API Reference<a class="headerlink" href="#module-depthai_sdk" title="Permalink to this headline">¶

queue(output, max_size=30)¶

Create a queue for the component output(s). This handles output streaming (OAK->Host) and message syncing.

Parameters

output (Union[depthai_sdk.components.component.ComponentOutput, depthai_sdk.components.component.Component, List]) – Component output(s) to be visualized. If component is passed, SDK will visualize its default output.
max_size (int) – Maximum queue size for this output.

Return type

depthai_sdk.classes.packet_handlers.QueuePacketHandler

callback(output, callback, main_thread=False)¶

Create a callback for the component output(s). This handles output streaming (OAK->Host) and message syncing.

Parameters

output (Union[List, Callable, depthai_sdk.components.component.Component]) – Component output(s) to be visualized. If component is passed, SDK will visualize its default output.
callback (Callable) – Handler function to which the Packet will be sent.
main_thread – Whether to run the callback in the main thread. If False, it will call the callback in a separate thread, so some functions (eg. cv2.imshow) won’t work.

Return type

depthai_sdk.classes.packet_handlers.CallbackPacketHandler

ros_stream(output)¶

Publish component output(s) to ROS streams.

Parameters: output (Union[List, depthai_sdk.components.component.ComponentOutput, depthai_sdk.components.component.Component]) –
Return type: depthai_sdk.classes.packet_handlers.RosPacketHandler

trigger_action(trigger, action)¶

Parameters

trigger (depthai_sdk.trigger_action.triggers.abstract_trigger.Trigger) –
action (Union[depthai_sdk.trigger_action.actions.abstract_action.Action, Callable]) –

Return type

property sensors¶: Returns list of all sensors added to the pipeline.

depthai_sdk.get_config_field(key)¶

Get sentry status from config file.

Returns: True if sentry is enabled, False otherwise.
Return type: bool
Parameters: key (str) –

class depthai_sdk.AbstractReader¶

Bases: abc.ABC

Methods:

`read`()	Read a frame (or multiple frames) from the reader.
`getStreams`()
`getShape`(name)	Returns (width, height)
`get_socket`(name)	Returns socket
`get_message_size`(name)	@param name: Stream name @return: Number of bytes for that this message contains
`close`()
`disableStream`(name)	@param name: Name of the stream to be disabled

abstract read()¶

Read a frame (or multiple frames) from the reader. @return: Single np.ndarray, or dict of frames and their names. None if frames weren’t read or there was an error.

Return type: Dict[str, numpy.ndarray]

abstract getStreams()¶

Return type: List[str]

abstract getShape(name)¶

Returns (width, height)

Parameters: name (str) –
Return type: Tuple[int, int]

get_socket(name)¶

Returns socket

Parameters: name (str) –

abstract get_message_size(name)¶

@param name: Stream name @return: Number of bytes for that this message contains

Parameters: name (str) –
Return type: int

abstract close()¶

abstract disableStream(name)¶

@param name: Name of the stream to be disabled

Parameters: name (str) –

class depthai_sdk.BboxStyle(value)¶

Bases: enum.IntEnum

How do we want to draw bounding box.

Attributes:

`RECTANGLE`
`CORNERS`
`ROUNDED_RECTANGLE`
`ROUNDED_CORNERS`

RECTANGLE = 0¶

CORNERS = 1¶

ROUNDED_RECTANGLE = 10¶

ROUNDED_CORNERS = 11¶

class depthai_sdk.CircleConfig(thickness=1, color=(255, 255, 255), line_type=16)¶

Bases: object

Configuration for drawing circles.

Attributes:

`thickness`
`color`
`line_type`

Methods:

__init__([thickness, color, line_type])

Initialize self.

thickness: int = 1¶

color: Tuple[int, int, int] = (255, 255, 255)¶

line_type: int = 16¶

__init__(thickness=1, color=(255, 255, 255), line_type=16)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

thickness (int) –
color (Tuple[int, int, int]) –
line_type (int) –

Return type

exception depthai_sdk.CrashDumpException¶: Bases: Exception

class depthai_sdk.DetectionConfig(thickness=1, fill_transparency=0.15, box_roundness=0, color=(0, 255, 0), bbox_style=<BboxStyle.RECTANGLE: 0>, line_width=0.5, line_height=0.5, hide_label=False, label_position=<TextPosition.TOP_LEFT: 0>, label_padding=10)¶

Bases: object

Configuration for drawing bounding boxes.

Attributes:

`thickness`
`fill_transparency`
`box_roundness`
`color`
`bbox_style`
`line_width`
`line_height`
`hide_label`
`label_position`
`label_padding`

Methods:

__init__([thickness, fill_transparency, …])

Initialize self.

thickness: int = 1¶

fill_transparency: float = 0.15¶

box_roundness: int = 0¶

color: Tuple[int, int, int] = (0, 255, 0)¶

bbox_style: depthai_sdk.visualize.configs.BboxStyle = 0¶

line_width: float = 0.5¶

line_height: float = 0.5¶

hide_label: bool = False¶

label_position: depthai_sdk.visualize.configs.TextPosition = 0¶

label_padding: int = 10¶

__init__(thickness=1, fill_transparency=0.15, box_roundness=0, color=(0, 255, 0), bbox_style=<BboxStyle.RECTANGLE: 0>, line_width=0.5, line_height=0.5, hide_label=False, label_position=<TextPosition.TOP_LEFT: 0>, label_padding=10)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

thickness (int) –
fill_transparency (float) –
box_roundness (int) –
color (Tuple[int, int, int]) –
bbox_style (depthai_sdk.visualize.configs.BboxStyle) –
line_width (float) –
line_height (float) –
hide_label (bool) –
label_position (depthai_sdk.visualize.configs.TextPosition) –
label_padding (int) –

Return type

class depthai_sdk.FramePacket(name, msg)¶

Bases: depthai_sdk.classes.packets.BasePacket

Contains only dai.ImgFrame message and cv2 frame, which is used by visualization logic.

Methods:

`__init__`(name, msg)	Initialize self.
`get_timestamp`()
`get_sequence_num`()
`set_decode_codec`(get_codec)
`decode`()
`get_size`()

Attributes:

frame

__init__(name, msg)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

name (str) –
msg (depthai.ImgFrame) –

property frame¶

get_timestamp()¶

Return type: datetime.timedelta

get_sequence_num()¶

Return type: int

set_decode_codec(get_codec)¶

Parameters: get_codec (Callable) –

decode()¶

Return type: Optional[numpy.ndarray]

get_size()¶

Return type: Tuple[int, int]

class depthai_sdk.IMUPacket(name, packet, rotation=None)¶

Bases: depthai_sdk.classes.packets.BasePacket

Methods:

`__init__`(name, packet[, rotation])	Initialize self.
`get_imu_vals`()	Returns imu values in a tuple.
`get_timestamp`()
`get_sequence_num`()

__init__(name, packet, rotation=None)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters: packet (depthai.IMUPacket) –

get_imu_vals()¶

Returns imu values in a tuple. Returns in format (accelerometer_values, gyroscope_values, quaternion, magnetometer_values)

Return type: Tuple[Sequence, Sequence, Sequence, Sequence]

get_timestamp()¶

Return type: datetime.timedelta

get_sequence_num()¶

Return type: int

class depthai_sdk.IntEnum(value)¶

Bases: int, enum.Enum

Enum where members are also (and must be) ints

class depthai_sdk.MouseClickTracker¶

Bases: object

Class that allows to track the click events on preview windows and show pixel value of a frame in coordinates pointed by the user.

