nabu.stitching.sample_normalization
[docs]
module
nabu.stitching.sample_normalization
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60 | from enum import Enum
import numpy
class SampleSide(Enum):
LEFT = "left"
RIGHT = "right"
class Method(Enum):
MEAN = "mean"
MEDIAN = "median"
def normalize_frame(
frame: numpy.ndarray, side: SampleSide, method: Method, sample_width: int = 50, margin_before_sample: int = 0
):
"""
normalize the frame from a sample section picked at the left of the right of the frame
:param frame: frame to normalize
:param SampleSide side: side to pick the sample
:param Method method: normalization method
:param int sample_width: sample width
:param int margin: margin before the sampling area
"""
if not isinstance(frame, numpy.ndarray):
raise TypeError(f"Frame is expected to be a 2D numpy array.")
if frame.ndim != 2:
raise TypeError(f"Frame is expected to be a 2D numpy array. Get {frame.ndim}D")
side = SampleSide(side)
method = Method(method)
if frame.shape[1] < sample_width + margin_before_sample:
raise ValueError(
f"frame width ({frame.shape[1]}) < sample_width + margin ({sample_width + margin_before_sample})"
)
# create sample
if side is SampleSide.LEFT:
sample_start = margin_before_sample
sample_end = margin_before_sample + sample_width
sample = frame[:, sample_start:sample_end]
elif side is SampleSide.RIGHT:
sample_start = frame.shape[1] - (sample_width + margin_before_sample)
sample_end = frame.shape[1] - margin_before_sample
sample = frame[:, sample_start:sample_end]
else:
raise ValueError(f"side {side.value} not handled")
# do normalization
if method is Method.MEAN:
normalization_array = numpy.mean(sample, axis=1)
elif method is Method.MEDIAN:
normalization_array = numpy.median(sample, axis=1)
else:
raise ValueError(f"side {side.value} not handled")
for line in range(normalization_array.shape[0]):
frame[line, :] -= normalization_array[line]
return frame
|