def get_projection(self, rows_expected=1):
binary = cv2.adaptiveThreshold(
self.image, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV,
Projection.to_odd(self.get_stroke_width(1) * 2), 5)
# th, binary = cv2.threshold(self.image, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
self.latest_reference_image = binary
binary[binary > 0] = 1
vector = np.sum(binary, axis=1 - self.orientation)
assert len(vector) == self.measurement
return Projection.normalize(vector)
def get_projection(self, rows_expected=1):
binary = cv2.adaptiveThreshold(
self.image,
255,
cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY_INV,
Projection.to_odd(self.get_stroke_width(1) * 2),
5)
# th, binary = cv2.threshold(self.image, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
self.latest_reference_image = binary
binary[binary > 0] = 1
vector = np.sum(binary, axis=1-self.orientation)
assert len(vector) == self.measurement
return Projection.normalize(vector)
def get_projection(self, interpolation_type=cv2.INTER_CUBIC):
"""List of average pixel values along the axis
>>> arr = cv2.imread('assets/img/doctests/digits.jpg', 0)
>>> # horizontal
>>> bins = ColorfulProjection(arr, Projection.TYPE_HORIZONTAL)
>>> bins.get_projection()[3]
0.0043103448275862068
>>> # bins.debug("colorful horizontal")
>>>
>>> # vertical
>>> bins = ColorfulProjection(arr, Projection.TYPE_VERTICAL)
>>> bins.get_projection()[3]
0.047008547008547008
>>> # bins.debug("colorful vertical")
"""
new_shape = (1, self.measurement
) if self.orientation == self.TYPE_HORIZONTAL else (
self.measurement, 1)
vector = cv2.resize(self.image,
new_shape,
interpolation=interpolation_type).flatten()
vector = 255 - vector
assert len(vector) == self.measurement
return Projection.normalize(vector)
def get_projection(self, interpolation_type=cv2.INTER_CUBIC):
"""List of average pixel values along the axis
>>> arr = cv2.imread('assets/img/doctests/digits.jpg', 0)
>>> # horizontal
>>> bins = ColorfulProjection(arr, Projection.TYPE_HORIZONTAL)
>>> bins.get_projection()[3]
0.0043103448275862068
>>> # bins.debug("colorful horizontal")
>>>
>>> # vertical
>>> bins = ColorfulProjection(arr, Projection.TYPE_VERTICAL)
>>> bins.get_projection()[3]
0.047008547008547008
>>> # bins.debug("colorful vertical")
"""
new_shape = (1, self.measurement) if self.orientation == self.TYPE_HORIZONTAL else (self.measurement, 1)
vector = cv2.resize(self.image, new_shape, interpolation=interpolation_type).flatten()
vector = 255 - vector
assert len(vector) == self.measurement
return Projection.normalize(vector)