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Merge pull request #330 from kwcckw/dev
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Fixed bugs in BrightnessTexturize and updated delaunay.
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@kwcckw
kwcckw authored Jul 27, 2023
2 parents facedd0 + 708d5f2 commit f783430
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Showing 3 changed files with 60 additions and 59 deletions.
10 changes: 7 additions & 3 deletions augraphy/augmentations/brightnesstexturize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,7 @@ def __call__(self, image, layer=None, force=False):
cv2.COLOR_GRAY2BGR,
)
hsv = cv2.cvtColor(bgr, cv2.COLOR_BGR2HSV)

# compute random value
value = random.uniform(self.low, self.high)
# convert to float
Expand All @@ -64,8 +65,10 @@ def __call__(self, image, layer=None, force=False):

# convert back to uint8, apply bitwise not and convert to hsv again
hsv = np.array(hsv, dtype=np.uint8)
hsv = cv2.bitwise_not(hsv)
hsv = np.array(hsv, dtype=np.float64)

# non hue and saturation channel to prevent color change
hsv[:, :, 2] = cv2.bitwise_not(hsv[:, :, 2])
hsv = hsv.astype("float64")

# add noise using deviation again
low_value = value - (value * self.deviation)
Expand All @@ -80,7 +83,8 @@ def __call__(self, image, layer=None, force=False):

# convert back to uint8, apply bitwise not
hsv = np.array(hsv, dtype=np.uint8)
hsv = cv2.bitwise_not(hsv)
# non hue and saturation channel to prevent color change
hsv[:, :, 2] = cv2.bitwise_not(hsv[:, :, 2])

image_output = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)

Expand Down
109 changes: 53 additions & 56 deletions augraphy/augmentations/delaunay.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,8 +33,6 @@
from augraphy.utilities.meshgenerator import Noise
from augraphy.utilities.slidingwindow import PatternMaker

# from scipy.spatial import Delaunay

warnings.filterwarnings("ignore")


Expand All @@ -51,19 +49,23 @@ class DelaunayTessellation(Augmentation):
The Delaunay Condition states that the circumcircle of each triangle in the triangulation must contain no other points in its interior.
The class inherits methods and properties from the Augmentation base class.
:param n_points_range: Range for the number of triangulating points from 500 to 800. Randomly selected.
:type n_points_range: tuple (int), optional
:param n_horizontal_points_range: Range for the number of points in the horizontal edge, from 500 to 800. The value is randomly selected.
:type n_horizontal_points_range: tuple (int), optional
:param n_vertical_points_range: Range for the number of points in the vertical edge, from 500 to 800. The value is randomly selected.
:type n_vertical_points_range: tuple (int), optional
:param noise_type: If "random", integration of Perlin Noise in the pipeline is randomly selected.
If noise_type is "perlin", perlin noise is added to the background pattern,
otherwise no Perlin Noise is added.
Perlin Noise is added to the image to create a smoother, more organic looking tessellation.
If noise_type is "perlin", perlin noise is added to the background pattern,
otherwise no Perlin Noise is added.
Perlin Noise is added to the image to create a smoother, more organic looking tessellation.
:type noise_type: string, optional
:param color_list: A single list contains a collection of colors (in BGR) where the color of the effect will be randomly selected from it.
Use "default" for default color or "random" for random colors.
:type color_list: list, optional
:param color_list_alternate: A single list contains a collection of colors (in BGR) where the alternate color of the effect will be randomly selected from it.
Use "default" for default color or "random" for random colors.
:type color_list_alternate: list, optional
:param p: The probability of applying the augmentation to an input image. Default value is 1.0
:type p: float, optional
Expand All @@ -75,16 +77,20 @@ def __init__(
n_horizontal_points_range=(500, 800),
n_vertical_points_range=(500, 800),
noise_type="random",
color_list="default",
color_list_alternate="default",
p=1,
):
super().__init__(p=p)
self.n_points_range = n_points_range # no. of random points generated on the geometric plane
self.n_horizontal_points_range = n_horizontal_points_range # no. of horizontal edge points
self.n_vertical_points_range = n_vertical_points_range # no. of edge vertical points
self.noise_type = noise_type # apply perlin or not
self.color_list = color_list
self.color_list_alternate = color_list_alternate