Used internally by depthai_sdk.managers.PreviewManager

Attributes:

`points`	Stores selected point position per frame
`values`	Stores values assigned to specific point per frame

Methods:

`selectPoint`(name)	Returns callback function for `cv2.setMouseCallback` that will update the selected point on mouse click event from frame.
`extractValue`(name, frame)	Extracts value from frame for a specific point

points = {}¶

Stores selected point position per frame

Type: dict

values = {}¶

Stores values assigned to specific point per frame

Type: dict

selectPoint(name)¶

Returns callback function for cv2.setMouseCallback that will update the selected point on mouse click event from frame.

Usually used as

mct = MouseClickTracker()
# create preview window
cv2.setMouseCallback(window_name, mct.select_point(window_name))

Parameters: name (str) – Name of the frame
Returns: Callback function for cv2.setMouseCallback

extractValue(name, frame)¶

Extracts value from frame for a specific point

Parameters

name (str) – Name of the frame
frame (numpy.ndarray) –

class depthai_sdk.OutputConfig(img_scale=1.0, show_fps=False, clickable=True)¶

Bases: object

Configuration for output of the visualizer.

Attributes:

`img_scale`
`show_fps`
`clickable`

Methods:

__init__([img_scale, show_fps, clickable])

Initialize self.

img_scale: float = 1.0¶

show_fps: bool = False¶

clickable: bool = True¶

__init__(img_scale=1.0, show_fps=False, clickable=True)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

img_scale (float) –
show_fps (bool) –
clickable (bool) –

Return type

class depthai_sdk.Path(*args, **kwargs)¶

Bases: pathlib.PurePath

PurePath subclass that can make system calls.

Path represents a filesystem path but unlike PurePath, also offers methods to do system calls on path objects. Depending on your system, instantiating a Path will return either a PosixPath or a WindowsPath object. You can also instantiate a PosixPath or WindowsPath directly, but cannot instantiate a WindowsPath on a POSIX system or vice versa.

Methods:

`cwd`()	Return a new path pointing to the current working directory (as returned by os.getcwd()).
`home`()	Return a new path pointing to the user’s home directory (as returned by os.path.expanduser(‘~’)).
`samefile`(other_path)	Return whether other_path is the same or not as this file (as returned by os.path.samefile()).
`iterdir`()	Iterate over the files in this directory.
`glob`(pattern)	Iterate over this subtree and yield all existing files (of any kind, including directories) matching the given relative pattern.
`rglob`(pattern)	Recursively yield all existing files (of any kind, including directories) matching the given relative pattern, anywhere in this subtree.
`absolute`()	Return an absolute version of this path.
`resolve`([strict])	Make the path absolute, resolving all symlinks on the way and also normalizing it (for example turning slashes into backslashes under Windows).
`stat`()	Return the result of the stat() system call on this path, like os.stat() does.
`owner`()	Return the login name of the file owner.
`group`()	Return the group name of the file gid.
`open`([mode, buffering, encoding, errors, …])	Open the file pointed by this path and return a file object, as the built-in open() function does.
`read_bytes`()	Open the file in bytes mode, read it, and close the file.
`read_text`([encoding, errors])	Open the file in text mode, read it, and close the file.
`write_bytes`(data)	Open the file in bytes mode, write to it, and close the file.
`write_text`(data[, encoding, errors])	Open the file in text mode, write to it, and close the file.
`touch`([mode, exist_ok])	Create this file with the given access mode, if it doesn’t exist.
`mkdir`([mode, parents, exist_ok])	Create a new directory at this given path.
`chmod`(mode)	Change the permissions of the path, like os.chmod().
`lchmod`(mode)	Like chmod(), except if the path points to a symlink, the symlink’s permissions are changed, rather than its target’s.
`unlink`([missing_ok])	Remove this file or link.
`rmdir`()	Remove this directory.
`lstat`()	Like stat(), except if the path points to a symlink, the symlink’s status information is returned, rather than its target’s.
`rename`(target)	Rename this path to the target path.
`replace`(target)	Rename this path to the target path, overwriting if that path exists.
`symlink_to`(target[, target_is_directory])	Make this path a symlink pointing to the target path.
`link_to`(target)	Make the target path a hard link pointing to this path.
`exists`()	Whether this path exists.
`is_dir`()	Whether this path is a directory.
`is_file`()	Whether this path is a regular file (also True for symlinks pointing to regular files).
`is_mount`()	Check if this path is a POSIX mount point
`is_symlink`()	Whether this path is a symbolic link.
`is_block_device`()	Whether this path is a block device.
`is_char_device`()	Whether this path is a character device.
`is_fifo`()	Whether this path is a FIFO.
`is_socket`()	Whether this path is a socket.
`expanduser`()	Return a new path with expanded ~ and ~user constructs (as returned by os.path.expanduser)

classmethod cwd()¶: Return a new path pointing to the current working directory (as returned by os.getcwd()).

classmethod home()¶: Return a new path pointing to the user’s home directory (as returned by os.path.expanduser(‘~’)).

samefile(other_path)¶: Return whether other_path is the same or not as this file (as returned by os.path.samefile()).

iterdir()¶: Iterate over the files in this directory. Does not yield any result for the special paths ‘.’ and ‘..’.

glob(pattern)¶: Iterate over this subtree and yield all existing files (of any kind, including directories) matching the given relative pattern.

rglob(pattern)¶: Recursively yield all existing files (of any kind, including directories) matching the given relative pattern, anywhere in this subtree.

absolute()¶

Return an absolute version of this path. This function works even if the path doesn’t point to anything.

No normalization is done, i.e. all ‘.’ and ‘..’ will be kept along. Use resolve() to get the canonical path to a file.

resolve(strict=False)¶: Make the path absolute, resolving all symlinks on the way and also normalizing it (for example turning slashes into backslashes under Windows).

stat()¶: Return the result of the stat() system call on this path, like os.stat() does.

owner()¶: Return the login name of the file owner.

group()¶: Return the group name of the file gid.

open(mode='r', buffering=- 1, encoding=None, errors=None, newline=None)¶: Open the file pointed by this path and return a file object, as the built-in open() function does.

read_bytes()¶: Open the file in bytes mode, read it, and close the file.

read_text(encoding=None, errors=None)¶: Open the file in text mode, read it, and close the file.

write_bytes(data)¶: Open the file in bytes mode, write to it, and close the file.

write_text(data, encoding=None, errors=None)¶: Open the file in text mode, write to it, and close the file.

touch(mode=438, exist_ok=True)¶: Create this file with the given access mode, if it doesn’t exist.

mkdir(mode=511, parents=False, exist_ok=False)¶: Create a new directory at this given path.

chmod(mode)¶: Change the permissions of the path, like os.chmod().

lchmod(mode)¶: Like chmod(), except if the path points to a symlink, the symlink’s permissions are changed, rather than its target’s.

unlink(missing_ok=False)¶: Remove this file or link. If the path is a directory, use rmdir() instead.

rmdir()¶: Remove this directory. The directory must be empty.

lstat()¶: Like stat(), except if the path points to a symlink, the symlink’s status information is returned, rather than its target’s.

rename(target)¶

Rename this path to the target path.

The target path may be absolute or relative. Relative paths are interpreted relative to the current working directory, not the directory of the Path object.

Returns the new Path instance pointing to the target path.

replace(target)¶

Rename this path to the target path, overwriting if that path exists.

The target path may be absolute or relative. Relative paths are interpreted relative to the current working directory, not the directory of the Path object.

