7 etc.). ###### std::optional< std::vector< std::string > > yoloOutputs Kind: variable A list of output names for each of the different YOLO grid sizes. ###### nlohmann::json extraParams Kind: variable Additional parameters ###### dai::nn_archive::v1::MetadataClass Kind: struct Metadata object defining the model metadata. Represents metadata of a model. @type name: str @ivar name: Name of the model. @type path: str @ivar path: Relative path to the model executable. Metadata object defining the model metadata. Represents metadata of a model. @type name: str @ivar name: Name of the model. @type path: str @ivar path: Relative path to the model executable. ###### std::string name Kind: variable Name of the model. ###### std::string path Kind: variable Relative path to the model executable. ###### std::optional< DataType > precision Kind: variable Precision of the model weights. ###### dai::nn_archive::v1::Model Kind: struct A Model object representing the neural network used in the archive. Class defining a single-stage model config scheme. @type metadata: Metadata @ivar metadata: Metadata object defining the model metadata. @type inputs: list @ivar inputs: List of Input objects defining the model inputs. @type outputs: list @ivar outputs: List of Output objects defining the model outputs. @type heads: list @ivar heads: List of Head objects defining the model heads. If not defined, we assume a raw output. A Model object representing the neural network used in the archive. Class defining a single-stage model config scheme. @type metadata: Metadata @ivar metadata: Metadata object defining the model metadata. @type inputs: list @ivar inputs: List of Input objects defining the model inputs. @type outputs: list @ivar outputs: List of Output objects defining the model outputs. @type heads: list @ivar heads: List of Head objects defining the model heads. If not defined, we assume a raw output. ###### std::optional< std::vector< Head > > heads Kind: variable List of Head objects defining the model heads. If not defined, we assume a raw output. ###### std::vector< Input > inputs Kind: variable List of Input objects defining the model inputs. ###### MetadataClass metadata Kind: variable Metadata object defining the model metadata. ###### std::vector< Output > outputs Kind: variable List of Output objects defining the model outputs. ###### dai::nn_archive::v1::Output Kind: struct Represents output stream of a model. @type name: str @ivar name: Name of the output layer. @type dtype: DataType @ivar dtype: Data type of the output data (e.g., 'float32'). Represents output stream of a model. @type name: str @ivar name: Name of the output layer. @type dtype: DataType @ivar dtype: Data type of the output data (e.g., 'float32'). ###### DataType dtype Kind: variable Data type of the output data (e.g., 'float32'). ###### std::optional< std::string > layout Kind: variable List of letters describing the output layout (e.g. 'NC'). ###### std::string name Kind: variable Name of the output layer. ###### std::optional< std::vector< int64_t > > shape Kind: variable Shape of the output as a list of integers (e.g. [1, 1000]). ###### dai::nn_archive::v1::PreprocessingBlock Kind: struct Preprocessing steps applied to the input data. Represents preprocessing operations applied to the input data. @type mean: list | None @ivar mean: Mean values in channel order. Order depends on the order in which the model was trained on. @type scale: list | None @ivar scale: Standardization values in channel order. Order depends on the order in which the model was trained on. @type reverse_channels: bool | None @ivar reverse_channels: If True input to the model is RGB else BGR. @type interleaved_to_planar: bool | None @ivar interleaved_to_planar: If True input to the model is interleaved (NHWC) else planar (NCHW). @type dai_type: str | None @ivar dai_type: DepthAI input type which is read by DepthAI to automatically setup the pipeline. Preprocessing steps applied to the input data. Represents preprocessing operations applied to the input data. @type mean: list | None @ivar mean: Mean values in channel order. Order depends on the order in which the model was trained on. @type scale: list | None @ivar scale: Standardization values in channel order. Order depends on the order in which the model was trained on. @type reverse_channels: bool | None @ivar reverse_channels: If True input to the model is RGB else BGR. @type interleaved_to_planar: bool | None @ivar interleaved_to_planar: If True input to the model is interleaved (NHWC) else planar (NCHW). @type dai_type: str | None @ivar dai_type: DepthAI input type which is read by DepthAI to automatically setup the pipeline. ###### std::optional< std::string > daiType Kind: variable DepthAI input type which is read by DepthAI to automatically setup the pipeline. ###### std::optional< bool > interleavedToPlanar Kind: variable If True input to the model is interleaved (NHWC) else planar (NCHW). ###### std::optional< std::vector< double > > mean Kind: variable Mean values in channel order. Order depends on the order in which the model was trained on. ###### std::optional< bool > reverseChannels Kind: variable If True input to the model is RGB else BGR. ###### std::optional< std::vector< double > > scale Kind: variable Standardization values in channel order. Order depends on the order in which the model was trained on. ###### int DataType Kind: enum Data type of the input data (e.g., 'float32'). Represents all existing data types used in i/o streams of the model. Precision of the model weights. Data type of the output data (e.g., 'float32'). Data type of the input data (e.g., 'float32'). Represents all existing data types used in i/o streams of the model. Precision of the model weights. Data type of the output data (e.g., 'float32'). ###### BOOLEAN Kind: enum_value ###### FLOAT16 Kind: enum_value ###### FLOAT32 Kind: enum_value ###### FLOAT64 Kind: enum_value ###### INT16 Kind: enum_value ###### INT32 Kind: enum_value ###### INT4 Kind: enum_value ###### INT64 Kind: enum_value ###### INT8 Kind: enum_value ###### STRING Kind: enum_value ###### UINT16 Kind: enum_value ###### UINT32 Kind: enum_value ###### UINT4 Kind: enum_value ###### UINT64 Kind: enum_value ###### UINT8 Kind: enum_value ###### int InputType Kind: enum Type of input data (e.g., 'image'). Represents a type of input the model is expecting. Type of input data (e.g., 'image'). Represents a type of input the model is expecting. ###### IMAGE Kind: enum_value ###### RAW Kind: enum_value #### dai::node Kind: namespace ##### dai::node::internal Kind: namespace ###### dai::node::internal::XLinkInBridge Kind: struct XLink bridge structure for host-to-device communication Contains pointers to XLinkOutHost and XLinkIn nodes. ###### std::shared_ptr< dai::node::internal::XLinkOutHost > xLinkOutHost Kind: variable ###### std::shared_ptr< dai::node::internal::XLinkIn > xLinkIn Kind: variable ###### dai::node::internal::XLinkOutBridge Kind: struct XLink bridge structure for device-to-host communication Contains pointers to XLinkOut and XLinkInHost nodes. ###### std::shared_ptr< dai::node::internal::XLinkOut > xLinkOut Kind: variable ###### std::shared_ptr< dai::node::internal::XLinkInHost > xLinkInHost Kind: variable ###### dai::node::internal::PipelineEventAggregation Kind: class Sync node. Performs syncing between image frames. ###### InputMap inputs Kind: variable A map of inputs ###### Input request Kind: variable Input PipelineEventAggregationConfig message with state request parameters ###### Output out Kind: variable Output message of type PipelineState ###### Output outTrace Kind: variable Continuous output message of type PipelineState ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### PipelineEventAggregation & setTraceOutput(bool enable) Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ###### dai::node::internal::XLinkIn Kind: class XLinkIn node. Receives messages over XLink. ###### Output out Kind: variable Outputs message of same type as send from host. ###### ~XLinkIn() Kind: function ###### void setStreamName(const std::string & name) Kind: function Specifies XLink stream name to use. The name should not start with double underscores '__', as those are reserved for internal use. parameters: name: Stream name ###### void setMaxDataSize(std::uint32_t maxDataSize) Kind: function Set maximum message size it can receive parameters: maxDataSize: Maximum size in bytes ###### void setNumFrames(std::uint32_t numFrames) Kind: function Set number of frames in pool for sending messages forward parameters: numFrames: Maximum number of frames in pool ###### std::string getStreamName() Kind: function Get stream name. ###### std::uint32_t getMaxDataSize() Kind: function Get maximum messages size in bytes. ###### std::uint32_t getNumFrames() Kind: function Get number of frames in pool. ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ###### dai::node::internal::XLinkInHost Kind: class ###### Output out Kind: variable ###### void setStreamName(const std::string & name) Kind: function ###### void setConnection(std::shared_ptr< XLinkConnection > conn) Kind: function ###### void disconnect() Kind: function ###### void run() Kind: function ###### dai::node::internal::XLinkOut Kind: class XLinkOut node. Sends messages over XLink. ###### Input input Kind: variable Input for any type of messages to be transferred over XLink stream Default queue is blocking with size 8 ###### void setStreamName(const std::string & name) Kind: function Specifies XLink stream name to use. The name should not start with double underscores '__', as those are reserved for internal use. parameters: name: Stream name ###### void setFpsLimit(float fps) Kind: function Specifies a message sending limit. It's approximated from specified rate. parameters: fps: Approximate rate limit in messages per second ###### void setMetadataOnly(bool metadataOnly) Kind: function Specify whether to transfer only messages attributes and not buffer data ###### void setPacketSize(int packetSize) Kind: function ###### void setBytesPerSecondLimit(int bytesPerSecondLimit) Kind: function ###### std::string getStreamName() Kind: function Get stream name. ###### float getFpsLimit() Kind: function Get rate limit in messages per second. ###### bool getMetadataOnly() Kind: function Get whether to transfer only messages attributes and not buffer data. ###### int getPacketSize() Kind: function ###### int getBytesPerSecondLimit() Kind: function ###### void buildInternal() Kind: function Function called from within the ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ###### dai::node::internal::XLinkOutHost Kind: class ###### Input in Kind: variable ###### void setStreamName(const std::string & name) Kind: function ###### void setConnection(std::shared_ptr< XLinkConnection > conn) Kind: function ###### void allowStreamResize(bool allow) Kind: function ###### void disconnect() Kind: function ###### void run() Kind: function ###### :: dai::internal::XLinkInProperties XLinkInProperties Kind: typedef ###### :: dai::internal::XLinkOutProperties XLinkOutProperties Kind: typedef ##### dai::node::test Kind: namespace ###### dai::node::test::MyConsumer Kind: class XLinkOut node. Sends messages over XLink. ###### Input input Kind: variable