Image Property#

Classes:

ImageProperty()

BrightnessProperty(issue_type)

AspectRatioProperty()

EntropyProperty()

BlurrinessProperty()

ColorSpaceProperty()

Functions:

calc_avg_brightness(image)

rtype:

float

calculate_brightness()

rtype:

Union[float, ndarray[Any, Any]]

calc_percentile_brightness(image, percentiles)

rtype:

ndarray[Any, Any]

calc_aspect_ratio(image)

rtype:

float

calc_entropy(image)

rtype:

float

calc_blurriness(gray_image)

rtype:

float

calc_std_grayscale(gray_image)

rtype:

float

get_edges(gray_image)

rtype:

Image

calc_color_space(image)

rtype:

str

get_image_mode(image)

rtype:

str
class cleanvision.issue_managers.image_property.ImageProperty[source]#

Bases: ABC

Attributes:

name

score_columns

rtype:

List[str]

Methods:

check_params(**kwargs)

rtype:

None

calculate(image)

rtype:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)

rtype:

Any

mark_issue(scores, threshold, issue_type)

rtype:

DataFrame
name: str#
abstract property score_columns: List[str]#
Return type:

List[str]

static check_params(**kwargs)[source]#
Return type:

None

abstract calculate(image)[source]#
Return type:

Dict[str, Union[float, str]]

abstract get_scores(raw_scores, issue_type, **kwargs)[source]#
Return type:

Any

mark_issue(scores, threshold, issue_type)[source]#
Return type:

DataFrame

cleanvision.issue_managers.image_property.calc_avg_brightness(image)[source]#
Return type:

float

cleanvision.issue_managers.image_property.calculate_brightness(red: float, green: float, blue: float) → float[source]#
cleanvision.issue_managers.image_property.calculate_brightness(red: ndarray[Any, Any], green: ndarray[Any, Any], blue: ndarray[Any, Any]) → ndarray[Any, Any]
Return type:

Union[float, ndarray[Any, Any]]

cleanvision.issue_managers.image_property.calc_percentile_brightness(image, percentiles)[source]#
Return type:

ndarray[Any, Any]

class cleanvision.issue_managers.image_property.BrightnessProperty(issue_type)[source]#

Bases: ImageProperty

Attributes:

name

score_columns

rtype:

List[str]

Methods:

calculate(image)

rtype:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)

rtype:

DataFrame

check_params(**kwargs)

rtype:

None

mark_issue(scores, threshold, issue_type)

rtype:

DataFrame
name: str = 'brightness'#
property score_columns: List[str]#
Return type:

List[str]

calculate(image)[source]#
Return type:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)[source]#
Return type:

DataFrame

static check_params(**kwargs)#
Return type:

None

mark_issue(scores, threshold, issue_type)#
Return type:

DataFrame

cleanvision.issue_managers.image_property.calc_aspect_ratio(image)[source]#
Return type:

float

class cleanvision.issue_managers.image_property.AspectRatioProperty[source]#

Bases: ImageProperty

Attributes:

name

score_columns

rtype:

List[str]

Methods:

calculate(image)

rtype:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)

rtype:

DataFrame

check_params(**kwargs)

rtype:

None

mark_issue(scores, threshold, issue_type)

rtype:

DataFrame
name: str = 'aspect_ratio'#
property score_columns: List[str]#
Return type:

List[str]

calculate(image)[source]#
Return type:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)[source]#
Return type:

DataFrame

static check_params(**kwargs)#
Return type:

None

mark_issue(scores, threshold, issue_type)#
Return type:

DataFrame

cleanvision.issue_managers.image_property.calc_entropy(image)[source]#
Return type:

float

class cleanvision.issue_managers.image_property.EntropyProperty[source]#

Bases: ImageProperty

Attributes:

name

score_columns

rtype:

List[str]

Methods:

calculate(image)

rtype:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type[, ...])

rtype:

DataFrame

check_params(**kwargs)

rtype:

None

mark_issue(scores, threshold, issue_type)

rtype:

DataFrame
name: str = 'entropy'#
property score_columns: List[str]#
Return type:

List[str]

calculate(image)[source]#
Return type:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, normalizing_factor=1.0, **kwargs)[source]#
Return type:

DataFrame

static check_params(**kwargs)#
Return type:

None

mark_issue(scores, threshold, issue_type)#
Return type:

DataFrame

cleanvision.issue_managers.image_property.calc_blurriness(gray_image)[source]#
Return type:

float

cleanvision.issue_managers.image_property.calc_std_grayscale(gray_image)[source]#
Return type:

float

class cleanvision.issue_managers.image_property.BlurrinessProperty[source]#

Bases: ImageProperty

Attributes:

name

score_columns

rtype:

List[str]

Methods:

calculate(image)

rtype:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type[, ...])

rtype:

DataFrame

check_params(**kwargs)

rtype:

None

mark_issue(scores, threshold, issue_type)

rtype:

DataFrame
name: str = 'blurriness'#
property score_columns: List[str]#
Return type:

List[str]

calculate(image)[source]#
Return type:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, normalizing_factor=1.0, color_threshold=1.0, **kwargs)[source]#
Return type:

DataFrame

static check_params(**kwargs)#
Return type:

None

mark_issue(scores, threshold, issue_type)#
Return type:

DataFrame

cleanvision.issue_managers.image_property.get_edges(gray_image)[source]#
Return type:

Image

cleanvision.issue_managers.image_property.calc_color_space(image)[source]#
Return type:

str

class cleanvision.issue_managers.image_property.ColorSpaceProperty[source]#

Bases: ImageProperty

Attributes:

name

score_columns

rtype:

List[str]

Methods:

calculate(image)

rtype:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)

rtype:

DataFrame

check_params(**kwargs)

rtype:

None

mark_issue(scores, threshold, issue_type)

rtype:

DataFrame
name: str = 'color_space'#
property score_columns: List[str]#
Return type:

List[str]

calculate(image)[source]#
Return type:

Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, **kwargs)[source]#
Return type:

DataFrame

static check_params(**kwargs)#
Return type:

None

mark_issue(scores, threshold, issue_type)[source]#
Return type:

DataFrame

cleanvision.issue_managers.image_property.get_image_mode(image)[source]#
Return type:

str