Returns the new Path instance pointing to the target path.

symlink_to(target, target_is_directory=False)¶: Make this path a symlink pointing to the target path. Note the order of arguments (link, target) is the reverse of os.symlink.

link_to(target)¶

Make the target path a hard link pointing to this path.

Note this function does not make this path a hard link to target, despite the implication of the function and argument names. The order of arguments (target, link) is the reverse of Path.symlink_to, but matches that of os.link.

exists()¶: Whether this path exists.

is_dir()¶: Whether this path is a directory.

is_file()¶: Whether this path is a regular file (also True for symlinks pointing to regular files).

is_mount()¶: Check if this path is a POSIX mount point

is_symlink()¶: Whether this path is a symbolic link.

is_block_device()¶: Whether this path is a block device.

is_char_device()¶: Whether this path is a character device.

is_fifo()¶: Whether this path is a FIFO.

is_socket()¶: Whether this path is a socket.

expanduser()¶: Return a new path with expanded ~ and ~user constructs (as returned by os.path.expanduser)

class depthai_sdk.PreviewDecoder¶

Bases: object

Methods:

`jpegDecode`(data, type)
`nnInput`(packet[, manager])	Produces NN passthough frame from raw data packet
`color`(packet[, manager])	Produces color camera frame from raw data packet
`left`(packet[, manager])	Produces left camera frame from raw data packet
`right`(packet[, manager])	Produces right camera frame from raw data packet
`rectifiedLeft`(packet[, manager])	Produces rectified left frame (`depthai.node.StereoDepth.rectifiedLeft`) from raw data packet
`rectifiedRight`(packet[, manager])	Produces rectified right frame (`depthai.node.StereoDepth.rectifiedRight`) from raw data packet
`depthRaw`(packet[, manager])	Produces raw depth frame (`depthai.node.StereoDepth.depth`) from raw data packet
`depth`(depthRaw[, manager])	Produces depth frame from raw depth frame (converts to disparity and applies color map)
`disparity`(packet[, manager])	Produces disparity frame (`depthai.node.StereoDepth.disparity`) from raw data packet
`disparityColor`(disparity[, manager])	Applies color map to disparity frame

static jpegDecode(data, type)¶

static nnInput(packet, manager=None)¶

Produces NN passthough frame from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static color(packet, manager=None)¶

Produces color camera frame from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static left(packet, manager=None)¶

Produces left camera frame from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static right(packet, manager=None)¶

Produces right camera frame from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static rectifiedLeft(packet, manager=None)¶

Produces rectified left frame (depthai.node.StereoDepth.rectifiedLeft) from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static rectifiedRight(packet, manager=None)¶

Produces rectified right frame (depthai.node.StereoDepth.rectifiedRight) from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static depthRaw(packet, manager=None)¶

Produces raw depth frame (depthai.node.StereoDepth.depth) from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static depth(depthRaw, manager=None)¶

Produces depth frame from raw depth frame (converts to disparity and applies color map)

Parameters

depthRaw (numpy.ndarray) – OpenCV frame containing raw depth frame
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static disparity(packet, manager=None)¶

Produces disparity frame (depthai.node.StereoDepth.disparity) from raw data packet

Parameters

packet (depthai.ImgFrame) – Packet received from output queue
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

static disparityColor(disparity, manager=None)¶

Applies color map to disparity frame

Parameters

disparity (numpy.ndarray) – OpenCV frame containing disparity frame
manager (depthai_sdk.managers.PreviewManager, optional) – PreviewManager instance

Returns

Ready to use OpenCV frame

Return type

class depthai_sdk.Previews(value)¶

Bases: enum.Enum

Enum class, assigning preview name with decode function.

Usually used as e.g. Previews.color.name when specifying color preview name.

Can be also used as e.g. Previews.color.value(packet) to transform queue output packet to color camera frame

Attributes:

`nnInput`(args, *kwargs)
`color`(args, *kwargs)
`left`(args, *kwargs)
`right`(args, *kwargs)
`rectifiedLeft`(args, *kwargs)
`rectifiedRight`(args, *kwargs)
`depthRaw`(args, *kwargs)
`depth`(args, *kwargs)
`disparity`(args, *kwargs)
`disparityColor`(args, *kwargs)

nnInput(*args, **kwargs) = functools.partial(<function PreviewDecoder.nnInput>)¶

color(*args, **kwargs) = functools.partial(<function PreviewDecoder.color>)¶

left(*args, **kwargs) = functools.partial(<function PreviewDecoder.left>)¶

right(*args, **kwargs) = functools.partial(<function PreviewDecoder.right>)¶

rectifiedLeft(*args, **kwargs) = functools.partial(<function PreviewDecoder.rectifiedLeft>)¶

rectifiedRight(*args, **kwargs) = functools.partial(<function PreviewDecoder.rectifiedRight>)¶

depthRaw(*args, **kwargs) = functools.partial(<function PreviewDecoder.depthRaw>)¶

depth(*args, **kwargs) = functools.partial(<function PreviewDecoder.depth>)¶

disparity(*args, **kwargs) = functools.partial(<function PreviewDecoder.disparity>)¶

disparityColor(*args, **kwargs) = functools.partial(<function PreviewDecoder.disparityColor>)¶

class depthai_sdk.Queue(maxsize=0)¶

Bases: object

Create a queue object with a given maximum size.

If maxsize is <= 0, the queue size is infinite.

Methods:

`__init__`([maxsize])	Initialize self.
`task_done`()	Indicate that a formerly enqueued task is complete.
`join`()	Blocks until all items in the Queue have been gotten and processed.
`qsize`()	Return the approximate size of the queue (not reliable!).
`empty`()	Return True if the queue is empty, False otherwise (not reliable!).
`full`()	Return True if the queue is full, False otherwise (not reliable!).
`put`(item[, block, timeout])	Put an item into the queue.
`get`([block, timeout])	Remove and return an item from the queue.
`put_nowait`(item)	Put an item into the queue without blocking.
`get_nowait`()	Remove and return an item from the queue without blocking.

__init__(maxsize=0)¶: Initialize self. See help(type(self)) for accurate signature.

task_done()¶

Indicate that a formerly enqueued task is complete.

Used by Queue consumer threads. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete.

If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue).

Raises a ValueError if called more times than there were items placed in the queue.

join()¶

Blocks until all items in the Queue have been gotten and processed.

The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate the item was retrieved and all work on it is complete.

When the count of unfinished tasks drops to zero, join() unblocks.

qsize()¶: Return the approximate size of the queue (not reliable!).

empty()¶

Return True if the queue is empty, False otherwise (not reliable!).

This method is likely to be removed at some point. Use qsize() == 0 as a direct substitute, but be aware that either approach risks a race condition where a queue can grow before the result of empty() or qsize() can be used.

To create code that needs to wait for all queued tasks to be completed, the preferred technique is to use the join() method.

full()¶

Return True if the queue is full, False otherwise (not reliable!).

This method is likely to be removed at some point. Use qsize() >= n as a direct substitute, but be aware that either approach risks a race condition where a queue can shrink before the result of full() or qsize() can be used.

put(item, block=True, timeout=None)¶

Put an item into the queue.

If optional args ‘block’ is true and ‘timeout’ is None (the default), block if necessary until a free slot is available. If ‘timeout’ is a non-negative number, it blocks at most ‘timeout’ seconds and raises the Full exception if no free slot was available within that time. Otherwise (‘block’ is false), put an item on the queue if a free slot is immediately available, else raise the Full exception (‘timeout’ is ignored in that case).

get(block=True, timeout=None)¶

Remove and return an item from the queue.