def __repr__(self):
return f"Delaunay Tessellation range of random points on geometric plane = {self.n_points_range}, range of horizontal edge points = {self.n_horizontal_points_range}, range of vertical edge points = {self.n_vertical_points_range}, noise_type = {self.noise_type}"
return f"Delaunay Tessellation range of random points on geometric plane = {self.n_points_range}, range of horizontal edge points = {self.n_horizontal_points_range}, range of vertical edge points = {self.n_vertical_points_range}, noise_type = {self.noise_type}, color_list = {self.color_list}, color_list_alternate = {self.color_list_alternate}"

def _edge_points(self, image):
"""
Expand Down Expand Up @@ -137,6 +143,43 @@ def apply_augmentation(self):

triangles = subdiv.getTriangleList()
triangles = triangles.astype(np.int32)

if self.color_list == "default":
colors = [
(250, 235, 215),
(240, 240, 230),
(253, 245, 230),
(255, 245, 238),
(255, 248, 220),
(248, 248, 255),
(255, 240, 245),
(245, 255, 250),
(255, 250, 250),
(240, 248, 255),
(240, 255, 255),
(240, 255, 240),
(255, 245, 238),
(243, 229, 171),
(250, 250, 210),
]
elif self.color_list == "random":
colors = [[random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)] for _ in range(15)]
else:
colors = self.color_list

if self.color_list_alternate == "default":
alt_colors = [
(255, 255, 240),
(255, 250, 205),
(238, 232, 170),
(255, 255, 224),
(255, 239, 213),
]
elif self.color_list_alternate == "random":
alt_colors = [[random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)] for _ in range(5)]
else:
alt_colors = self.color_list_alternate

# adding perlin noise
if self.perlin:
obj_noise = Noise()
Expand All @@ -163,30 +206,7 @@ def apply_augmentation(self):
0,
) # creating a white texture from the perlin noise mesh
img = ndimage.gaussian_filter(img, sigma=(3, 3, 0), order=0) # applying gaussian filter
colors = [
(250, 235, 215),
(240, 240, 230),
(253, 245, 230),
(255, 245, 238),
(255, 248, 220),
(248, 248, 255),
(255, 240, 245),
(245, 255, 250),
(255, 250, 250),
(240, 248, 255),
(240, 255, 255),
(240, 255, 240),
(255, 245, 238),
(243, 229, 171),
(250, 250, 210),
]
alt_colors = [
(255, 255, 240),
(255, 250, 205),
(238, 232, 170),
(255, 255, 224),
(255, 239, 213),
]

img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# Draw the Delaunay triangulation on the empty numpy array

Expand All @@ -213,30 +233,7 @@ def apply_augmentation(self):
pt1 = (t[0], t[1])
pt2 = (t[2], t[3])
pt3 = (t[4], t[5])
colors = [
(250, 235, 215),
(240, 240, 230),
(253, 245, 230),
(255, 245, 238),
(255, 248, 220),
(248, 248, 255),
(255, 240, 245),
(245, 255, 250),
(255, 250, 250),
(240, 248, 255),
(240, 255, 255),
(240, 255, 240),
(255, 245, 238),
(243, 229, 171),
(250, 250, 210),
]
alt_colors = [
(255, 255, 240),
(255, 250, 205),
(238, 232, 170),
(255, 255, 224),
(255, 239, 213),
]

if (
pt1[0]
and pt2[0]
Expand Down
Binary file modified ...source/augmentations/augmentations/brightnesstexturize/brightness_texturize.png
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