luxonis_ml.data.utils.visualizations

module documentation

Undocumented

Class	`ColorMap`	A mapping that assigns distinct RGB colors to hashable labels.
Function	`add_augmentation_footer`	Append the applied augmentations as a footer below the image.
Function	`append_text_block`	Append a multi-line text block below the image.
Function	`concat_images`	Concatenate images into a single labeled image.
Function	`create_text_image`	Create an image with centered text.
Function	`distinct_color_generator`	Generate distinct RGB colors using the golden ratio.
Function	`draw_bbox_label`	Draw the class name label at the top-left corner of the bounding box.
Function	`draw_cross`	Draw a cross on the image.
Function	`draw_dashed_rectangle`	Draw a dashed rectangle on the image.
Function	`draw_keypoint_label`	Draw a text label next to a keypoint on the image.
Function	`get_contrast_color`	Return a contrasting color for the given RGB color.
Function	`hsv_to_rgb`	Convert an HSV color to RGB.
Function	`resolve_color`	Resolve a color to RGB.
Function	`rgb_to_hsv`	Convert an RGB color to HSV.
Function	`str_to_rgb`	Convert a string to its deterministic RGB color.
Function	`visualize`	Visualize labels on the image.
Function	`wrap_text`	Wrap text into lines that fit within the given width.

def add_augmentation_footer(image: np.ndarray, augmentations: list[str]) -> np.ndarray: ¶

Append the applied augmentations as a footer below the image.

def append_text_block(image: np.ndarray, lines: list[str], font_scale: float, bg_color: Color = (245, 245, 245), text_color: Color = (32, 32, 32)) -> np.ndarray: ¶

Append a multi-line text block below the image.

def concat_images(image_dict: dict[str, np.ndarray], padding: int = 10, label_height: int = 30) -> np.ndarray: ¶

Concatenate images into a single labeled image.

It will attempt to create a square grid of images.

Parameters
image_dict:`dict[str, np.ndarray]`	Mapping of image names to images.
padding:`int`	Padding between images.
label_height:`int`	Height of each label.

Returns
`np.ndarray`	The concatenated image.

def create_text_image(text: str, width: int, height: int, font_size: float = 0.7, bg_color: Color = 255, text_color: Color = 0) -> np.ndarray: ¶

Create an image with centered text.

Parameters
text:`str`	Text to display.
width:`int`	Image width.
height:`int`	Image height.
font_size:`float`	Font size for the text.
bg_color:`Color`	Background color.
text_color:`Color`	Text color.

Returns
`np.ndarray`	The generated image.

def distinct_color_generator(stop: int = -1) -> Generator[RGB, None, None]: ¶

Generate distinct RGB colors using the golden ratio.

This generator produces a sequence of distinct colors in RGB format. The colors are generated by incrementing the hue by the golden ratio and keeping saturation and value fixed. This ensures a wide distribution of visually distinct colors.

Examples

>>> colors = list(distinct_color_generator(stop=2))
>>> len(colors)
2
>>> all(len(color) == 3 for color in colors)
True

Parameters
stop:`int`	optional maximum number of colors to generate. If set to − 1, the generator continues indefinitely.

Returns
`Generator[RGB, None, None]`	Undocumented

Yields
The next RGB color with each component in the range [0, 255].

def draw_bbox_label(image: np.ndarray, class_name: str, box: np.ndarray, color: tuple[int, int, int], font_scale: float): ¶

Draw the class name label at the top-left corner of the bounding box.

Parameters
image:`np.ndarray`	Image to draw on.
class_name:`str`	Name of the class.
box:`np.ndarray`	Bounding box coordinates in `[class_id, x1, y1, x2, y2]` format, where `(x1, y1)` is the top-left corner and `(x2, y2)` is the bottom-right corner.
color:`tuple[int, int, int]`	Label color.
font_scale:`float`	Font scale.

def draw_cross(img: np.ndarray, center: tuple[int, int], size: int = 5, color: Color = 0, thickness: int = 1): ¶

Draw a cross on the image.