If optional args ‘block’ is true and ‘timeout’ is None (the default), block if necessary until an item is available. If ‘timeout’ is a non-negative number, it blocks at most ‘timeout’ seconds and raises the Empty exception if no item was available within that time. Otherwise (‘block’ is false), return an item if one is immediately available, else raise the Empty exception (‘timeout’ is ignored in that case).

put_nowait(item)¶

Put an item into the queue without blocking.

Only enqueue the item if a free slot is immediately available. Otherwise raise the Full exception.

get_nowait()¶

Remove and return an item from the queue without blocking.

Only get an item if one is immediately available. Otherwise raise the Empty exception.

class depthai_sdk.Record(path, record_type)¶

Bases: object

This class records depthai streams from OAK cameras into different formats. It will also save calibration .json, so depth reconstruction will be possible.

Methods:

`__init__`(path, record_type)	param path Path to the recording folder
`write`(packets)
`start`(device, xouts)	Start recording process.
`config_mcap`(pointcloud)
`close`()

__init__(path, record_type)¶

Parameters

path (Path) – Path to the recording folder
record_type (RecordType) – Recording type

write(packets)¶

start(device, xouts)¶

Start recording process. This will create and start the pipeline, start recording threads, and initialize all queues.

Parameters

device (depthai.Device) –
xouts (List[depthai_sdk.oak_outputs.xout.xout_frames.XoutFrames]) –

config_mcap(pointcloud)¶

Parameters: pointcloud (bool) –

close()¶

class depthai_sdk.RecordType(value)¶

Bases: enum.IntEnum

An enumeration.

Attributes:

`VIDEO`
`VIDEO_LOSSLESS`
`ROSBAG`
`MCAP`
`DB3`

VIDEO = 1¶

VIDEO_LOSSLESS = 2¶

ROSBAG = 3¶

MCAP = 4¶

DB3 = 5¶

class depthai_sdk.Recorder¶

Bases: abc.ABC

Methods:

`write`(name, frame)
`close`()
`update`(path, device, xouts)

abstract write(name, frame)¶

Parameters

name (str) –
frame (depthai.ImgFrame) –

abstract close()¶

abstract update(path, device, xouts)¶

Parameters

path (pathlib.Path) –
device (depthai.Device) –
xouts (List[XoutFrames]) –

class depthai_sdk.Replay(path)¶

Bases: object

Methods:

`__init__`(path)	Helper file to replay recorded depthai stream.
`toggle_pause`()	Toggle pausing of sending frames to the OAK camera.
`set_fps`(fps)	Sets frequency at which Replay module will send frames to the camera.
`set_loop`(flag)	Sets whether to loop the replay.
`get_fps`()
`resize`(stream_name, size[, mode])	Resize color frames prior to sending them to the device.
`keepAspectRatio`(keepAspectRatio)
`disableStream`(stream_name[, disableReading])	Disable sending a recorded stream to the device.
`specify_socket`(stream_name, socket)
`initPipeline`([pipeline])	Prepares the pipeline for replaying.
`initStereoDepth`(stereo[, left_name, …])
`start`()	Start sending frames to the OAK device on a new thread
`sendFrames`()	Reads and sends recorded frames from all enabled streams to the OAK camera.
`createQueues`(device)	Creates input queue for each enabled stream
`getStreams`()
`getShape`(name)	Get shape of a stream
`close`()	Closes all video readers.

__init__(path)¶

Helper file to replay recorded depthai stream. It reads from recorded files (mjpeg/avi/mp4/h265/h264/bag) and sends frames back to OAK camera to replay the scene, including depth reconstruction from 2 synced mono streams.

Parameters: path (str) – Path to the recording folder.

toggle_pause()¶: Toggle pausing of sending frames to the OAK camera.

set_fps(fps)¶

Sets frequency at which Replay module will send frames to the camera. Default 30FPS.

Parameters: fps (float) –

set_loop(flag)¶

Sets whether to loop the replay.

Parameters: flag (bool) – Whether to loop the replay.

get_fps()¶

Return type: float

resize(stream_name, size, mode=<ResizeMode.STRETCH: 1>)¶

Resize color frames prior to sending them to the device.

Parameters

stream_name (str) – Name of the stream we want to resize
size (Tuple(width, heigth)) – Size of color frames that are sent to the camera
mode (ResizeMode) – How to actually resize the stream

keepAspectRatio(keepAspectRatio)¶

Parameters: keepAspectRatio (bool) –

disableStream(stream_name, disableReading=False)¶

Disable sending a recorded stream to the device.

Parameters

streamName (str) – Name of the stream to disable (eg. ‘left’, ‘color’, ‘depth’, etc.)
disableReading (bool, Optional) – Also disable reading frames from the file
stream_name (str) –

specify_socket(stream_name, socket)¶

Parameters

stream_name (str) –
socket (depthai.CameraBoardSocket) –

initPipeline(pipeline=None)¶

Prepares the pipeline for replaying. It creates XLinkIn nodes and sets up StereoDepth node. Returns: dai.Pipeline

Parameters: pipeline (Optional[depthai.Pipeline]) –

initStereoDepth(stereo, left_name='left', right_name='right', align_to='')¶

Parameters

stereo (depthai.node.StereoDepth) –
left_name (str) –
right_name (str) –
align_to (str) –

start()¶: Start sending frames to the OAK device on a new thread

sendFrames()¶

Reads and sends recorded frames from all enabled streams to the OAK camera.

Returns: True if successful, otherwise False.
Return type: bool

createQueues(device)¶

Creates input queue for each enabled stream

Parameters: device (dai.Device) – Device to which we will stream frames

getStreams()¶

Return type: List[str]

getShape(name)¶

Get shape of a stream

Parameters: name (str) –
Return type: Tuple[int, int]

close()¶: Closes all video readers.

class depthai_sdk.ReplayStream¶

Bases: object

Attributes:

shape

Methods:

`__init__`()	Initialize self.
`get_socket`()

property shape¶

__init__()¶: Initialize self. See help(type(self)) for accurate signature.

get_socket()¶

Return type: depthai.CameraBoardSocket

class depthai_sdk.SegmentationConfig(mask_alpha=0.5)¶

Bases: object

Configuration for drawing segmentation masks.

Attributes:

mask_alpha

Methods:

__init__([mask_alpha])

Initialize self.

mask_alpha: float = 0.5¶

__init__(mask_alpha=0.5)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters: mask_alpha (float) –
Return type: None

class depthai_sdk.StereoColor(value)¶

Bases: enum.IntEnum

An enumeration.

Attributes:

`GRAY`
`RGB`
`RGBD`

GRAY = 1¶

RGB = 2¶

RGBD = 3¶

class depthai_sdk.StereoConfig(colorize: depthai_sdk.visualize.configs.StereoColor = <StereoColor.RGB: 2>, colormap: numpy.ndarray = <factory>, wls_filter: bool = False, wls_lambda: float = 8000, wls_sigma: float = 1.5)¶

Bases: object

Attributes:

`colorize`
`wls_filter`
`wls_lambda`
`wls_sigma`

Methods:

__init__([colorize, colormap, wls_filter, …])

Initialize self.

colorize: depthai_sdk.visualize.configs.StereoColor = 2¶

colormap: numpy.ndarray¶

wls_filter: bool = False¶

wls_lambda: float = 8000¶

wls_sigma: float = 1.5¶

__init__(colorize=<StereoColor.RGB: 2>, colormap=<factory>, wls_filter=False, wls_lambda=8000, wls_sigma=1.5)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

colorize (depthai_sdk.visualize.configs.StereoColor) –
colormap (numpy.ndarray) –
wls_filter (bool) –
wls_lambda (float) –
wls_sigma (float) –

Return type

class depthai_sdk.TextConfig(font_face=0, font_color=(255, 255, 255), font_transparency=0.5, font_scale=1.0, font_thickness=2, font_position=<TextPosition.TOP_LEFT: 0>, background_color=None, background_transparency=0.5, outline_color=(0, 0, 0), line_type=16, auto_scale=True)¶

Bases: object

Configuration for drawing labels.