Input for any type of messages to be transferred over XLink stream Default queue is blocking with size 8 ###### void run() Kind: function ###### dai::node::test::MyProducer Kind: class XLinkOut node. Sends messages over XLink. ###### Output out Kind: variable Outputs message of same type as sent from host. ###### void run() Kind: function ##### dai::node::BasaltVIO Kind: class Basalt Visual Inertial Odometry node. Performs VIO on stereo images and IMU data. ###### dai::node::BasaltVIO::VioConfig Kind: struct ###### std::string optical_flow_type Kind: variable ###### int optical_flow_detection_grid_size Kind: variable ###### int optical_flow_detection_num_points_cell Kind: variable ###### int optical_flow_detection_min_threshold Kind: variable ###### int optical_flow_detection_max_threshold Kind: variable ###### bool optical_flow_detection_nonoverlap Kind: variable ###### float optical_flow_max_recovered_dist2 Kind: variable ###### int optical_flow_pattern Kind: variable ###### int optical_flow_max_iterations Kind: variable ###### int optical_flow_levels Kind: variable ###### float optical_flow_epipolar_error Kind: variable ###### int optical_flow_skip_frames Kind: variable ###### MatchingGuessType optical_flow_matching_guess_type Kind: variable ###### float optical_flow_matching_default_depth Kind: variable ###### float optical_flow_image_safe_radius Kind: variable ###### bool optical_flow_recall_enable Kind: variable ###### bool optical_flow_recall_all_cams Kind: variable ###### bool optical_flow_recall_num_points_cell Kind: variable ###### bool optical_flow_recall_over_tracking Kind: variable ###### bool optical_flow_recall_update_patch_viewpoint Kind: variable ###### float optical_flow_recall_max_patch_dist Kind: variable ###### std::vector< float > optical_flow_recall_max_patch_norms Kind: variable ###### LinearizationType vio_linearization_type Kind: variable ###### bool vio_sqrt_marg Kind: variable ###### int vio_max_states Kind: variable ###### int vio_max_kfs Kind: variable ###### int vio_min_frames_after_kf Kind: variable ###### float vio_new_kf_keypoints_thresh Kind: variable ###### bool vio_debug Kind: variable ###### bool vio_extended_logging Kind: variable ###### int vio_max_iterations Kind: variable ###### double vio_obs_std_dev Kind: variable ###### double vio_obs_huber_thresh Kind: variable ###### double vio_min_triangulation_dist Kind: variable ###### bool vio_enforce_realtime Kind: variable ###### bool vio_use_lm Kind: variable ###### double vio_lm_lambda_initial Kind: variable ###### double vio_lm_lambda_min Kind: variable ###### double vio_lm_lambda_max Kind: variable ###### bool vio_scale_jacobian Kind: variable ###### double vio_init_pose_weight Kind: variable ###### double vio_init_ba_weight Kind: variable ###### double vio_init_bg_weight Kind: variable ###### bool vio_marg_lost_landmarks Kind: variable ###### bool vio_fix_long_term_keyframes Kind: variable ###### double vio_kf_marg_feature_ratio Kind: variable ###### KeyframeMargCriteria vio_kf_marg_criteria Kind: variable ###### double mapper_obs_std_dev Kind: variable ###### double mapper_obs_huber_thresh Kind: variable ###### int mapper_detection_num_points Kind: variable ###### double mapper_num_frames_to_match Kind: variable ###### double mapper_frames_to_match_threshold Kind: variable ###### double mapper_min_matches Kind: variable ###### double mapper_ransac_threshold Kind: variable ###### double mapper_min_track_length Kind: variable ###### double mapper_max_hamming_distance Kind: variable ###### double mapper_second_best_test_ratio Kind: variable ###### int mapper_bow_num_bits Kind: variable ###### double mapper_min_triangulation_dist Kind: variable ###### bool mapper_no_factor_weights Kind: variable ###### bool mapper_use_factors Kind: variable ###### bool mapper_use_lm Kind: variable ###### double mapper_lm_lambda_min Kind: variable ###### double mapper_lm_lambda_max Kind: variable ###### LinearizationType Kind: enum ###### ABS_QR Kind: enum_value ###### ABS_SC Kind: enum_value ###### REL_SC Kind: enum_value ###### MatchingGuessType Kind: enum ###### SAME_PIXEL Kind: enum_value ###### REPROJ_FIX_DEPTH Kind: enum_value ###### REPROJ_AVG_DEPTH Kind: enum_value ###### KeyframeMargCriteria Kind: enum ###### KF_MARG_DEFAULT Kind: enum_value ###### KF_MARG_FORWARD_VECTOR Kind: enum_value ###### Subnode < node::Sync > sync Kind: variable ###### InputMap & inputs Kind: variable ###### std::string leftInputName Kind: variable ###### std::string rightInputName Kind: variable ###### Input & left Kind: variable Input left image on which VIO is performed. ###### Input & right Kind: variable Input right image on which VIO is performed. ###### Input imu Kind: variable Input IMU data. ###### Output transform Kind: variable Output transform data. ###### Output passthrough Kind: variable Output passthrough of left image. ###### BasaltVIO() Kind: function ###### ~BasaltVIO() Kind: function ###### void buildInternal() Kind: function ###### void setImuUpdateRate(int rate) Kind: function ###### void setConfigPath(const std::string & path) Kind: function ###### void setConfig(const VioConfig & config) Kind: function ###### void setUseSpecTranslation(bool use) Kind: function ###### void setLocalTransform(const std::shared_ptr< TransformData > & transform) Kind: function ###### void setImuExtrinsics(const std::shared_ptr< TransformData > & imuExtr) Kind: function ###### void setAccelBias(const std::vector< double > & accelBias) Kind: function ###### void setAccelNoiseStd(const std::vector< double > & accelNoiseStd) Kind: function ###### void setGyroBias(const std::vector< double > & gyroBias) Kind: function ###### void setGyroNoiseStd(const std::vector< double > & gyroNoiseStd) Kind: function ###### void setDefaultVIOConfig() Kind: function ###### void runSyncOnHost(bool runOnHost) Kind: function ##### dai::node::ThreadedHostNode Kind: class ###### ~ThreadedHostNode() Kind: function ###### bool runOnHost() Kind: function Returns true or false whether the node should be run on host or not. ###### ThreadedNode() Kind: function ##### dai::node::AprilTag Kind: class AprilTag node. ###### std::shared_ptr< AprilTagConfig > initialConfig Kind: variable Initial config to use when calculating spatial location data. ###### Input inputConfig Kind: variable Input AprilTagConfig message with ability to modify parameters in runtime. Default queue is non-blocking with size 4. ###### Input inputImage Kind: variable Input message with depth data used to retrieve spatial information about detected object. Default queue is non-blocking with size 4. ###### Output out Kind: variable Outputs AprilTags message that carries spatial location results. ###### Output outConfig Kind: variable Outputs AprilTagConfig message that contains current configuration. ###### Output passthroughInputImage Kind: variable Passthrough message on which the calculation was performed. Suitable for when input queue is set to non-blocking behavior. ###### AprilTag() Kind: function ###### AprilTag(std::unique_ptr< Properties > props) Kind: function ###### void setWaitForConfigInput(bool wait) Kind: function Specify whether or not wait until configuration message arrives to inputConfig Input. parameters: wait: True to wait for configuration message, false otherwise. ###### bool getWaitForConfigInput() Kind: function Get whether or not wait until configuration message arrives to inputConfig Input. ###### void setNumThreads(int numThreads) Kind: function Set number of threads to use for AprilTag detection. parameters: numThreads: Number of threads to use. ###### int getNumThreads() Kind: function Get number of threads to use for AprilTag detection. return: Number of threads to use. ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### void buildInternal() Kind: function Function called from within the ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::AutoCalibration Kind: class ###### dai::DynamicCalibrationControl DCC Kind: enum ###### std::shared_ptr< AutoCalibrationConfig > initialConfig Kind: variable ###### Output output Kind: variable ###### std::shared_ptr< AutoCalibration > build(const std::shared_ptr< Camera > & cameraLeft, const std::shared_ptr< Camera > & cameraRight) Kind: function ###### ~AutoCalibration() Kind: function ###### void run() Kind: function ###### void setRunOnHost(bool runOnHost) Kind: function ###### bool runOnHost() Kind: function Returns true or false whether the node should be run on host or not. ###### void buildInternal() Kind: function Function called from within the ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::BenchmarkIn Kind: class ###### Input input Kind: variable Receive messages as fast as possible ###### Output passthrough Kind: variable Passthrough for input messages (so the node can be placed between other nodes) ###### Output report Kind: variable Send a benchmark report when the set number of messages are received ###### void sendReportEveryNMessages(uint32_t n) Kind: function Specify how many messages to measure for each report ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void logReportsAsWarnings(bool logReportsAsWarnings) Kind: function Log the reports as warnings ###### void measureIndividualLatencies(bool attachLatencies) Kind: function Attach latencies to the report ###### void run() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::BenchmarkOut Kind: class ###### Output out Kind: variable Send messages out as fast as possible ###### Input input Kind: variable Message that will be sent repeatedly ###### void setNumMessagesToSend(int num) Kind: function Sets number of messages to send, by default send messages indefinitely parameters: num: number of messages to send ###### void setFps(float fps) Kind: function Set FPS at which the node is sending out messages. 