def cbad_post_processing_fn(
probs: np.array,
sigma: float = 2.5,
low_threshold: float = 0.8,
high_threshold: float = 0.9,
filter_width: float = 0,
vertical_maxima: bool = False,
output_basename=None) -> Tuple[List[np.ndarray], np.ndarray]:
"""
:param probs: output of the model (probabilities) in range [0, 255]
:param sigma:
:param low_threshold:
:param high_threshold:
:param filter_width:
:param output_basename:
:param vertical_maxima:
:return: contours, mask
WARNING : contours IN OPENCV format List[np.ndarray(n_points, 1, (x,y))]
"""
contours, lines_mask = line_extraction_v1(probs[:, :, 1], sigma,
low_threshold, high_threshold,
filter_width, vertical_maxima)
if output_basename is not None:
dump_pickle(output_basename + '.pkl', (contours, lines_mask.shape))
return contours, lines_mask
def cbad_post_processing_fn(
probs: np.array,
baseline_chanel: int = 1,
sigma: float = 2.5,
low_threshold: float = 0.8,
high_threshold: float = 0.9,
filter_width: float = 0,
vertical_maxima: bool = False,
output_basename=None) -> Tuple[List[np.ndarray], np.ndarray]:
"""
Given a probability map, returns the contour of lines and the corresponding mask.
Saves the results in .pkl file if requested.
:param probs: output of the model (probabilities) in range [0, 255]
:param baseline_chanel: channel where the baseline class is detected
:param sigma: sigma value for gaussian filtering
:param low_threshold: hysteresis low threshold
:param high_threshold: hysteresis high threshold
:param filter_width: percentage of the image width to filter out lines that are close to borders (default 0.0)
:param output_basename: name of file to save the intermediaty result as .pkl file.
:param vertical_maxima: set to True to use vertical local maxima as candidates for the hysteresis thresholding
:return: contours, mask
WARNING : contours IN OPENCV format List[np.ndarray(n_points, 1, (x,y))]
"""
contours, lines_mask = line_extraction_v1(probs[:, :,
baseline_chanel], sigma,
low_threshold, high_threshold,
filter_width, vertical_maxima)
if output_basename is not None:
dump_pickle(output_basename + '.pkl', (contours, lines_mask.shape))
return contours, lines_mask
def cbad_post_processing_fn(probs: np.array, sigma: float=2.5, low_threshold: float=0.8, high_threshold: float=0.9,
filter_width: float=0, output_basename=None):
"""
:param probs: output of the model (probabilities) in range [0, 255]
:param filename: filename of the image processed
:param xml_output_dir: directory to export the resulting PAGE XML
:param upsampled_shape: shape of the original image
:param sigma:
:param low_threshold:
:param high_threshold:
:return: contours, mask
WARNING : contours IN OPENCV format List[np.ndarray(n_points, 1, (x,y))]
"""
contours, lines_mask = line_extraction_v1(probs[:, :, 1], sigma, low_threshold, high_threshold, filter_width)
if output_basename is not None:
dump_pickle(output_basename+'.pkl', (contours, lines_mask.shape))
return contours, lines_mask