Attributes:

`font_face`
`font_color`
`font_transparency`
`font_scale`
`font_thickness`
`font_position`
`background_color`
`background_transparency`
`outline_color`
`line_type`
`auto_scale`

Methods:

__init__([font_face, font_color, …])

Initialize self.

font_face: int = 0¶

font_color: Tuple[int, int, int] = (255, 255, 255)¶

font_transparency: float = 0.5¶

font_scale: float = 1.0¶

font_thickness: int = 2¶

font_position: depthai_sdk.visualize.configs.TextPosition = 0¶

background_color: Optional[Tuple[int, int, int]] = None¶

background_transparency: float = 0.5¶

outline_color: Tuple[int, int, int] = (0, 0, 0)¶

line_type: int = 16¶

auto_scale: bool = True¶

__init__(font_face=0, font_color=(255, 255, 255), font_transparency=0.5, font_scale=1.0, font_thickness=2, font_position=<TextPosition.TOP_LEFT: 0>, background_color=None, background_transparency=0.5, outline_color=(0, 0, 0), line_type=16, auto_scale=True)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

font_face (int) –
font_color (Tuple[int, int, int]) –
font_transparency (float) –
font_scale (float) –
font_thickness (int) –
font_position (depthai_sdk.visualize.configs.TextPosition) –
background_color (Optional[Tuple[int, int, int]]) –
background_transparency (float) –
outline_color (Tuple[int, int, int]) –
line_type (int) –
auto_scale (bool) –

Return type

class depthai_sdk.TextPosition(value)¶

Bases: enum.IntEnum

Where on frame do we want to print text.

Attributes:

`TOP_LEFT`
`MID_LEFT`
`BOTTOM_LEFT`
`TOP_MID`
`MID`
`BOTTOM_MID`
`TOP_RIGHT`
`MID_RIGHT`
`BOTTOM_RIGHT`

TOP_LEFT = 0¶

MID_LEFT = 1¶

BOTTOM_LEFT = 2¶

TOP_MID = 10¶

MID = 11¶

BOTTOM_MID = 12¶

TOP_RIGHT = 20¶

MID_RIGHT = 21¶

BOTTOM_RIGHT = 22¶

class depthai_sdk.Thread(group=None, target=None, name=None, args=(), kwargs=None, *, daemon=None)¶

Bases: object

A class that represents a thread of control.

This class can be safely subclassed in a limited fashion. There are two ways to specify the activity: by passing a callable object to the constructor, or by overriding the run() method in a subclass.

Methods:

`__init__`([group, target, name, args, …])	This constructor should always be called with keyword arguments.
`start`(a, *kw)
`run`()	Method representing the thread’s activity.
`join`([timeout])	Wait until the thread terminates.
`is_alive`()	Return whether the thread is alive.
`isAlive`()	Return whether the thread is alive.
`isDaemon`()
`setDaemon`(daemonic)
`getName`()
`setName`(name)

Attributes:

`name`	A string used for identification purposes only.
`ident`	Thread identifier of this thread or None if it has not been started.
`native_id`	Native integral thread ID of this thread, or None if it has not been started.
`daemon`	A boolean value indicating whether this thread is a daemon thread.

__init__(group=None, target=None, name=None, args=(), kwargs=None, *, daemon=None)¶

This constructor should always be called with keyword arguments. Arguments are:

group should be None; reserved for future extension when a ThreadGroup class is implemented.

target is the callable object to be invoked by the run() method. Defaults to None, meaning nothing is called.

name is the thread name. By default, a unique name is constructed of the form “Thread-N” where N is a small decimal number.

args is the argument tuple for the target invocation. Defaults to ().

kwargs is a dictionary of keyword arguments for the target invocation. Defaults to {}.

If a subclass overrides the constructor, it must make sure to invoke the base class constructor (Thread.__init__()) before doing anything else to the thread.

start(*a, **kw)¶

Parameters

a (Thread) –
kw (Any) –

Return type

Any

run()¶

Method representing the thread’s activity.

You may override this method in a subclass. The standard run() method invokes the callable object passed to the object’s constructor as the target argument, if any, with sequential and keyword arguments taken from the args and kwargs arguments, respectively.

join(timeout=None)¶

Wait until the thread terminates.

This blocks the calling thread until the thread whose join() method is called terminates – either normally or through an unhandled exception or until the optional timeout occurs.

When the timeout argument is present and not None, it should be a floating point number specifying a timeout for the operation in seconds (or fractions thereof). As join() always returns None, you must call is_alive() after join() to decide whether a timeout happened – if the thread is still alive, the join() call timed out.

When the timeout argument is not present or None, the operation will block until the thread terminates.

A thread can be join()ed many times.

join() raises a RuntimeError if an attempt is made to join the current thread as that would cause a deadlock. It is also an error to join() a thread before it has been started and attempts to do so raises the same exception.

property name¶

A string used for identification purposes only.

It has no semantics. Multiple threads may be given the same name. The initial name is set by the constructor.

property ident¶

Thread identifier of this thread or None if it has not been started.

This is a nonzero integer. See the get_ident() function. Thread identifiers may be recycled when a thread exits and another thread is created. The identifier is available even after the thread has exited.

property native_id¶

Native integral thread ID of this thread, or None if it has not been started.

This is a non-negative integer. See the get_native_id() function. This represents the Thread ID as reported by the kernel.

is_alive()¶

Return whether the thread is alive.

This method returns True just before the run() method starts until just after the run() method terminates. The module function enumerate() returns a list of all alive threads.

isAlive()¶

Return whether the thread is alive.

This method is deprecated, use is_alive() instead.

property daemon¶

A boolean value indicating whether this thread is a daemon thread.

This must be set before start() is called, otherwise RuntimeError is raised. Its initial value is inherited from the creating thread; the main thread is not a daemon thread and therefore all threads created in the main thread default to daemon = False.

The entire Python program exits when only daemon threads are left.

isDaemon()¶

setDaemon(daemonic)¶

getName()¶

setName(name)¶

class depthai_sdk.TrackingConfig(max_length=500, deletion_lost_threshold=5, line_thickness=1, fading_tails=False, line_color=(255, 255, 255), line_type=16, show_speed=False)¶

Bases: object

Configuration for drawing tracking bounding boxes.

Attributes:

`max_length`
`deletion_lost_threshold`
`line_thickness`
`fading_tails`
`line_color`
`line_type`
`show_speed`

Methods:

__init__([max_length, …])

Initialize self.

max_length: int = 500¶

deletion_lost_threshold: int = 5¶

line_thickness: int = 1¶

fading_tails: bool = False¶

line_color: Tuple[int, int, int] = (255, 255, 255)¶

line_type: int = 16¶

show_speed: bool = False¶

__init__(max_length=500, deletion_lost_threshold=5, line_thickness=1, fading_tails=False, line_color=(255, 255, 255), line_type=16, show_speed=False)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

max_length (int) –
deletion_lost_threshold (int) –
line_thickness (int) –
fading_tails (bool) –
line_color (Tuple[int, int, int]) –
line_type (int) –
show_speed (bool) –

Return type

class depthai_sdk.TurboJPEG(lib_path=None)¶

Bases: object

A Python wrapper of libjpeg-turbo for decoding and encoding JPEG image.