0 means as fast as possible ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::Camera Kind: class ###### CameraControl initialControl Kind: variable Initial control options to apply to sensor ###### Input inputControl Kind: variable Input for CameraControl message, which can modify camera parameters in runtime ###### Input mockIsp Kind: variable Input for mocking 'isp' functionality on RVC2. Default queue is blocking with size 8 ###### Output raw Kind: variable Outputs ImgFrame message that carries RAW10-packed (MIPI CSI-2 format) frame data. Captured directly from the camera sensor, and the source for the 'isp' output. ###### OutputMap dynamicOutputs Kind: variable ###### Node::Output * requestOutput(std::pair< uint32_t, uint32_t > size, std::optional< ImgFrame::Type > type, ImgResizeMode resizeMode, std::optional< float > fps, std::optional< bool > enableUndistortion) Kind: function Get video output with specified size. ###### Node::Output * requestOutput(const Capability & capability, bool onHost) Kind: function Request output with advanced controls. Mainly to be used by custom node writers. ###### Node::Output * requestFullResolutionOutput(std::optional< ImgFrame::Type > type, std::optional< float > fps, bool useHighestResolution) Kind: function Get a high resolution output with full FOV on the sensor. By default the function will not use the resolutions higher than 5000x4000, as those often need a lot of resources, making them hard to use in combination with other nodes. parameters: type: Type of the output (NV12, BGR, ...) - by default it's auto-selected for best performance; fps: FPS of the output - by default it's auto-selected to highest possible that a sensor config support or 30, whichever is lower; useHighestResolution: If true, the function will use the highest resolution available on the sensor, even if it's higher than 5000x4000 ###### Node::Output * requestIspOutput(std::optional< float > fps) Kind: function Request output with isp resolution. The fps does not vote. ###### std::shared_ptr< Camera > build(dai::CameraBoardSocket boardSocket, std::optional< std::pair< uint32_t, uint32_t >> sensorResolution, std::optional< float > sensorFps) Kind: function Build with a specific board socket parameters: boardSocket: Board socket to use; sensorResolution: Sensor resolution to use - by default it's auto-detected from the requested outputs; sensorFps: Sensor FPS to use - by default it's auto-detected from the requested outputs (maximum is used) ###### std::shared_ptr< Camera > setSensorType(CameraSensorType sensorType) Kind: function Set the sensor type to use parameters: sensorType: Sensor type to use ###### CameraSensorType getSensorType() Kind: function Get the sensor type return: Sensor type ###### std::shared_ptr< Camera > setImageOrientation(CameraImageOrientation imageOrientation) Kind: function Set camera image orientation parameters: imageOrientation: Image orientation to set return: Shared pointer to the camera node ###### CameraImageOrientation getImageOrientation() Kind: function Get camera image orientation return: Image orientation ###### std::shared_ptr< Camera > build(dai::CameraBoardSocket boardSocket, ReplayVideo & replay) Kind: function Build with a specific board socket and mock input ###### std::shared_ptr< Camera > build(ReplayVideo & replay) Kind: function Build with mock input ###### uint32_t getMaxWidth() Kind: function Get max width of the camera (can only be called after build) ###### uint32_t getMaxHeight() Kind: function Get max height of the camera (can only be called after build) ###### CameraBoardSocket getBoardSocket() Kind: function Retrieves which board socket to use return: Board socket to use ###### std::shared_ptr< Camera > setRawNumFramesPool(int num) Kind: function Set number of frames in raw pool (will be automatically reduced if the maximum pool memory size is exceeded) parameters: num: Number of frames return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setMaxSizePoolRaw(int size) Kind: function Set maximum size of raw pool parameters: size: Maximum size in bytes of raw pool return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setIspNumFramesPool(int num) Kind: function Set number of frames in isp pool (will be automatically reduced if the maximum pool memory size is exceeded) parameters: num: Number of frames return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setMaxSizePoolIsp(int size) Kind: function Set maximum size of isp pool parameters: size: Maximum size in bytes of isp pool return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setNumFramesPools(int raw, int isp, int outputs) Kind: function Set number of frames in all pools (will be automatically reduced if the maximum pool memory size is exceeded) parameters: raw: Number of frames in raw pool; isp: Number of frames in isp pool; outputs: Number of frames in outputs pools return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setMaxSizePools(int raw, int isp, int outputs) Kind: function Set maximum memory size of all pools parameters: raw: Maximum size in bytes of raw pool; isp: Maximum size in bytes of isp pool; outputs: Maximum size in bytes of outputs pools return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setOutputsNumFramesPool(int num) Kind: function Set number of frames in pools for all outputs parameters: num: Number of frames in pools for all outputs return: Shared pointer to the camera node ###### std::shared_ptr< Camera > setOutputsMaxSizePool(int size) Kind: function Set maximum size of pools for all outputs parameters: size: Maximum size in bytes of pools for all outputs return: Shared pointer to the camera node ###### int getRawNumFramesPool() Kind: function Get number of frames in raw pool return: Number of frames ###### int getMaxSizePoolRaw() Kind: function Get maximum size of raw pool return: Maximum size in bytes of raw pool ###### int getIspNumFramesPool() Kind: function Get number of frames in isp pool return: Number of frames ###### int getMaxSizePoolIsp() Kind: function Get maximum size of isp pool return: Maximum size in bytes of isp pool ###### std::optional< int > getOutputsNumFramesPool() Kind: function Get number of frames in outputs pool for all outputs return: Number of frames ###### std::optional< size_t > getOutputsMaxSizePool() Kind: function Get maximum size of outputs pool for all outputs return: Maximum size in bytes of image manip pool ###### Camera & setMockIsp(ReplayVideo & replay) Kind: function Set mock ISP for Camera node. Automatically sets mockIsp size. parameters: replay: ReplayVideo node to use as mock ISP ###### Camera() Kind: function ###### Camera(std::shared_ptr< Device > & defaultDevice) Kind: function ###### Camera(std::unique_ptr< Properties > props) Kind: function ###### void buildStage1() Kind: function Build stages;. ###### float getMaxRequestedFps() Kind: function ###### uint32_t getMaxRequestedWidth() Kind: function ###### uint32_t getMaxRequestedHeight() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::ColorCamera Kind: class ColorCamera node. For use with color sensors. ###### CameraControl initialControl Kind: variable Initial control options to apply to sensor ###### Input inputControl Kind: variable Input for CameraControl message, which can modify camera parameters in runtime ###### Input mockIsp Kind: variable Input for mocking 'isp' functionality. Default queue is blocking with size 8 ###### Output video Kind: variable Outputs ImgFrame message that carries NV12 encoded (YUV420, UV plane interleaved) frame data. Suitable for use with VideoEncoder node ###### Output preview Kind: variable Outputs ImgFrame message that carries BGR/RGB planar/interleaved encoded frame data. Suitable for use with NeuralNetwork node ###### Output still Kind: variable Outputs ImgFrame message that carries NV12 encoded (YUV420, UV plane interleaved) frame data. The message is sent only when a CameraControl message arrives to inputControl with captureStill command set. ###### Output isp Kind: variable Outputs ImgFrame message that carries YUV420 planar (I420/IYUV) frame data. Generated by the ISP engine, and the source for the 'video', 'preview' and 'still' outputs ###### Output raw Kind: variable Outputs ImgFrame message that carries RAW10-packed (MIPI CSI-2 format) frame data. Captured directly from the camera sensor, and the source for the 'isp' output. ###### Output frameEvent Kind: variable Outputs metadata-only ImgFrame message as an early indicator of an incoming frame. It's sent on the MIPI SoF (start-of-frame) event, just after the exposure of the current frame has finished and before the exposure for next frame starts. Could be used to synchronize various processes with camera capture. Fields populated: camera id, sequence number, timestamp ###### ColorCamera() Kind: function ###### ColorCamera(std::unique_ptr< Properties > props) Kind: function ###### int getScaledSize(int input, int num, int denom) Kind: function Computes the scaled size given numerator and denominator ###### void setBoardSocket(CameraBoardSocket boardSocket) Kind: function Specify which board socket to use parameters: boardSocket: Board socket to use ###### CameraBoardSocket getBoardSocket() Kind: function Retrieves which board socket to use return: Board socket to use ###### void setCamera(std::string name) Kind: function Specify which camera to use by name parameters: name: Name of the camera to use ###### std::string getCamera() Kind: function Retrieves which camera to use by name return: Name of the camera to use ###### void setCamId(int64_t id) Kind: function Set which color camera to use. ###### int64_t getCamId() Kind: function Get which color camera to use. ###### void setImageOrientation(CameraImageOrientation imageOrientation) Kind: function Set camera image orientation. ###### CameraImageOrientation getImageOrientation() Kind: function Get camera image orientation. ###### void setColorOrder(ColorCameraProperties::ColorOrder colorOrder) Kind: function Set color order of preview output images. RGB or BGR. ###### ColorCameraProperties::ColorOrder getColorOrder() Kind: function Get color order of preview output frames. RGB or BGR. ###### void setInterleaved(bool interleaved) Kind: function Set planar or interleaved data of preview output frames. ###### bool getInterleaved() Kind: function Get planar or interleaved data of preview output frames. ###### void setPreviewType(ImgFrame::Type type) Kind: function Set type of preview output images. ###### ImgFrame::Type getPreviewType() Kind: function Get the preview type. ###### void setFp16(bool fp16) Kind: function Set fp16 (0..255) data type of preview output frames. ###### bool getFp16() Kind: function Get fp16 (0..255) data of preview output frames. ###### void setPreviewSize(int width, int height) Kind: function Set preview output size. ###### void setPreviewSize(std::tuple< int, int > size) Kind: function Set preview output size, as a tuple ###### void setPreviewNumFramesPool(int num) Kind: function Set number of frames in preview pool. ###### void setVideoSize(int width, int height) Kind: function Set video output size. ###### void setVideoSize(std::tuple< int, int > size) Kind: function Set video output size, as a tuple ###### void setVideoNumFramesPool(int num) Kind: function Set number of frames in preview pool. ###### void setStillSize(int width, int height) Kind: function Set still output size. ###### void setStillSize(std::tuple< int, int > size) Kind: function Set still output size, as a tuple ###### void setMockIspSize(int width, int height) Kind: function ###### void setStillNumFramesPool(int num) Kind: function Set number of frames in preview pool. ###### void setResolution(Properties::SensorResolution resolution) Kind: function Set sensor resolution. ###### Properties::SensorResolution getResolution() Kind: function Get sensor resolution. ###### void setRawNumFramesPool(int num) Kind: function Set number of frames in raw pool. ###### void setIspNumFramesPool(int num) Kind: function Set number of frames in isp pool. ###### void setNumFramesPool(int raw, int isp, int preview, int video, int still) Kind: function Set number of frames in all pools. ###### void setIspScale(int numerator, int denominator) Kind: function Set 'isp' output scaling (numerator/denominator), preserving the aspect ratio. The fraction numerator/denominator is simplified first to a irreducible form, then a set of hardware scaler constraints applies: max numerator = 16, max denominator = 63 ###### void setIspScale(std::tuple< int, int > scale) Kind: function Set 'isp' output scaling, as a tuple ###### void setIspScale(int horizNum, int horizDenom, int vertNum, int vertDenom) Kind: function Set 'isp' output scaling, per each direction. If the horizontal scaling