Image Property#

Classes:

`ImageProperty`()
`BrightnessProperty`(issue_type)
`AspectRatioProperty`()
`EntropyProperty`()
`BlurrinessProperty`()
`ColorSpaceProperty`()
`SizeProperty`()

Functions:

`calc_avg_brightness`(image)	rtype: `float`
`calculate_brightness`(red, green, blue)	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`
`calc_image_area_sqrt`(image)	rtype: `float`
`get_image_mode`(image)	rtype: `str`

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

Bases: ABC

Attributes:

`name`
`score_columns`

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, issue_type[, threshold])	rtype: `DataFrame`

name: str#

abstract property score_columns: 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, issue_type, threshold=None)[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, green, blue)[source]#

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`

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, issue_type[, threshold])	rtype: `DataFrame`

name: str = 'brightness'#

property score_columns: 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, issue_type, threshold=None)#

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`

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, issue_type[, threshold])	rtype: `DataFrame`

name: str = 'aspect_ratio'#

property score_columns: 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, issue_type, threshold=None)#

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`

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, issue_type[, threshold])	rtype: `DataFrame`

name: str = 'entropy'#

property score_columns: 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, issue_type, threshold=None)#

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`

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, issue_type[, threshold])	rtype: `DataFrame`

name: str = 'blurriness'#

property score_columns: 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, issue_type, threshold=None)#

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

cleanvision.issue_managers.image_property.calc_image_area_sqrt(image)[source]#

Return type:: float

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

Bases: ImageProperty

Attributes:

`name`
`score_columns`

Methods:

`calculate`(image)	rtype: `Dict`[`str`, `Union`[`float`, `str`]]
`get_scores`(raw_scores, issue_type, **kwargs)	rtype: `DataFrame`
`mark_issue`(scores, issue_type[, threshold])	rtype: `DataFrame`
`check_params`(**kwargs)	rtype: `None`

name: str = 'color_space'#

property score_columns: List[str]#

calculate(image)[source]#

Return type:: Dict[str, Union[float, str]]

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

Return type:: DataFrame

mark_issue(scores, issue_type, threshold=None)[source]#

Return type:: DataFrame

static check_params(**kwargs)#

Return type:: None

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

Bases: ImageProperty

Attributes:

`name`
`score_columns`

Methods:

`calculate`(image)	rtype: `Dict`[`str`, `Union`[`float`, `str`]]
`get_scores`(raw_scores, issue_type[, iqr_factor])	rtype: `DataFrame`
`check_params`(**kwargs)	rtype: `None`
`mark_issue`(scores, issue_type[, threshold])	rtype: `DataFrame`

name: str = 'size'#

property score_columns: List[str]#

calculate(image)[source]#

Return type:: Dict[str, Union[float, str]]

get_scores(raw_scores, issue_type, iqr_factor=3.0, **kwargs)[source]#

Return type:: DataFrame

static check_params(**kwargs)#

Return type:: None

mark_issue(scores, issue_type, threshold=None)[source]#

Return type:: DataFrame

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

Return type:: str