Methods:

`__init__`([lib_path])	Initialize self.
`decode_header`(jpeg_buf)	decodes JPEG header and returns image properties as a tuple.
`decode`(jpeg_buf[, pixel_format, …])	decodes JPEG memory buffer to numpy array.
`decode_to_yuv`(jpeg_buf[, scaling_factor, …])	decodes JPEG memory buffer to yuv array.
`decode_to_yuv_planes`(jpeg_buf[, …])	decodes JPEG memory buffer to yuv planes.
`encode`(img_array[, quality, pixel_format, …])	encodes numpy array to JPEG memory buffer.
`scale_with_quality`(jpeg_buf[, …])	decompresstoYUV with scale factor, recompresstoYUV with quality factor
`crop`(jpeg_buf, x, y, w, h[, preserve, gray])	losslessly crop a jpeg image with optional grayscale
`crop_multiple`(jpeg_buf, crop_parameters[, …])	Lossless crop and/or extension operations on jpeg image.

Attributes:

scaling_factors

__init__(lib_path=None)¶: Initialize self. See help(type(self)) for accurate signature.

decode_header(jpeg_buf)¶: decodes JPEG header and returns image properties as a tuple. e.g. (width, height, jpeg_subsample, jpeg_colorspace)

decode(jpeg_buf, pixel_format=1, scaling_factor=None, flags=0)¶: decodes JPEG memory buffer to numpy array.

decode_to_yuv(jpeg_buf, scaling_factor=None, pad=4, flags=0)¶: decodes JPEG memory buffer to yuv array.

decode_to_yuv_planes(jpeg_buf, scaling_factor=None, strides=(0, 0, 0), flags=0)¶: decodes JPEG memory buffer to yuv planes.

encode(img_array, quality=85, pixel_format=1, jpeg_subsample=1, flags=0)¶: encodes numpy array to JPEG memory buffer.

scale_with_quality(jpeg_buf, scaling_factor=None, quality=85, flags=0)¶: decompresstoYUV with scale factor, recompresstoYUV with quality factor

crop(jpeg_buf, x, y, w, h, preserve=False, gray=False)¶: losslessly crop a jpeg image with optional grayscale

crop_multiple(jpeg_buf, crop_parameters, background_luminance=1.0, gray=False)¶

Lossless crop and/or extension operations on jpeg image. Crop origin(s) needs be divisable by the MCU block size and inside the input image, or OSError: Invalid crop request is raised.

Parameters

jpeg_buf (bytes) – Input jpeg image.
crop_parameters (List[Tuple[int, int, int, int]]) – List of crop parameters defining start x and y origin and width and height of each crop operation.
background_luminance (float) – Luminance level (0 -1 ) to fill background when extending image. Default to 1, resulting in white background.
gray (bool) – Produce greyscale output

Returns

Cropped and/or extended jpeg images.

Return type

List[bytes]

property scaling_factors¶

class depthai_sdk.VisConfig(output=<factory>, stereo=<factory>, detection=<factory>, text=<factory>, tracking=<factory>, circle=<factory>)¶

Bases: object

Configuration for visualizer.

Attributes:

Methods:

__init__([output, stereo, detection, text, …])

Initialize self.

output: depthai_sdk.visualize.configs.OutputConfig¶

stereo: depthai_sdk.visualize.configs.StereoConfig¶

detection: depthai_sdk.visualize.configs.DetectionConfig¶

text: depthai_sdk.visualize.configs.TextConfig¶

tracking: depthai_sdk.visualize.configs.TrackingConfig¶

circle: depthai_sdk.visualize.configs.CircleConfig¶

__init__(output=<factory>, stereo=<factory>, detection=<factory>, text=<factory>, tracking=<factory>, circle=<factory>)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

output (depthai_sdk.visualize.configs.OutputConfig) –
stereo (depthai_sdk.visualize.configs.StereoConfig) –
detection (depthai_sdk.visualize.configs.DetectionConfig) –
text (depthai_sdk.visualize.configs.TextConfig) –
tracking (depthai_sdk.visualize.configs.TrackingConfig) –
circle (depthai_sdk.visualize.configs.CircleConfig) –

Return type

class depthai_sdk.Visualizer(scale=None, fps=False)¶

Bases: object

Methods:

`__init__`([scale, fps])	Initialize self.
`add_object`(obj)	Call set_config, set_frame_shape and prepare for the object and add it to the list of objects.
`add_bbox`(bbox[, color, thickness, …])	Add a bounding box to the visualizer.
`add_detections`(detections[, normalizer, …])	Add detections to the visualizer.
`add_text`(text[, coords, size, color, …])	Add text to the visualizer.
`add_trail`(tracklets, label_map[, bbox])	Add a trail to the visualizer.
`add_circle`(coords, radius[, color, thickness])	Add a circle to the visualizer.
`add_line`(pt1, pt2[, color, thickness])	Add a line to the visualizer.
`add_mask`(mask, alpha)	Add a mask to the visualizer.
`drawn`(frame)	Draw all objects on the frame if the platform is PC.
`show`(packet)	Show the packet on the screen.
`serialize`([force_reset])	Serialize all contained objects to JSON.
`reset`()	Clear all objects.
`output`([img_scale, show_fps])	Configure the output of the visualizer.
`stereo`([colorize, colormap, wls_filter, …])
`detections`([thickness, fill_transparency, …])	Configure how bounding boxes will look like.
`text`([font_face, font_color, …])	Configure how text will look like.
`tracking`([max_length, …])	Configure how tracking trails will look like.
`segmentation`([mask_alpha])
`close`()

Attributes:

frame_shape

__init__(scale=None, fps=False)¶

Initialize self. See help(type(self)) for accurate signature.

Parameters

scale (Optional[float]) –
fps (bool) –

add_object(obj)¶

Call set_config, set_frame_shape and prepare for the object and add it to the list of objects. :param obj: The object to add.

Returns: self
Parameters: obj (depthai_sdk.visualize.objects.GenericObject) –
Return type: depthai_sdk.visualize.visualizer.Visualizer

add_bbox(bbox, color=None, thickness=None, bbox_style=None, label=None)¶

Add a bounding box to the visualizer.

Parameters

bbox (depthai_sdk.visualize.bbox.BoundingBox) – Bounding box.
label (Optional[str]) – Label for the detection.
thickness (Optional[int]) – Bounding box thickness.
color (Optional[Tuple[int, int, int]]) – Bounding box color (RGB).
bbox_style (Optional[depthai_sdk.visualize.configs.BboxStyle]) – Bounding box style (one of depthai_sdk.visualize.configs.BboxStyle).

Returns

self

Return type

add_detections(detections, normalizer=None, label_map=None, spatial_points=None, label_color=None, label_background_color=None, label_background_transparency=None, is_spatial=False, bbox=None)¶

Add detections to the visualizer.