factor (horizNum/horizDen) is different than the vertical scaling factor (vertNum/vertDen), a distorted (stretched or squished) image is generated ###### void setIspScale(std::tuple< int, int > horizScale, std::tuple< int, int > vertScale) Kind: function Set 'isp' output scaling, per each direction, as tuples. ###### void setFps(float fps) Kind: function Set rate at which camera should produce frames parameters: fps: Rate in frames per second ###### void setIsp3aFps(int isp3aFps) Kind: function Isp 3A rate (auto focus, auto exposure, auto white balance, camera controls etc.). Default (0) matches the camera FPS, meaning that 3A is running on each frame. Reducing the rate of 3A reduces the CPU usage on CSS, but also increases the convergence rate of 3A. Note that camera controls will be processed at this rate. E.g. if camera is running at 30 fps, and camera control is sent at every frame, but 3A fps is set to 15, the camera control messages will be processed at 15 fps rate, which will lead to queueing. ###### void setFrameEventFilter(const std::vector< dai::FrameEvent > & events) Kind: function ###### std::vector< dai::FrameEvent > getFrameEventFilter() Kind: function ###### float getFps() Kind: function Get rate at which camera should produce frames return: Rate in frames per second ###### std::tuple< int, int > getPreviewSize() Kind: function Get preview size as tuple. ###### int getPreviewWidth() Kind: function Get preview width. ###### int getPreviewHeight() Kind: function Get preview height. ###### std::tuple< int, int > getVideoSize() Kind: function Get video size as tuple. ###### int getVideoWidth() Kind: function Get video width. ###### int getVideoHeight() Kind: function Get video height. ###### std::tuple< int, int > getStillSize() Kind: function Get still size as tuple. ###### int getStillWidth() Kind: function Get still width. ###### int getStillHeight() Kind: function Get still height. ###### std::tuple< int, int > getResolutionSize() Kind: function Get sensor resolution as size. ###### int getResolutionWidth() Kind: function Get sensor resolution width. ###### int getResolutionHeight() Kind: function Get sensor resolution height. ###### std::tuple< int, int > getIspSize() Kind: function Get 'isp' output resolution as size, after scaling. ###### int getIspWidth() Kind: function Get 'isp' output width. ###### int getIspHeight() Kind: function Get 'isp' output height. ###### void sensorCenterCrop() Kind: function Specify sensor center crop. Resolution size / video size ###### void setSensorCrop(float x, float y) Kind: function Specifies the cropping that happens when converting ISP to video output. By default, video will be center cropped from the ISP output. Note that this doesn't actually do on-sensor cropping (and MIPI-stream only that region), but it does postprocessing on the ISP (on RVC). parameters: x: Top left X coordinate; y: Top left Y coordinate ###### std::tuple< float, float > getSensorCrop() Kind: function return: Sensor top left crop coordinates ###### float getSensorCropX() Kind: function Get sensor top left x crop coordinate. ###### float getSensorCropY() Kind: function Get sensor top left y crop coordinate. ###### void setPreviewKeepAspectRatio(bool keep) Kind: function Specifies whether preview output should preserve aspect ratio, after downscaling from video size or not. parameters: keep: If true, a larger crop region will be considered to still be able to create the final image in the specified aspect ratio. Otherwise video size is resized to fit preview size ###### bool getPreviewKeepAspectRatio() Kind: function see: setPreviewKeepAspectRatio return: Preview keep aspect ratio option ###### int getPreviewNumFramesPool() Kind: function Get number of frames in preview pool. ###### int getVideoNumFramesPool() Kind: function Get number of frames in video pool. ###### int getStillNumFramesPool() Kind: function Get number of frames in still pool. ###### int getRawNumFramesPool() Kind: function Get number of frames in raw pool. ###### int getIspNumFramesPool() Kind: function Get number of frames in isp pool. ###### void setRawOutputPacked(bool packed) Kind: function Configures whether the camera ToF . ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::DetectionNetwork Kind: class DetectionNetwork , base for different network specializations. ###### NeuralNetwork::Model Model Kind: enum ###### Subnode < NeuralNetwork > neuralNetwork Kind: variable ###### Subnode < DetectionParser > detectionParser Kind: variable ###### Output & out Kind: variable Outputs ImgDetections message that carries parsed detection results. Overrides NeuralNetwork 'out' with ImgDetections output message type. ###### Output & outNetwork Kind: variable Outputs unparsed inference results. ###### Input & input Kind: variable Input message with data to be inferred upon Default queue is blocking with size 5 ###### Output & passthrough Kind: variable Passthrough message on which the inference was performed. Suitable for when input queue is set to non-blocking behavior. ###### DetectionNetwork(const std::shared_ptr< Device > & device) Kind: function ###### std::shared_ptr< DetectionNetwork > build(Node::Output & input, const NNArchive & nnArchive) Kind: function Build DetectionNetwork node. Connect output to this node's input. Also call setNNArchive() with provided NNArchive . parameters: output: Output to link; nnArchive: Neural network archive return: Shared pointer to DetectionNetwork node ###### std::shared_ptr< DetectionNetwork > build(const std::shared_ptr< Camera > & input, const Model & model, std::optional< float > fps, std::optional< dai::ImgResizeMode > resizeMode) Kind: function Build DetectionNetwork node. Connect Camera output to this node's input and configure the inference model. parameters: input: Camera node; model: Neural network model description, NNArchive or HubAI model id string; fps: Desired frames per second; resizeMode: Resize mode for input frames return: Shared pointer to DetectionNetwork node ###### std::shared_ptr< DetectionNetwork > build(const std::shared_ptr< Camera > & input, const Model & model, const ImgFrameCapability & capability) Kind: function Build DetectionNetwork node. Connect Camera output to this node's input and configure the inference model. parameters: input: Camera node; model: Neural network model description, NNArchive or HubAI model id string; capability: Camera capabilities return: Shared pointer to DetectionNetwork node ###### std::shared_ptr< DetectionNetwork > build(const std::shared_ptr< ReplayVideo > & input, const Model & model, std::optional< float > fps) Kind: function ###### void setNNArchive(const NNArchive & nnArchive) Kind: function Set NNArchive for this Node . If the archive's type is SUPERBLOB, use default number of shaves. parameters: nnArchive: NNArchive to set ###### void setNNArchive(const NNArchive & nnArchive, int numShaves) Kind: function Set NNArchive for this Node , throws if the archive's type is not SUPERBLOB. parameters: nnArchive: NNArchive to set; numShaves: Number of shaves to use ###### void setFromModelZoo(NNModelDescription description, bool useCached) Kind: function Download model from zoo and set it for this Node . parameters: description: Model description to download; useCached: Use cached model if available ###### void setFromModelZoo(NNModelDescription description, int numShaves, bool useCached) Kind: function Download model from zoo and set it for this node. parameters: description: Model description to download; numShaves: Number of shaves to use; useCached: Use cached model if available ###### void setBlobPath(const std::filesystem::path & path) Kind: function Load network blob into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network blob. parameters: path: Path to network blob ###### void setBlob(OpenVINO::Blob blob) Kind: function Load network blob into assets and use once pipeline is started. parameters: blob: Network blob ###### void setBlob(const std::filesystem::path & path) Kind: function Same functionality as the setBlobPath() . Load network blob into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network blob. parameters: path: Path to network blob ###### void setModelPath(const std::filesystem::path & modelPath) Kind: function Load network model into assets. parameters: modelPath: Path to the model file. ###### void setNumPoolFrames(int numFrames) Kind: function Specifies how many frames will be available in the pool parameters: numFrames: How many frames will pool have ###### void setNumInferenceThreads(int numThreads) Kind: function How many threads should the node use to run the network. parameters: numThreads: Number of threads to dedicate to this node ###### void setNumNCEPerInferenceThread(int numNCEPerThread) Kind: function How many Neural Compute Engines should a single thread use for inference parameters: numNCEPerThread: Number of NCE per thread ###### void setNumShavesPerInferenceThread(int numShavesPerThread) Kind: function How many Shaves should a single thread use for inference parameters: numShavesPerThread: Number of shaves per thread ###### void setBackend(std::string backend) Kind: function Specifies backend to use parameters: backend: String specifying backend to use ###### void setBackendProperties(std::map< std::string, std::string > properties) Kind: function Set backend properties parameters: backendProperties: backend properties map ###### int getNumInferenceThreads() Kind: function How many inference threads will be used to run the network return: Number of threads, 0, 1 or 2. Zero means AUTO ###### void setConfidenceThreshold(float thresh) Kind: function Specifies confidence threshold at which to filter the rest of the detections. parameters: thresh: Detection confidence must be greater than specified threshold to be added to the list ###### float getConfidenceThreshold() Kind: function Retrieves threshold at which to filter the rest of the detections. return: Detection confidence ###### std::vector< std::pair< Input &, std::shared_ptr< Capability > > > getRequiredInputs() Kind: function ###### std::optional< std::vector< std::string > > getClasses() Kind: function ###### void buildInternal() Kind: function Function called from within the ##### dai::node::DetectionParser Kind: class DetectionParser node. Parses detection results from Mobilenet-SSD or YOLO neural networks. note: If multiple detection heads are present in the NNArchive , only one type is supported (either YOLO or Mobilenet-SSD) and the last one will be used. ###### Input input Kind: variable Input NN results with detection data to parse Default queue is blocking with size 5 ###### Output out Kind: variable Outputs image frame with detected edges ###### ~DetectionParser() Kind: function ###### std::shared_ptr< DetectionParser > build(Node::Output & nnInput, const NNArchive & nnArchive) Kind: function Build DetectionParser node. Connect output to this node's input. Also call setNNArchive() with provided NNArchive . parameters: nnInput: Output to link; nnArchive: Neural network archive ###### void setNumFramesPool(int numFramesPool) Kind: function Specify number of frames in pool. parameters: numFramesPool: How many frames should the pool have ###### int getNumFramesPool() Kind: function Returns number of frames