def apply_quasicrystal(self):
"""
Create a background with quasicrystal (https://en.wikipedia.org/wiki/Quasicrystal)
"""
width = Random.random_int(self._width_range[0], self._width_range[1])
height = Random.random_int(self._height_range[0], self._height_range[1])
image = np.zeros((height, width, 3), dtype=np.uint8)
rotation_count = Random.random_int(10, 20)
y_vec = np.arange(start=0, stop=width, dtype=np.float32)
x_vec = np.arange(start=0, stop=height, dtype=np.float32)
grid = np.meshgrid(y_vec, x_vec)
y_matrix = np.reshape(np.asarray(grid[0]) / (width - 1) * 4 * math.pi - 2 * math.pi, (height, width, 1))
x_matrix = np.reshape(np.asarray(grid[1]) / (height - 1) * 4 * math.pi - 2 * math.pi, (height, width, 1))
y_matrix_3d = np.repeat(y_matrix, rotation_count, axis=-1)
x_matrix_3d = np.repeat(x_matrix, rotation_count, axis=-1)
rotation_vec = np.arange(start=0, stop=rotation_count, dtype=np.float32)
rotation_vec = np.reshape(rotation_vec, newshape=(1, 1, rotation_count))
for k in range(3):
frequency = Random.random_float(0, 1) * 30 + 20 # frequency
phase = Random.random_float(0, 1) * 2 * math.pi # phase
r = np.hypot(x_matrix_3d, y_matrix_3d)
a = np.arctan2(y_matrix_3d, x_matrix_3d) + (rotation_vec * math.pi * 2.0 / rotation_count)
z = np.cos(r * np.sin(a) * frequency + phase)
z = np.sum(z, axis=-1)
c = 255 - np.round(255 * z / rotation_count)
c = np.asarray(c, dtype=np.uint8)
image[:, :, k] = c
return image
def gen_one_box():
l = Random.random_int(0, w)
t = Random.random_int(0, h)
r = int(l + min_w * Random.random_float(1, 3))
b = int(t + min_h * Random.random_float(1, 2))
box = (l, t, r, b)
if r > w or b > h:
return None
return box
def get_fontcolor(self, bg_img):
"""
get font color by mean
:param bg_img:
:return:
"""
char_common_color_list = self.char_common_color_list
if Random.random_float(
0, 1
) <= self.use_char_common_color_probability and char_common_color_list:
return eval(Random.random_choice_list(char_common_color_list))
else:
image = np.asarray(bg_img)
lab_image = cv2.cvtColor(image, cv2.COLOR_RGB2Lab)
bg = lab_image[:, :, 0]
l_mean = np.mean(bg)
new_l = Random.random_int(
0, 127 -
80) if l_mean > 127 else Random.random_int(127 + 80, 255)
new_a = Random.random_int(0, 255)
new_b = Random.random_int(0, 255)
lab_rgb = np.asarray([[[new_l, new_a, new_b]]], np.uint8)
rbg = cv2.cvtColor(lab_rgb, cv2.COLOR_Lab2RGB)
r = rbg[0, 0, 0]
g = rbg[0, 0, 1]
b = rbg[0, 0, 2]
return (r, g, b, 255)
def apply_gauss_blur(self, ks=None):
"""
:param ks: guass kernal window size
:return:
"""
bg_high = Random.random_float(220, 255)
bg_low = bg_high - Random.random_float(1, 60)
width = Random.random_int(self._width_range[0], self._width_range[1])
height = Random.random_int(self._height_range[0], self._height_range[1])
img = np.random.randint(bg_low, bg_high, (height, width)).astype(np.uint8)
if ks is None:
ks = [7, 9, 11, 13]
k_size = Random.random_choice_list(ks)
sigmas = [0, 1, 2, 3, 4, 5, 6, 7]
sigma = 0
if k_size <= 3:
sigma = Random.random_choice_list(sigmas)
img = cv2.GaussianBlur(img, (k_size, k_size), sigma)
return img