Parameters

detections (List[Union[depthai.ImgDetection, depthai.Tracklet]]) – List of detections.
normalizer (Optional[depthai_sdk.visualize.bbox.BoundingBox]) – Normalizer object.
label_map (Optional[List[Tuple[str, Tuple]]]) – List of tuples (label, color).
spatial_points (Optional[List[depthai.Point3f]]) – List of spatial points. None if not spatial.
label_color (Optional[Tuple[int, int, int]]) – Color for the label.
label_background_color (Optional[Tuple[int, int, int]]) – Color for the label background.
label_background_transparency (Optional[float]) – Transparency for the label background.
is_spatial – Flag that indicates if the detections are spatial.
bbox (Optional[Union[numpy.ndarray, Tuple[int, int, int, int]]]) – Bounding box, if there’s a detection inside a bounding box.

Returns

self

Return type

add_text(text, coords=None, size=None, color=None, thickness=None, outline=True, background_color=None, background_transparency=0.5, bbox=None, position=<TextPosition.TOP_LEFT: 0>, padding=10)¶

Add text to the visualizer.

Parameters

text (str) – Text.
coords (Optional[Tuple[int, int]]) – Coordinates.
size (Optional[int]) – Size of the text.
color (Optional[Tuple[int, int, int]]) – Color of the text.
thickness (Optional[int]) – Thickness of the text.
outline (bool) – Flag that indicates if the text should be outlined.
background_color (Optional[Tuple[int, int, int]]) – Background color.
background_transparency (float) – Background transparency.
bbox (Optional[Union[numpy.ndarray, Tuple, depthai_sdk.visualize.bbox.BoundingBox]]) – Bounding box.
position (depthai_sdk.visualize.configs.TextPosition) – Position.
padding (int) – Padding.

Returns

self

Return type

add_trail(tracklets, label_map, bbox=None)¶

Add a trail to the visualizer.

Parameters

tracklets (List[depthai.Tracklet]) – List of tracklets.
label_map (List[Tuple[str, Tuple]]) – List of tuples (label, color).
bbox (Optional[depthai_sdk.visualize.bbox.BoundingBox]) – Bounding box.

Returns

self

Return type

add_circle(coords, radius, color=None, thickness=None)¶

Add a circle to the visualizer.

Parameters

coords (Tuple[int, int]) – Center of the circle.
radius (int) – Radius of the circle.
color (Optional[Tuple[int, int, int]]) – Color of the circle.
thickness (Optional[int]) – Thickness of the circle.

Returns

self

Return type

add_line(pt1, pt2, color=None, thickness=None)¶

Add a line to the visualizer.

Parameters

pt1 (Tuple[int, int]) – Start coordinates.
pt2 (Tuple[int, int]) – End coordinates.
color (Optional[Tuple[int, int, int]]) – Color of the line.
thickness (Optional[int]) – Thickness of the line.

Returns

self

Return type

add_mask(mask, alpha)¶

Add a mask to the visualizer.

Parameters

mask (numpy.ndarray) – Mask represented as uint8 numpy array.
alpha (float) – Transparency of the mask.

Returns

self

drawn(frame)¶

Draw all objects on the frame if the platform is PC. Otherwise, serialize the objects and communicate with the RobotHub application.

Parameters: frame (numpy.ndarray) – The frame to draw on.
Returns: np.ndarray if the platform is PC, None otherwise.
Return type: Optional[numpy.ndarray]

show(packet)¶: Show the packet on the screen.

serialize(force_reset=True)¶

Serialize all contained objects to JSON.

Parameters: force_reset (bool) – Flag that indicates if the objects should be cleared after serialization.
Returns: Stringified JSON.
Return type: str

reset()¶: Clear all objects.

output(img_scale=None, show_fps=None)¶

Configure the output of the visualizer.

Parameters

img_scale (Optional[float]) – Scale of the output image.
show_fps (Optional[bool]) – Flag that indicates if the FPS should be shown.

Returns

self

Return type

stereo(colorize=None, colormap=None, wls_filter=None, wls_lambda=None, wls_sigma=None)¶

Parameters

colorize (Optional[depthai_sdk.visualize.configs.StereoColor]) –
colormap (Optional[int]) –
wls_filter (Optional[bool]) –
wls_lambda (Optional[float]) –
wls_sigma (Optional[float]) –

detections(thickness=None, fill_transparency=None, bbox_roundness=None, color=None, bbox_style=None, line_width=None, line_height=None, hide_label=None, label_position=None, label_padding=None)¶

Configure how bounding boxes will look like. :param thickness: Thickness of the bounding box. :param fill_transparency: Transparency of the bounding box. :param bbox_roundness: Roundness of the bounding box. :param color: Color of the bounding box. :param bbox_style: Style of the bounding box. :param line_width: Width of the bbox horizontal lines CORNERS or ROUNDED_CORNERS style is used. :param line_height: Height of the bbox vertical lines when CORNERS or ROUNDED_CORNERS style is used. :param hide_label: Flag that indicates if the label should be hidden. :param label_position: Position of the label. :param label_padding: Padding of the label.

Returns

self

Parameters

thickness (Optional[int]) –
fill_transparency (Optional[float]) –
bbox_roundness (Optional[float]) –
color (Optional[Tuple[int, int, int]]) –
bbox_style (Optional[depthai_sdk.visualize.configs.BboxStyle]) –
line_width (Optional[float]) –
line_height (Optional[float]) –
hide_label (Optional[bool]) –
label_position (Optional[depthai_sdk.visualize.configs.TextPosition]) –
label_padding (Optional[int]) –

Return type

text(font_face=None, font_color=None, font_transparency=None, font_scale=None, font_thickness=None, font_position=None, background_transparency=None, background_color=None, outline_color=None, line_type=None, auto_scale=None)¶

Configure how text will look like.

Parameters

font_face (Optional[int]) – Font face (from cv2).
font_color (Optional[Tuple[int, int, int]]) – Font color.
font_transparency (Optional[float]) – Font transparency.
font_scale (Optional[float]) – Font scale.
font_thickness (Optional[int]) – Font thickness.
font_position (Optional[depthai_sdk.visualize.configs.TextPosition]) – Font position.
background_transparency (Optional[float]) – Text background transparency.
background_color (Optional[Tuple[int, int, int]]) – Text background color.
outline_color (Optional[Tuple[int, int, int]]) – Outline color.
line_type (Optional[int]) – Line type (from cv2).
auto_scale (Optional[bool]) – Flag that indicates if the font scale should be automatically adjusted.

Returns

self

Return type

tracking(max_length=None, deletion_lost_threshold=None, line_thickness=None, fading_tails=None, show_speed=None, line_color=None, line_type=None, bg_color=None)¶

Configure how tracking trails will look like.

Parameters

max_length (Optional[int]) – Maximum length of the trail (in pixels).
deletion_lost_threshold (Optional[int]) – Number of consequent LOST statuses after which the trail is deleted.
line_thickness (Optional[int]) – Thickness of the line.
fading_tails (Optional[bool]) – Flag that indicates if the tails should fade.
show_speed (Optional[bool]) – Flag that indicates if the speed should be shown.
line_color (Optional[Tuple[int, int, int]]) – Color of the line.
line_type (Optional[int]) – Type of the line (from cv2).
bg_color (Optional[Tuple[int, int, int]]) – Text background color.

Returns

self

Return type

segmentation(mask_alpha=None)¶

Parameters: mask_alpha (Optional[float]) –
Return type: depthai_sdk.visualize.visualizer.Visualizer

property frame_shape¶

close()¶

class depthai_sdk.XoutFrames(frames, fourcc=None)¶

Bases: depthai_sdk.oak_outputs.xout.xout_base.XoutBase

Stream of frames. Single message, no syncing required.