in pool ###### void setNNArchive(const NNArchive & nnArchive) Kind: function Set NNArchive for this Node . If the archive's type is SUPERBLOB, use default number of shaves. parameters: nnArchive: NNArchive to set ###### void setModelPath(const std::filesystem::path & modelPath) Kind: function Load network xml and bin files into assets. parameters: xmlModelPath: Path to the neural network model file. ###### void setBlobPath(const std::filesystem::path & path) Kind: function Load network blob into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network blob. parameters: path: Path to network blob ###### void setBlob(OpenVINO::Blob blob) Kind: function Retrieves some input tensor information from the blob parameters: blob: OpenVINO blob to retrieve the information from ###### void setBlob(const std::filesystem::path & path) Kind: function Same functionality as the setBlobPath() . Load network blob into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network blob. parameters: path: Path to network blob ###### void setInputImageSize(int width, int height) Kind: function Set input image size This should only be used instead of setBlob, not besides it ###### void setInputImageSize(std::tuple< int, int > size) Kind: function Set preview output size, as a tuple ###### void setNNFamily(DetectionNetworkType type) Kind: function Sets NN Family to parse. Possible values are: DetectionNetworkType::YOLO - 0 DetectionNetworkType::MOBILENET - 1 warning: If NN Family is set manually, user must ensure that it matches the actual model being used. ###### DetectionNetworkType getNNFamily() Kind: function Gets NN Family to parse ###### void setConfidenceThreshold(float thresh) Kind: function Specifies confidence threshold at which to filter the rest of the detections. parameters: thresh: Detection confidence must be greater than specified threshold to be added to the list ###### float getConfidenceThreshold() Kind: function Retrieves threshold at which to filter the rest of the detections. return: Detection confidence ###### void setNumClasses(int numClasses) Kind: function Set number of classes. This will clear any previously set class names. parameters: numClasses: Number of classes ###### void setClasses(const std::vector< std::string > & classes) Kind: function Set class names. This will clear any previously set number of classes. parameters: classes: Vector of class names ###### void setCoordinateSize(int coordinates) Kind: function Sets the number of coordinates per bounding box. parameters: coordinates: Number of coordinates. Default is 4 ###### void setAnchors(std::vector< float > anchors) Kind: function Set anchors for anchor-based yolo models parameters: anchors: Flattened vector of anchors warning: This method is deprecated, use setAnchorsV2 instead. ###### void setAnchorMasks(std::map< std::string, std::vector< int >> anchorMasks) Kind: function Set anchor masks for anchor-based yolo models parameters: anchorMasks: Map of anchor masks ###### void setAnchors(const std::vector< std::vector< std::vector< float >>> & anchors) Kind: function Set anchors for anchor-based yolo models (v2) parameters: anchors: 3D vector of anchors [layer][anchor][dim] ###### void setIouThreshold(float thresh) Kind: function Set IOU threshold for non-maxima suppression parameters: thresh: IOU threshold ###### void setSubtype(const std::string & subtype) Kind: function Set subtype for the parser. parameters: subtype: Subtype string, currently supported subtypes are: yolov6r1, yolov6r2 yolov8n, yolov6, yolov8, yolov10, yolov11, yolov3, yolov3-tiny, yolov5, yolov7, yolo-p, yolov5-u ###### void setDecodeKeypoints(bool decode) Kind: function Enable/disable keypoints decoding. If enabled, number of keypoints must also be set. ###### void setDecodeSegmentation(bool decode) Kind: function Enable/disable segmentation mask decoding. ###### void setNumKeypoints(int numKeypoints) Kind: function Set number of keypoints to decode. Automatically enables keypoints decoding. ###### void setStrides(const std::vector< int > & strides) Kind: function Set strides for yolo models ###### void setKeypointEdges(const std::vector< dai::Edge > & edges) Kind: function Set edges connections between keypoints. parameters: edges: Vector edges connections represented as pairs of keypoint indices. note: This is only applicable if keypoints decoding is enabled. ###### int getNumClasses() Kind: function Get number of classes to decode. ###### std::optional< std::vector< std::string > > getClasses() Kind: function Get class names to decode. ###### int getCoordinateSize() Kind: function Get number of coordinates per bounding box. ###### std::vector< float > getAnchors() Kind: function Get anchors for anchor-based yolo models ###### std::map< std::string, std::vector< int > > getAnchorMasks() Kind: function Get anchor masks for anchor-based yolo models ###### float getIouThreshold() Kind: function Get IOU threshold for non-maxima suppression ###### std::string getSubtype() Kind: function Get subtype for the parser. ###### bool getDecodeKeypoints() Kind: function Get whether keypoints decoding is enabled. ###### bool getDecodeSegmentation() Kind: function Get whether segmentation mask decoding is enabled. ###### int getNKeypoints() Kind: function Get number of keypoints to decode. ###### std::vector< int > getStrides() Kind: function Get strides for yolo models ###### const NNArchiveVersionedConfig & getNNArchiveVersionedConfig() Kind: function Get NNArchive set for this node ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### void decodeMobilenet(dai::NNData & nnData, dai::ImgDetections & outDetections, float confidenceThr) Kind: function Decode Mobilenet-SSD detections from NNData . ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::DynamicCalibration Kind: class ###### Input inputControl Kind: variable Input DynamicCalibrationControl message with ability to modify parameters in runtime. ###### Output calibrationOutput Kind: variable Output calibration quality result ###### Output qualityOutput Kind: variable ###### Output metricsOutput Kind: variable ###### Output coverageOutput Kind: variable ###### Input syncInput Kind: variable ###### Subnode < node::Sync > sync Kind: variable ###### InputMap & inputs Kind: variable ###### std::string leftInputName Kind: variable ###### std::string rightInputName Kind: variable ###### Input & left Kind: variable Input left image ###### Input & right Kind: variable Input right image ###### ~DynamicCalibration() Kind: function ###### void buildInternal() Kind: function Function called from within the ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on host on RVC2 and on device on RVC4. ###### bool runOnHost() Kind: function Returns true or false whether the node should be run on host or not. ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::EdgeDetector Kind: class EdgeDetector node. Performs edge detection using 3x3 Sobel filter. ###### std::shared_ptr< EdgeDetectorConfig > initialConfig Kind: variable Initial config to use for edge detection. ###### Input inputConfig Kind: variable Input EdgeDetectorConfig message with ability to modify parameters in runtime. Default queue is non-blocking with size 4. ###### Input inputImage Kind: variable Input image on which edge detection is performed. Default queue is non-blocking with size 4. ###### Output outputImage Kind: variable Outputs image frame with detected edges ###### Output passthroughInputImage Kind: variable Passthrough message on which the calculation was performed. ###### EdgeDetector() Kind: function ###### EdgeDetector(std::unique_ptr< Properties > props) Kind: function ###### void setNumFramesPool(int numFramesPool) Kind: function Specify number of frames in pool. parameters: numFramesPool: How many frames should the pool have ###### void setMaxOutputFrameSize(int maxFrameSize) Kind: function Specify maximum size of output image. parameters: maxFrameSize: Maximum frame size in bytes ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::FeatureTracker Kind: class FeatureTracker node. Performs feature tracking and reidentification using motion estimation between 2 consecutive frames. ###### std::shared_ptr< FeatureTrackerConfig > initialConfig Kind: variable Initial config to use for feature tracking. ###### Input inputConfig Kind: variable Input FeatureTrackerConfig message with ability to modify parameters in runtime. Default queue is non-blocking with size 4. ###### Input inputImage Kind: variable Input message with frame data on which feature tracking is performed. Default queue is non-blocking with size 4. ###### Output outputFeatures Kind: variable Outputs TrackedFeatures message that carries tracked features results. ###### Output passthroughInputImage Kind: variable Passthrough message on which the calculation was performed. Suitable for when input queue is set to non-blocking behavior. ###### FeatureTracker() Kind: function ###### FeatureTracker(std::unique_ptr< Properties > props) Kind: function ###### void setHardwareResources(int numShaves, int numMemorySlices) Kind: function Specify allocated hardware resources for feature tracking. 2 shaves/memory slices are required for optical flow, 1 for corner detection only. parameters: numShaves: Number of shaves. Maximum 2.; numMemorySlices: Number of memory slices. Maximum 2. ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::Gate Kind: class Gate Node . This node acts as a valve for data pipelines. It controls the flow of messages from the 'input' to the 'output' based on the state configured via 'inputControl'. It can be configured to stay open indefinitely, stay closed, or open for a specific number of messages. ###### std::shared_ptr< GateControl > initialConfig Kind: variable ###### Input input Kind: variable Main data input. Accepts arbitrary Buffer messages (e.g., ImgFrame , NNData ). If the Gate is Open, messages received here are forwarded to 'output'. If the Gate is Closed, messages received here are discarded/dropped.; Default queue size: 1 Blocking: False ###### Output output Kind: variable Main data output. Forwards messages that were allowed through the Gate . The data type matches the input message. ###### Input inputControl Kind: variable Control input. Accepts ' GateControl ' messages to dynamically change the Gate 's state. Use this to Open/Close the gate or set it to pass a specific number of frames at runtime.; Default queue size: 4 ###### Gate(std::unique_ptr< Properties > props) Kind: function ###### Gate() Kind: function ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is configured to run on the host. return: true if running on host, false otherwise. ###### void run() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::IMU Kind: class IMU node for BNO08X. ###### Output out Kind: variable Outputs IMUData message that carries IMU packets. ###### Input mockIn Kind: variable Mock IMU data for replaying recorded data ###### void enableIMUSensor(IMUSensorConfig sensorConfig) Kind: function Enable a new IMU sensor with explicit configuration ###### void enableIMUSensor(const std::vector< IMUSensorConfig > & sensorConfigs) Kind: function Enable a list of IMU sensors with explicit configuration ###### void enableIMUSensor(IMUSensor sensor, uint32_t reportRate) Kind: function Enable a new IMU sensor with default configuration ###### void enableIMUSensor(const std::vector< IMUSensor > & sensors, uint32_t reportRate) Kind: function Enable a list of IMU sensors with default configuration ###### void setBatchReportThreshold(std::int32_t batchReportThreshold) Kind: function Above this packet threshold data will be sent to host, if queue is not blocked ###### std::int32_t getBatchReportThreshold() Kind: function Above this packet threshold data will be sent to host, if queue is not blocked ###### void setMaxBatchReports(std::int32_t maxBatchReports) Kind: function Maximum number of IMU packets in a batch report ###### std::int32_t getMaxBatchReports() Kind: function Maximum number of IMU packets in a batch report ###### void enableFirmwareUpdate(bool enable) Kind: function Whether to perform firmware update or not. Default value: false. ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::ImageAlign Kind: class ImageAlign node. Calculates spatial location data on a set of ROIs on depth map. ###### std::shared_ptr< ImageAlignConfig > initialConfig Kind: variable Initial config to use when calculating spatial location data. ###### Input inputConfig Kind: variable Input message with ability to modify parameters in runtime. Default queue is non-blocking with size 4. ###### Input input Kind: variable Input message. Default queue is non-blocking with size 4. ###### Input inputAlignTo Kind: variable Input align to message. Default queue is non-blocking with size 1. ###### Output outputAligned Kind: variable Outputs ImgFrame message that is aligned to inputAlignTo. ###### Output passthroughInput Kind: variable Passthrough message on which the calculation was performed. Suitable for when input queue is set to non-blocking behavior. ###### ImageAlign & setOutputSize(int alignWidth, int alignHeight) Kind: function Specify the output size of the aligned image ###### ImageAlign & setOutKeepAspectRatio(bool keep) Kind: function Specify whether to keep aspect ratio when resizing ###### ImageAlign & setInterpolation(Interpolation interp) Kind: function Specify interpolation method to use when resizing ###### ImageAlign & setNumShaves(int numShaves) Kind: function Specify number of shaves to use for this node ###### ImageAlign & setNumFramesPool(int numFramesPool) Kind: function Specify number of frames in the pool ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::ImageFilters Kind: class ###### std::shared_ptr< ImageFiltersConfig > initialConfig Kind: variable Initial config for image filters. ###### Node::Input input Kind: variable Input for image frames to be filtered ###### Node::Output output Kind: variable Filtered frame ###### Node::Input inputConfig Kind: variable Config to be set for a specific filter ###### std::shared_ptr< ImageFilters > build(Node::Output & input, ImageFiltersPresetMode presetMode) Kind: function Build the node. parameters: input: Input for image frames to be filtered; presetMode: Preset mode for image filters return: Shared pointer to the node ###### std::shared_ptr< ImageFilters > build(ImageFiltersPresetMode presetMode) Kind: function Build the node. parameters: presetMode: Preset mode for image filters return: Shared pointer to the node ###### void run() Kind: function ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void setDefaultProfilePreset(ImageFiltersPresetMode mode) Kind: function Set default profile preset for ImageFilters . parameters: mode: Preset mode for ImageFilters . ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::ToFDepthConfidenceFilter Kind: class Node for depth confidence filter, designed to be used with the ###### std::shared_ptr< ToFDepthConfidenceFilterConfig > initialConfig Kind: variable Initial config for ToF depth confidence filter. ###### Node::Input depth Kind: variable Depth frame image, expected ImgFrame type is RAW8 or RAW16. ###### Node::Input amplitude Kind: variable Amplitude frame image, expected ImgFrame type is RAW8 or RAW16. ###### Node::Output filteredDepth Kind: variable RAW16 encoded filtered depth frame ###### Node::Output confidence Kind: variable RAW16 encoded confidence frame ###### Node::Input inputConfig Kind: variable Config message for runtime filter configuration ###### std::shared_ptr< ToFDepthConfidenceFilter > build(Node::Output & depth, Node::Output & amplitude, ImageFiltersPresetMode presetMode) Kind: function Build the node. parameters: depth: Depth frame image, expected ImgFrame type is RAW8 or RAW16.; amplitude: Amplitude frame image, expected ImgFrame type is RAW8 or RAW16.; presetMode: Preset mode for ToF depth confidence filter return: Shared pointer to the node ###### std::shared_ptr< ToFDepthConfidenceFilter > build(ImageFiltersPresetMode presetMode) Kind: function Build the node. parameters: presetMode: Preset mode for ToF depth confidence filter return: Shared pointer to the node ###### void run() Kind: function ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::ImageManip Kind: class ImageManip node. Capability to crop, resize, warp, ... incoming image frames. ###### ImageManipProperties::Backend Backend Kind: enum ###### ImageManipProperties::PerformanceMode PerformanceMode Kind: enum ###### std::shared_ptr< ImageManipConfig > initialConfig Kind: variable Initial config to use when manipulating frames ###### Input inputConfig Kind: variable Input ImageManipConfig message with ability to modify parameters in runtime ###### Input inputImage Kind: variable Input image to be modified ###### Output out Kind: variable Outputs ImgFrame message that carries modified image. ###### ImageManip() Kind: function ###### ImageManip(std::unique_ptr< Properties > props) Kind: function ###### std::shared_ptr< ImageManip > build() Kind: function ###### void setNumFramesPool(int numFramesPool) Kind: function Specify number of frames in pool. parameters: numFramesPool: How many frames should the pool have ###### void setMaxOutputFrameSize(int maxFrameSize) Kind: function Specify maximum size of output image. parameters: maxFrameSize: Maximum frame size in bytes ###### ImageManip & setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device parameters: runOnHost: Run node on host ###### ImageManip & setBackend(Backend backend) Kind: function Set CPU as backend preference parameters: backend: Backend preference ###### ImageManip & setPerformanceMode(PerformanceMode performanceMode) Kind: function Set performance mode parameters: performanceMode: Performance mode ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::MessageDemux Kind: class ###### Input input Kind: variable Input message of type MessageGroup ###### OutputMap outputs Kind: variable A map of outputs, where keys are same as in the input MessageGroup ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### void setProcessor(ProcessorType type) Kind: function Specify on which processor the node should run. RVC2 only. parameters: type: Processor type - Leon CSS or Leon MSS ###### ProcessorType getProcessor() Kind: function Get on which processor the node should run return: Processor type - Leon CSS or Leon MSS ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::MonoCamera Kind: class MonoCamera node. For use with grayscale sensors. ###### CameraControl initialControl Kind: variable Initial control options to apply to sensor ###### Input inputControl Kind: variable Input for CameraControl message, which can modify camera parameters in runtime Default queue is blocking with size 8 ###### Input mockIsp Kind: variable Input for mocking 'isp' functionality. Default queue is blocking with size 8 ###### Output out Kind: variable Outputs ImgFrame message that carries RAW8 encoded (grayscale) frame data. Suitable for use StereoDepth node. Processed by ISP ###### Output raw Kind: variable Outputs ImgFrame message that carries RAW10-packed (MIPI CSI-2 format) frame data. Captured directly from the camera sensor ###### Output frameEvent Kind: variable Outputs metadata-only ImgFrame message as an early indicator of an incoming frame. It's sent on the MIPI SoF (start-of-frame) event, just after the exposure of the current frame has finished and before the exposure for next frame starts. Could be used to synchronize various processes with camera capture. Fields populated: camera id, sequence number, timestamp ###### MonoCamera() Kind: function ###### MonoCamera(std::unique_ptr< Properties > props) Kind: function ###### void setBoardSocket(CameraBoardSocket boardSocket) Kind: function Specify which board socket to use parameters: boardSocket: Board socket to use ###### CameraBoardSocket getBoardSocket() Kind: function Retrieves which board socket to use return: Board socket to use ###### void setCamera(std::string name) Kind: function Specify which camera to use by name parameters: name: Name of the camera to use ###### std::string getCamera() Kind: function Retrieves which camera to use by name return: Name of the camera to use ###### void setCamId(int64_t id) Kind: function ###### int64_t getCamId() Kind: function ###### void setImageOrientation(CameraImageOrientation imageOrientation) Kind: function Set camera image orientation. ###### CameraImageOrientation getImageOrientation() Kind: function Get camera image orientation. ###### void setMockIspSize(int width, int height) Kind: function ###### void setResolution(Properties::SensorResolution resolution) Kind: function Set sensor resolution. ###### Properties::SensorResolution getResolution() Kind: function Get sensor resolution. ###### void setFrameEventFilter(const std::vector< dai::FrameEvent > & events) Kind: function ###### std::vector< dai::FrameEvent > getFrameEventFilter() Kind: function ###### void setFps(float fps) Kind: function Set rate at which camera should produce frames parameters: fps: Rate in frames per second ###### void setIsp3aFps(int isp3aFps) Kind: function Isp 3A rate (auto focus, auto exposure, auto white balance, camera controls etc.). Default (0) matches the camera FPS, meaning that 3A is running on each frame. Reducing the rate of 3A reduces the CPU usage on CSS, but also increases the convergence rate of 3A. Note that camera controls will be processed at this rate. E.g. if camera is running at 30 fps, and camera control is sent at every frame, but 3A fps is set to 15, the camera control messages will be processed at 15 fps rate, which will lead to queueing. ###### float getFps() Kind: function Get rate at which camera should produce frames return: Rate in frames per second ###### std::tuple< int, int > getResolutionSize() Kind: function Get sensor resolution as size. ###### int getResolutionWidth() Kind: function Get sensor resolution width. ###### int getResolutionHeight() Kind: function Get sensor resolution height. ###### void setNumFramesPool(int num) Kind: function Set number of frames in main (ISP output) pool. ###### void setRawNumFramesPool(int num) Kind: function Set number of frames in raw pool. ###### int getNumFramesPool() Kind: function Get number of frames in main (ISP output) pool. ###### int getRawNumFramesPool() Kind: function Get number of frames in raw pool. ###### void setRawOutputPacked(bool packed) Kind: function Configures whether the camera ToF . ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::NeuralAssistedStereo Kind: class NeuralAssistedStereo node. Combines Neural Depth with VPP and traditional Stereo Depth. This composite node internally creates and connects: Rectification node (full resolution); NeuralDepth node (low resolution depth estimation); VPP node (applies virtual projection pattern); StereoDepth node (final depth computation on VPP-enhanced images) Pipeline structure: Left/Right Cameras → Rectification → [Full res to VPP] ↓ NeuralDepth (low res) → [disparity + confidence to VPP] ↓ VPP (combines neural depth with full res images) ↓ StereoDepth → Final Depth Output ###### Node::Input Input Kind: enum ###### Node::Output Output Kind: enum ###### Subnode < node::Rectification > rectification Kind: variable ###### Subnode < node::NeuralDepth > neuralDepth Kind: variable ###### Subnode < node::Vpp > vpp Kind: variable ###### Subnode < node::StereoDepth > stereoDepth Kind: variable ###### Input & left Kind: variable ###### Input & right Kind: variable ###### Output & rectifiedLeft Kind: variable ###### Output & rectifiedRight Kind: variable ###### Output & vppLeft Kind: variable ###### Output & vppRight Kind: variable ###### Output & neuralDisparity Kind: variable ###### Output & neuralConfidence Kind: variable ###### Input & inputVppConfig Kind: variable ###### Input & inputStereoConfig Kind: variable ###### Input & inputNeuralConfig Kind: variable ###### Output & depth Kind: variable ###### Output & disparity Kind: variable ###### ~NeuralAssistedStereo() Kind: function ###### NeuralAssistedStereo(const std::shared_ptr< Device > & device) Kind: function ###### std::shared_ptr< NeuralAssistedStereo > build(Output & leftInput, Output & rightInput, DeviceModelZoo neuralModel, bool rectifyImages) Kind: function ##### dai::node::NeuralDepth Kind: class NeuralDepth node. Compute depth from left-right image pair using neural network. ###### std::shared_ptr< NeuralDepthConfig > initialConfig Kind: variable Initial config to use for NeuralDepth . ###### Subnode < Sync > sync Kind: variable ###### Subnode < MessageDemux > messageDemux Kind: variable ###### Subnode < Rectification > rectification Kind: variable ###### Subnode < NeuralNetwork > neuralNetwork Kind: variable ###### Input & left Kind: variable Input for left ImgFrame of left-right pair ###### Input & right Kind: variable Input for right ImgFrame of left-right pair ###### Output & rectifiedLeft Kind: variable Output for rectified left ImgFrame ###### Output & rectifiedRight Kind: variable Output for rectified right ImgFrame ###### Input inputConfig Kind: variable Input config to modify parameters in runtime. ###### Input nnDataInput Kind: variable Input NNData to parse ###### Input leftInternal Kind: variable Input left frame internal, used to extract frame info ###### Input rightInternal Kind: variable Input right frame internal, used to extract frame info ###### Output disparity Kind: variable Output disparity ImgFrame ###### Output depth Kind: variable Output depth ImgFrame ###### Output edge Kind: variable Output edge ImgFrame ###### Output confidence Kind: variable Output confidence ImgFrame ###### NeuralDepth() Kind: function ###### NeuralDepth & setRectification(bool enable) Kind: function Enable or disable rectification (useful for prerectified inputs) ###### std::shared_ptr< NeuralDepth > build(Output & left, Output & right, DeviceModelZoo model) Kind: function ###### void buildInternal() Kind: function Function called from within the ##### dai::node::NeuralNetwork Kind: class NeuralNetwork node. Runs a neural inference on input data. ###### std::variant< NNModelDescription , NNArchive , std::string > Model Kind: enum ###### Input input Kind: variable Input message with data to be inferred upon ###### Output out Kind: variable Outputs NNData message that carries inference results ###### Output passthrough Kind: variable Passthrough message on which the inference was performed. Suitable for when input queue is set to non-blocking behavior. ###### InputMap inputs Kind: variable Inputs mapped to network inputs. Useful for inferring from separate data sources Default input is non-blocking with queue size 1 and waits for messages ###### OutputMap passthroughs Kind: variable Passthroughs which correspond to specified input ###### ~NeuralNetwork() Kind: function ###### std::shared_ptr< NeuralNetwork > build(Node::Output & input, const NNArchive & nnArchive) Kind: function Build NeuralNetwork node. Connect output to this node's input and sets up the NNArchive . parameters: output: Output to link; nnArchive: Neural network archive return: Shared pointer to NeuralNetwork node ###### std::shared_ptr< NeuralNetwork > build(const std::shared_ptr< Camera > & input, const Model & model, std::optional< float > fps, std::optional< dai::ImgResizeMode > resizeMode) Kind: function Build NeuralNetwork node. Connect Camera output to this node's input and configure the inference model. parameters: input: Camera node; model: Neural network model description, NNArchive or HubAI model id string; fps: Desired frames per second; resizeMode: Resize mode for input frames return: Shared pointer to NeuralNetwork node ###### std::shared_ptr< NeuralNetwork > build(const std::shared_ptr< Camera > & input, const Model & model, const ImgFrameCapability & capability) Kind: function Build NeuralNetwork node. Connect Camera output to this node's input and configure the inference model. parameters: input: Camera node; model: Neural network model description, NNArchive or HubAI model id string; capability: Camera capabilities return: Shared pointer to NeuralNetwork node ###### std::shared_ptr< NeuralNetwork > build(const std::shared_ptr< ReplayVideo > & input, const Model & model, std::optional< float > fps) Kind: function Build NeuralNetwork node. Connect ReplayVideo output to this node's input and configure the inference model. parameters: input: ReplayVideo node; model: Neural network model description, NNArchive or HubAI model id string; fps: Desired frames per second return: Shared pointer to NeuralNetwork node ###### std::optional< std::reference_wrapper< const NNArchive > > getNNArchive() Kind: function Get the archive owned by this Node . return: constant reference to this Nodes archive ###### void setNNArchive(const NNArchive & nnArchive) Kind: function Set NNArchive for this Node . If the archive's type is SUPERBLOB, use default number of shaves. parameters: nnArchive: NNArchive to set ###### void setNNArchive(const NNArchive & nnArchive, int numShaves) Kind: function Set NNArchive for this Node , throws if the archive's type is not SUPERBLOB. parameters: nnArchive: NNArchive to set; numShaves: Number of shaves to use ###### void setFromModelZoo(NNModelDescription description, bool useCached) Kind: function Download model from zoo and set it for this Node . parameters: description: Model description to download; useCached: Use cached model if available ###### void setBlobPath(const std::filesystem::path & path) Kind: function Load network blob into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network blob. parameters: path: Path to network blob ###### void setBlob(OpenVINO::Blob blob) Kind: function Load network blob into assets and use once pipeline is started. parameters: blob: Network blob ###### void setBlob(const std::filesystem::path & path) Kind: function Same functionality as the setBlobPath() . Load network blob into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network blob. parameters: path: Path to network blob ###### void setOtherModelFormat(std::vector< uint8_t > model) Kind: function Load network model into assets and use once pipeline is started. parameters: model: Network model ###### void setOtherModelFormat(const std::filesystem::path & path) Kind: function Load network model into assets and use once pipeline is started. parameters: Error: if file doesn't exist or isn't a valid network model. parameters: path: Path to the network model ###### void setModelPath(const std::filesystem::path & modelPath) Kind: function Load network xml and bin files into assets. parameters: xmlModelPath: Path to the neural network model file. ###### void setNumPoolFrames(int numFrames) Kind: function Specifies how many frames will be available in the pool parameters: numFrames: How many frames will pool have ###### void setNumInferenceThreads(int numThreads) Kind: function How many threads should the node use to run the network. parameters: numThreads: Number of threads to dedicate to this node ###### void setNumNCEPerInferenceThread(int numNCEPerThread) Kind: function How many Neural Compute Engines should a single thread use for inference parameters: numNCEPerThread: Number of NCE per thread ###### void setNumShavesPerInferenceThread(int numShavesPerThread) Kind: function How many Shaves should a single thread use for inference parameters: numShavesPerThread: Number of shaves per thread ###### void setBackend(std::string backend) Kind: function Specifies backend to use parameters: backend: String specifying backend to use ###### void setBackendProperties(std::map< std::string, std::string > properties) Kind: function Set backend properties parameters: backendProperties: backend properties map ###### int getNumInferenceThreads() Kind: function How many inference threads will be used to run the network return: Number of threads, 0, 1 or 2. Zero means AUTO ###### void setModelFromDeviceZoo(DeviceModelZoo model) Kind: function Set model from Device Model Zoo parameters: model: DeviceModelZoo model enum note: Only applicable for RVC4 devices with OS 1.20.5 or higher ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::ObjectTracker Kind: class ObjectTracker node. Performs object tracking using Kalman filter and hungarian algorithm. ###### Input inputTrackerFrame Kind: variable Input ImgFrame message on which tracking will be performed. RGBp, BGRp, NV12, YUV420p types are supported. Default queue is non-blocking with size 4. ###### Input inputDetectionFrame Kind: variable Input ImgFrame message on which object detection was performed. Default queue is non-blocking with size 4. ###### Input inputDetections Kind: variable Input message with image detection from neural network. Default queue is non-blocking with size 4. ###### Input inputConfig Kind: variable Input ObjectTrackerConfig message with ability to modify parameters at runtime. Default queue is non-blocking with size 4. ###### Output out Kind: variable Outputs Tracklets message that carries object tracking results. ###### Output passthroughTrackerFrame Kind: variable Passthrough ImgFrame message on which tracking was performed. Suitable for when input queue is set to non-blocking behavior. ###### Output passthroughDetectionFrame Kind: variable Passthrough ImgFrame message on which object detection was performed. Suitable for when input queue is set to non-blocking behavior. ###### Output passthroughDetections Kind: variable Passthrough image detections message from neural network output. Suitable for when input queue is set to non-blocking behavior. ###### void setTrackerThreshold(float threshold) Kind: function Specify tracker threshold. parameters: threshold: Above this threshold the detected objects will be tracked. Default 0, all image detections are tracked. ###### void setMaxObjectsToTrack(std::int32_t maxObjectsToTrack) Kind: function Specify