viqa.fr_metrics.mad.MAD

class viqa.fr_metrics.mad.MAD(data_range=255, normalize=False, **kwargs)[source]

Class to calculate the most apparent distortion (MAD) between two images.

score_val

MAD score value of the last calculation.

Type:

float

parameters

Dictionary containing the parameters for MAD calculation.

Type:

dict

Parameters:

  • data_range ({1, 255, 65535}, optional) – Data range of the returned data in data loading. Is used for image loading when normalize is True and for the MAD calculation. Passed to viqa.utils.load_data() and viqa.fr_metrics.mad.most_apparent_distortion().

  • normalize (bool, default False) – If True, the input images are normalized to the data_range argument.

  • **kwargs (optional) – Additional parameters for data loading. The keyword arguments are passed to viqa.utils.load_data().

  • chromatic (bool, default False) – If True, the input images are expected to be RGB images. If False, the input images are converted to grayscale images if necessary.

Raises:

ValueError – If data_range is None.

Warning

The metric is not yet validated. Use with caution.

Notes

data_range for image loading is also used for the MAD calculation if the image type is integer and therefore must be set. The parameter is set through the constructor of the class and is passed to __call__(). MAD [1] is a full-reference IQA metric. It is based on the human visual system and is designed to predict the perceived quality of an image.

References

print_score(decimals=2)[source]

Print the MAD score value of the last calculation.

Parameters:

decimals (int, default=2) – Number of decimal places to print the score value.

Warns:

RuntimeWarning – If score_val is not available.

export_results(path, filename)

Export the score to a csv file.

Parameters:

  • path (str) – The path where the csv file should be saved.

  • filename (str) – The name of the csv file.

Notes

The arguments get passed to viqa.utils.export_results().

load_images(img_r, img_m)

Load the images and perform checks.

Parameters:

  • img_r (np.ndarray, viqa.ImageArray, torch.Tensor, str or os.PathLike) – The reference image.

  • img_m (np.ndarray, viqa.ImageArray, torch.Tensor, str or os.PathLike) – The modified image.

Returns:

score(*args, **kwargs)

Calculate the score.

Deprecated since version 3.0.0: Call the metric directly instead, e.g. metric(img_m, img_r). score will be removed in the future. For full-reference metrics.