Methods:

`__init__`(frames[, fourcc])	param frames StreamXout object.
`set_fourcc`(fourcc)
`xstreams`()
`new_msg`(name, msg)
`get_codec`()

__init__(frames, fourcc=None)¶

Parameters

frames (depthai_sdk.oak_outputs.xout.xout_base.StreamXout) – StreamXout object.
fourcc (Optional[str]) – Codec to use for encoding. If None, no encoding will be done.

set_fourcc(fourcc)¶

Parameters: fourcc (str) –
Return type: depthai_sdk.oak_outputs.xout.xout_frames.XoutFrames

xstreams()¶

Return type: List[depthai_sdk.oak_outputs.xout.xout_base.StreamXout]

new_msg(name, msg)¶

Parameters: name (str) –

get_codec()¶

depthai_sdk.cosDist(a, b)¶: Calculates cosine distance - https://en.wikipedia.org/wiki/Cosine_similarity

depthai_sdk.createBlankFrame(width, height, rgb_color=(0, 0, 0))¶

Create new image(numpy array) filled with certain color in RGB

Parameters

width (int) – New frame width
height (int) – New frame height
rgb_color (tuple, Optional) – Specify frame fill color in RGB format (default (0,0,0) - black)

Returns

New frame filled with specified color

Return type

depthai_sdk.cropToAspectRatio(frame, size)¶

Crop the frame to desired aspect ratio and then scales it down to desired size :param frame: Source frame that will be cropped :type frame: numpy.ndarray :param size: Desired frame size (width, height) :type size: tuple

Returns: Cropped frame
Return type: numpy.ndarray

depthai_sdk.dataclass(cls=None, /, *, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False)¶

Returns the same class as was passed in, with dunder methods added based on the fields defined in the class.

Examines PEP 526 __annotations__ to determine fields.

If init is true, an __init__() method is added to the class. If repr is true, a __repr__() method is added. If order is true, rich comparison dunder methods are added. If unsafe_hash is true, a __hash__() method function is added. If frozen is true, fields may not be assigned to after instance creation.

depthai_sdk.downloadContent(url)¶

Parameters: url (str) –
Return type: pathlib.Path

depthai_sdk.downloadRecording(name, keys)¶

Parameters

name (str) –
keys (List[str]) –

Return type

pathlib.Path

depthai_sdk.downloadYTVideo(video, output_dir=None)¶

Downloads a video from YouTube and returns the path to video. Will choose the best resolutuion if possible.

Parameters

video (str) – URL to YouTube video
output_dir (pathlib.Path) – Path to directory where youtube video should be downloaded.

Returns

Path to downloaded video file

Return type

pathlib.Path

Raises

RuntimeError – thrown when video download was unsuccessful

depthai_sdk.field(*, default=<dataclasses._MISSING_TYPE object>, default_factory=<dataclasses._MISSING_TYPE object>, init=True, repr=True, hash=None, compare=True, metadata=None)¶

Return an object to identify dataclass fields.

default is the default value of the field. default_factory is a 0-argument function called to initialize a field’s value. If init is True, the field will be a parameter to the class’s __init__() function. If repr is True, the field will be included in the object’s repr(). If hash is True, the field will be included in the object’s hash(). If compare is True, the field will be used in comparison functions. metadata, if specified, must be a mapping which is stored but not otherwise examined by dataclass.

It is an error to specify both default and default_factory.

depthai_sdk.frameNorm(frame, bbox)¶

Mapps bounding box coordinates (0..1) to pixel values on frame

Parameters

frame (numpy.ndarray) – Frame to which adjust the bounding box
bbox (list) – list of bounding box points in a form of [x1, y1, x2, y2, ...]

Returns

Bounding box points mapped to pixel values on frame

Return type

list

depthai_sdk.getAvailableRecordings()¶

Get available (online) depthai-recordings. Returns list of available recordings and it’s size

Return type: Dict[str, Tuple[List[str], int]]

depthai_sdk.getDeviceInfo(deviceId=None, debug=False)¶

Find a correct depthai.DeviceInfo object, either matching provided deviceId or selected by the user (if multiple devices available) Useful for almost every app where there is a possibility of multiple devices being connected simultaneously

Parameters

deviceId (str, optional) – Specifies device MX ID, for which the device info will be collected

Returns

Object representing selected device info

Return type

depthai.DeviceInfo

Raises

RuntimeError – if no DepthAI device was found or, if deviceId was specified, no device with matching MX ID was found
ValueError – if value supplied by the user when choosing the DepthAI device was incorrect

depthai_sdk.getLocalRecording(recording)¶

Parameters: recording (str) –
Return type: Optional[pathlib.Path]

depthai_sdk.isUrl(source)¶

Parameters: source (Union[str, pathlib.Path]) –
Return type: bool

depthai_sdk.isYoutubeLink(source)¶

Parameters: source (str) –
Return type: bool

depthai_sdk.loadModule(path)¶

Loads module from specified path. Used internally e.g. to load a custom handler file from path

Parameters: path (pathlib.Path) – path to the module to be loaded
Returns: loaded module from provided path
Return type: module

depthai_sdk.merge(source, destination)¶

Utility function to merge two dictionaries

a = { 'first' : { 'all_rows' : { 'pass' : 'dog', 'number' : '1' } } }
b = { 'first' : { 'all_rows' : { 'fail' : 'cat', 'number' : '5' } } }
print(merge(b, a))
# { 'first' : { 'all_rows' : { 'pass' : 'dog', 'fail' : 'cat', 'number' : '5' } } }

Parameters

source (dict) – first dict to merge
destination (dict) – second dict to merge

Returns

merged dict

Return type

dict

depthai_sdk.monotonic() → float ¶: Monotonic clock, cannot go backward.

class depthai_sdk.partial¶

Bases: object

partial(func, *args, **keywords) - new function with partial application of the given arguments and keywords.

Attributes:

`args`	tuple of arguments to future partial calls
`func`	function object to use in future partial calls
`keywords`	dictionary of keyword arguments to future partial calls

args¶: tuple of arguments to future partial calls

func¶: function object to use in future partial calls

keywords¶: dictionary of keyword arguments to future partial calls

depthai_sdk.report_crash_dump(device)¶

Report crash dump to Sentry if sentry is enabled and crash dump is available.

Parameters: device (depthai.Device) – DepthAI device object that will be used to get crash dump.
Return type: None

depthai_sdk.resizeLetterbox(frame, size)¶

Transforms the frame to meet the desired size, preserving the aspect ratio and adding black borders (letterboxing) :param frame: Source frame that will be resized :type frame: numpy.ndarray :param size: Desired frame size (width, height) :type size: tuple

Returns: Resized frame
Return type: numpy.ndarray

depthai_sdk.set_sentry_status(status=True)¶

Set sentry status in config file.

Parameters: status (bool) – True if sentry should be enabled, False otherwise. Default is True.
Returns: None.
Return type: None

depthai_sdk.showProgress(curr, max)¶

Print progressbar to stdout. Each call to this method will write exactly to the same line, so usually it’s used as

print("Staring processing")
while processing:
    showProgress(currProgress, maxProgress)
print(" done") # prints in the same line as progress bar and adds a new line
print("Processing finished!")

Parameters

curr (int) – Current position on progress bar
max (int) – Maximum position on progress bar

depthai_sdk.toPlanar(arr, shape=None)¶

Converts interleaved frame into planar

Parameters

arr (numpy.ndarray) – Interleaved frame
shape (tuple, optional) – If provided, the interleaved frame will be scaled to specified shape before converting into planar

Returns

Planar frame

Return type