Parameters
img:`np.ndarray`	Image to draw on.
center:`tuple[int, int]`	Center of the cross.
size:`int`	Size of the cross.
color:`Color`	Cross color.
thickness:`int`	Line thickness.

def draw_dashed_rectangle(image: np.ndarray, pt1: tuple[int, int], pt2: tuple[int, int], color: Color, thickness: int = 1, dash_length: int = 10): ¶

Draw a dashed rectangle on the image.

Parameters
image:`np.ndarray`	Image to draw on.
pt1:`tuple[int, int]`	Top-left corner of the rectangle.
pt2:`tuple[int, int]`	Bottom-right corner of the rectangle.
color:`Color`	Rectangle color.
thickness:`int`	Line thickness.
dash_length:`int`	Length of each dash.

def draw_keypoint_label(image: np.ndarray, text: str, point: tuple[int, int], size: int, color: tuple[int, int, int], font_scale: float): ¶

Draw a text label next to a keypoint on the image.

Parameters
image:`np.ndarray`	Image to draw on.
text:`str`	Text to draw.
point:`tuple[int, int]`	Keypoint coordinates.
size:`int`	Keypoint size.
color:`tuple[int, int, int]`	Text color.
font_scale:`float`	Font scale.

def get_contrast_color(color: Color) -> RGB: ¶

Return a contrasting color for the given RGB color.

Examples

>>> get_contrast_color((255, 0, 0))
(0, 255, 255)
>>> get_contrast_color(0)
(0, 0, 0)

Parameters
color:`Color`	Color to contrast.

Returns
`RGB`	The contrasting color.

def hsv_to_rgb(color: HSV) -> RGB: ¶

Convert an HSV color to RGB.

Examples

>>> hsv_to_rgb((0, 1, 1))
(255, 0, 0)
>>> hsv_to_rgb((120, 1, 1))
(0, 255, 0)

Parameters
color:`HSV`	HSV color to convert.

Returns
`RGB`	The converted RGB color.

def resolve_color(color: Color) -> RGB: ¶

Resolve a color to RGB.

Examples

>>> resolve_color(12)
(12, 12, 12)
>>> resolve_color((1, 2, 3))
(1, 2, 3)
>>> resolve_color(300)
Traceback (most recent call last):
...
ValueError: Color value 300 is out of range [0, 255]

Parameters
color:`Color`	Color to resolve.

Returns
`RGB`	The resolved RGB color.

Raises
`ValueError`	If an integer channel value is outside [0, 255].

def rgb_to_hsv(color: Color) -> HSV: ¶

Convert an RGB color to HSV.

Examples

>>> tuple(round(v, 3) for v in rgb_to_hsv((255, 0, 0)))
(0.0, 1.0, 1.0)
>>> tuple(round(v, 3) for v in rgb_to_hsv(128))
(0.0, 0.0, 0.502)

Parameters
color:`Color`	Color to convert.

Returns
`HSV`	The converted HSV color.

def str_to_rgb(string: str) -> RGB: ¶

Convert a string to its deterministic RGB color.

Examples

>>> str_to_rgb("car") == str_to_rgb("car")
True
>>> len(str_to_rgb("car"))
3

Parameters
string:`str`	String to convert.

Returns
`RGB`	Deterministic RGB color.

def visualize(image: np.ndarray, source_name: str, labels: Labels, classes: dict[str, dict[str, int]], blend_all: bool = False, categorical_encodings: dict[str, dict[str, int]] | None = None) -> np.ndarray: ¶

Visualize labels on the image.

Parameters
image:`np.ndarray`	Image to visualize.
source_name:`str`	Name of the image source.
labels:`Labels`	Labels to visualize.
classes:`dict[str, dict[str, int]]`	Mapping from task names to class ID mappings.
blend_all:`bool`	Whether to blend all labels into a single image. This mixes labels that belong to different tasks.
categorical_encodings:`dict[str, dict[str, int]] \| None`	optional mapping for categorical metadata tasks. Keys are full task identifiers such as `"task_name/metadata/key"` and values map string labels to encoded integers.

Returns
`np.ndarray`	The visualized image.

def wrap_text(text: str, max_width: int, font_scale: float, thickness: int = 1) -> list[str]: ¶

Wrap text into lines that fit within the given width.