maximum number of object to track. parameters: maxObjectsToTrack: Maximum number of object to track. Maximum 60 in case of SHORT_TERM_KCF, otherwise 1000. ###### void setDetectionLabelsToTrack(std::vector< std::uint32_t > labels) Kind: function Specify detection labels to track. parameters: labels: Detection labels to track. Default every label is tracked from image detection network output. ###### void setTrackerType(TrackerType type) Kind: function Specify tracker type algorithm. parameters: type: Tracker type. ###### void setTrackerIdAssignmentPolicy(TrackerIdAssignmentPolicy type) Kind: function Specify tracker ID assignment policy. parameters: type: Tracker ID assignment policy. ###### void setTrackingPerClass(bool trackingPerClass) Kind: function Whether tracker should take into consideration class label for tracking. ###### void setOcclusionRatioThreshold(float theshold) Kind: function Set the occlusion ratio threshold. Used to filter out overlapping tracklets. parameters: theshold: Occlusion ratio threshold. Default 0.3. ###### void setTrackletMaxLifespan(uint32_t trackletMaxLifespan) Kind: function Set the tracklet lifespan in number of frames. Number of frames after which a LOST tracklet is removed. parameters: trackletMaxLifespan: Tracklet lifespan in number of frames. Default 120. ###### void setTrackletBirthThreshold(uint32_t trackletBirthThreshold) Kind: function Set the tracklet birth threshold. Minimum consecutive tracked frames required to consider a tracklet as a new (TRACKED) instance. parameters: trackletBirthThreshold: Tracklet birth threshold. Default 3. ###### void setSpatialAssociation(bool enabled) Kind: function Enable or disable spatially-aware association. If disabled, only 2D association is used. parameters: enabled: ###### void setSpatialAssociationWeight(float weight) Kind: function Set spatial association weight in [0,1]. parameters: weight: Spatial association weight in [0,1] used to blend 2D and spatial association scores (0 = 2D-only scoring, 1 = spatial-only scoring). This weight affects candidate scoring only; final acceptance still requires passing the 2D IoU threshold gate. Default is 0.5. ###### void setSpatialDistanceThreshold(float thresholdMeters) Kind: function Set base 3D gating threshold in meters for spatial association. parameters: thresholdMeters: Base spatial gating distance in meters. Default is 1.5m. ###### void setSpatialDepthAwareScale(float scale) Kind: function Set depth-aware gating scale used for spatial association. Increases gating threshold with increased depth. parameters: scale: Depth-aware gating scale factor. Default is 0.35 ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::PointCloud Kind: class PointCloud node. Computes point cloud from depth frames. ###### dai::node::PointCloud::Impl Kind: class ###### LengthUnit targetLengthUnit Kind: variable ###### Impl() Kind: function ###### void setLogger(std::shared_ptr<::spdlog::logger > log) Kind: function ###### void computePointCloudDense(const uint8_t * depthData, std::vector< Point3f > & points) Kind: function ###### void computePointCloudDenseColored(const uint8_t * depthData, const uint8_t * colorData, std::vector< Point3fRGBA > & points) Kind: function ###### void applyTransformation(std::vector< PointT > & points) Kind: function ###### std::vector< PointT > filterValidPoints(const std::vector< PointT > & densePoints) Kind: function ###### void setLengthUnit(dai::LengthUnit lengthUnit) Kind: function ###### void useCPU() Kind: function ###### void useCPUMT(uint32_t numThreads) Kind: function ###### void useGPU(uint32_t device) Kind: function ###### void setIntrinsics(float fx, float fy, float cx, float cy, unsigned int width, unsigned int height) Kind: function ###### void setExtrinsics(const std::vector< std::vector< float >> & transformMatrix) Kind: function ###### void clearExtrinsics() Kind: function ###### std::shared_ptr< PointCloudConfig > initialConfig Kind: variable Initial config to use when computing the point cloud. ###### Input inputConfig Kind: variable Input PointCloudConfig message with ability to modify parameters in runtime. Default queue is non-blocking with size 4. ###### Subnode < node::Sync > sync Kind: variable Sync subnode for synchronized depth + color input. When only depth is connected, Sync passes through single-item MessageGroups. When both depth and color are connected, Sync pairs them by timestamp. ###### InputMap & syncInputs Kind: variable ###### Input & inputDepth Kind: variable Input message with depth data used to create the point cloud. Routed through the internal Sync subnode. ###### Output outputPointCloud Kind: variable Outputs PointCloudData message ###### Output passthroughDepth Kind: variable Passthrough depth from which the point cloud was calculated. Suitable for when input queue is set to non-blocking behavior. ###### PointCloud() Kind: function ###### ~PointCloud() Kind: function ###### Input & getColorInput() Kind: function Get the optional color input for colorized point clouds. Lazily creates the Sync entry so that depth-only mode works without Sync waiting for a color frame that never arrives. Link an aligned color image (RGB888i, same dimensions as depth) to this input to enable colored point cloud output. ###### void setNumFramesPool(int numFramesPool) Kind: function Specify number of frames in pool. parameters: numFramesPool: How many frames should the pool have ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on host. ###### void useCPU() Kind: function Use single-threaded CPU for processing ###### void useCPUMT(uint32_t numThreads) Kind: function Use multi-threaded CPU for processing ###### void useGPU(uint32_t device) Kind: function Use GPU for point cloud computation parameters: device: GPU device index (default 0) ###### void setTargetCoordinateSystem(CameraBoardSocket targetCamera, bool useSpecTranslation) Kind: function Set target coordinate system to transform point cloud parameters: targetCamera: Target camera socket; useSpecTranslation: Use spec translation instead of calibration (default: false) ###### void setTargetCoordinateSystem(HousingCoordinateSystem housingCS, bool useSpecTranslation) Kind: function Set target coordinate system to housing coordinate system Point cloud will be transformed to this housing coordinate system parameters: housingCS: Target housing coordinate system; useSpecTranslation: Whether to use spec translation (default: true) ###### bool runOnHost() Kind: function Returns true or false whether the node should be run on host or not. ###### void buildInternal() Kind: function Function called from within the ##### dai::node::Rectification Kind: class ###### Input input1 Kind: variable Input images to be rectified ###### Input input2 Kind: variable ###### Output passthrough1 Kind: variable Passthrough for input messages (so the node can be placed between other nodes) ###### Output passthrough2 Kind: variable ###### Output output1 Kind: variable Send outputs ###### Output output2 Kind: variable ###### void setRunOnHost(bool runOnHost) Kind: function Specify whether to run on host or device By default, the node will run on device. ###### Rectification & setOutputSize(uint32_t width, uint32_t height) Kind: function Set output size ###### Rectification & setOutputSize(std::pair< uint32_t, uint32_t > size) Kind: function Set output size ###### Rectification & enableRectification(bool enable) Kind: function Enable or disable rectification (useful for minimal changes during debugging) ###### bool runOnHost() Kind: function Check if the node is set to run on host ###### void run() Kind: function ###### CalibrationHandler getCalibrationData() Kind: function ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::SPIIn Kind: class SPIIn node. Receives messages over SPI. ###### Output out Kind: variable Outputs message of same type as send from host. ###### void setStreamName(const std::string & name) Kind: function Specifies stream name over which the node will receive data parameters: name: Stream name ###### void setBusId(int id) Kind: function Specifies SPI Bus number to use parameters: id: SPI Bus id ###### void setMaxDataSize(std::uint32_t maxDataSize) Kind: function Set maximum message size it can receive parameters: maxDataSize: Maximum size in bytes ###### void setNumFrames(std::uint32_t numFrames) Kind: function Set number of frames in pool for sending messages forward parameters: numFrames: Maximum number of frames in pool ###### std::string getStreamName() Kind: function Get stream name. ###### int getBusId() Kind: function Get bus id. ###### std::uint32_t getMaxDataSize() Kind: function Get maximum messages size in bytes. ###### std::uint32_t getNumFrames() Kind: function Get number of frames in pool. ###### void buildInternal() Kind: function Function called from within the ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::SPIOut Kind: class SPIOut node. Sends messages over SPI. ###### Input input Kind: variable Input for any type of messages to be transferred over SPI stream Default queue is blocking with size 8 ###### void setStreamName(std::string name) Kind: function Specifies stream name over which the node will send data parameters: name: Stream name ###### void setBusId(int busId) Kind: function Specifies SPI Bus number to use parameters: id: SPI Bus id ###### void buildInternal() Kind: function Function called from within the ###### DeviceNodeCRTP() Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props) Kind: function ###### DeviceNodeCRTP(std::unique_ptr< Properties > props, bool confMode) Kind: function ###### DeviceNodeCRTP(const std::shared_ptr< Device > & device, std::unique_ptr< Properties > props, bool confMode) Kind: function ##### dai::node::Script Kind: class ###### InputMap inputs Kind: variable Inputs to Script node. Can be accessed using subscript operator (Eg: inputs['in1']) By default inputs are set to blocking with queue size 8 ###### OutputMap outputs Kind: variable Outputs from Script node. Can be accessed subscript operator (Eg: outputs['out1']) ###### void setScriptPath(const std::filesystem::path & path, const std::string & name) Kind: function Specify local filesystem path to load the script parameters: path: Filesystem path to load the script; name: Optionally set a name of this script, otherwise the name defaults to the path ###### void setScript(const std::string & script, const std::string & name) Kind: function Sets script data to be interpreted parameters: script: Script string to be interpreted; name: Optionally set a name of this script ###### void setScript(const std::vector< std::uint8_t > & data, const std::string & name) Kind: function Sets script data to be interpreted parameters: data: Binary data that represents the script to be interpreted; name: Optionally set a name of this script ###### std::filesystem::path getScriptPath() Kind: function Get filesystem path from where script was loaded. return: std::filesystem::path from where script was loaded, otherwise returns empty path ###### std::string getScriptName() Kind: function Get the script name in utf-8. When name set with setScript() or setScriptPath() , returns that name. When script loaded with setScriptPath() with name not provided, returns the utf-8 string of that path. Otherwise, returns "