def process(self, text_arr, bg_arr, min_h):
"""
text_arr : one alpha mask : nxm, uint8
bg_arr : background image: nxmx3, uint8
min_h : height of the smallest character (px)
return text_arr blit onto bg_arr.
"""
# decide on a color for the text:
l_text, fg_col, bg_col = self.color_text(text_arr, min_h, bg_arr)
bg_col = np.mean(np.mean(bg_arr, axis=0), axis=0)
l_bg = Layer(alpha=255 * np.ones_like(text_arr, 'uint8'), color=bg_col)
l_text.alpha = l_text.alpha * np.clip(0.88 + 0.1 * np.random.randn(),
0.72, 1.0)
layers = [l_text]
blends = []
# add border:
if np.random.rand() < self.p_border:
if min_h <= 15: bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
border_a = self.border(l_text.alpha, size=bsz)
l_border = Layer(border_a,
self.color_border(l_text.color, l_bg.color))
layers.append(l_border)
blends.append('normal')
# add shadow:
if np.random.rand() < self.p_drop_shadow:
# shadow gaussian size:
if min_h <= 15: bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
# shadow angle:
theta = np.pi / 4 * np.random.choice([1, 3, 5, 7
]) + 0.5 * np.random.randn()
# shadow shift:
if min_h <= 15: shift = 2
elif 15 < min_h < 30: shift = 7 + np.random.randn()
else: shift = 15 + 3 * np.random.randn()
# opacity:
op = 0.50 + 0.1 * np.random.randn()
shadow = self.drop_shadow(l_text.alpha, theta, shift, 3 * bsz, op)
l_shadow = Layer(shadow, 0)
layers.append(l_shadow)
blends.append('normal')
l_bg = Layer(alpha=255 * np.ones_like(text_arr, 'uint8'), color=bg_col)
layers.append(l_bg)
blends.append('normal')
l_normal = self.merge_down(layers, blends)
# now do poisson image editing:
l_bg = Layer(alpha=255 * np.ones_like(text_arr, 'uint8'), color=bg_arr)
l_out = blit_images(l_normal.color, l_bg.color.copy())
# plt.subplot(1,3,1)
# plt.imshow(l_normal.color)
# plt.subplot(1,3,2)
# plt.imshow(l_bg.color)
# plt.subplot(1,3,3)
# plt.imshow(l_out)
# plt.show()
if l_out is None:
# poisson recontruction produced
# imperceptible text. In this case,
# just do a normal blend:
layers[-1] = l_bg
return self.merge_down(layers, blends).color
return l_out
def process(self, text_arr, bg_arr, min_h):
"""
text_arr : one alpha mask : nxm, uint8
bg_arr : background image: nxmx3, uint8
min_h : height of the smallest character (px)
return text_arr blit onto bg_arr.
"""
# decide on a color for the text:
l_text, fg_col, bg_col = self.color_text(text_arr, min_h, bg_arr)
bg_col = np.mean(np.mean(bg_arr,axis=0),axis=0)
l_bg = Layer(alpha=255*np.ones_like(text_arr,'uint8'),color=bg_col)
l_text.alpha = l_text.alpha * np.clip(0.88 + 0.1*np.random.randn(), 0.72, 1.0)
layers = [l_text]
blends = []
# add border:
if np.random.rand() < self.p_border:
if min_h <= 15 : bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
border_a = self.border(l_text.alpha, size=bsz)
l_border = Layer(border_a, self.color_border(l_text.color,l_bg.color))
layers.append(l_border)
blends.append('normal')
# add shadow:
if np.random.rand() < self.p_drop_shadow:
# shadow gaussian size:
if min_h <= 15 : bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
# shadow angle:
theta = np.pi/4 * np.random.choice([1,3,5,7]) + 0.5*np.random.randn()
# shadow shift:
if min_h <= 15 : shift = 2
elif 15 < min_h < 30: shift = 7+np.random.randn()
else: shift = 15 + 3*np.random.randn()
# opacity:
op = 0.50 + 0.1*np.random.randn()
shadow = self.drop_shadow(l_text.alpha, theta, shift, 3*bsz, op)
l_shadow = Layer(shadow, 0)
layers.append(l_shadow)
blends.append('normal')
l_bg = Layer(alpha=255*np.ones_like(text_arr,'uint8'), color=bg_col)
layers.append(l_bg)
blends.append('normal')
l_normal = self.merge_down(layers,blends)
# now do poisson image editing:
l_bg = Layer(alpha=255*np.ones_like(text_arr,'uint8'), color=bg_arr)
l_out = blit_images(l_normal.color,l_bg.color.copy())
# plt.subplot(1,3,1)
# plt.imshow(l_normal.color)
# plt.subplot(1,3,2)
# plt.imshow(l_bg.color)
# plt.subplot(1,3,3)
# plt.imshow(l_out)
# plt.show()
if l_out is None:
# poisson recontruction produced
# imperceptible text. In this case,
# just do a normal blend:
layers[-1] = l_bg
return self.merge_down(layers,blends).color
return l_out
def process(self, text_arr, bg_arr,light_map, min_h):
"""
text_arr : one alpha mask : nxm, uint8
bg_arr : background image: nxmx3, uint8
min_h : height of the smallest character (px)
return text_arr blit onto bg_arr.
"""
# decide on a color for the text:
l_text, fg_col, bg_col = self.color_text(text_arr, min_h, bg_arr)
print(fg_col,bg_col)
bg_col = np.mean(np.mean(bg_arr,axis=0),axis=0)
l_bg = Layer(alpha=255*np.ones_like(text_arr,'uint8'),color=bg_col)
l_text.alpha = l_text.alpha * np.clip(0.92 + 0.1*np.random.randn(), 0.72, 1.0)
#print(np.max(l_text.alpha))
layers = [l_text]
blends = []
# add border:
if np.random.rand() < self.p_border:
if min_h <= 15 : bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
border_a = self.border(l_text.alpha, size=bsz)
l_border = Layer(border_a, self.color_border(l_text.color,l_bg.color))
layers.append(l_border)
blends.append('normal')
# add shadow:
if np.random.rand() < self.p_drop_shadow:
# shadow gaussian size:
if min_h <= 15 : bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
# shadow angle:
theta = np.pi/4 * np.random.choice([1,3,5,7]) + 0.5*np.random.randn()
# shadow shift:
if min_h <= 15 : shift = 2
elif 15 < min_h < 30: shift = 7+np.random.randn()
else: shift = 15 + 3*np.random.randn()
# opacity:
op = 0.50 + 0.1*np.random.randn()
shadow = self.drop_shadow(l_text.alpha, theta, shift, 3*bsz, op)
l_shadow = Layer(shadow, 0)
layers.append(l_shadow)
blends.append('normal')
l_bg = Layer(alpha=255*np.ones_like(text_arr,'uint8'), color=bg_col)
layers.append(l_bg)
blends.append('normal')
l_normal = self.merge_down(layers,blends)
# now do poisson image editing:
l_bg = Layer(alpha=255*np.ones_like(text_arr,'uint8'), color=bg_arr)
#print(text_arr.shape)
#txt = np.concatenate((l_normal.color, l_normal.alpha.reshape(l_normal.alpha.shape[0],l_normal.alpha.shape[1],1)),axis=2)
#txt = l_bg.color[text_arr]
l_out = blit_images(l_normal.color,l_bg.color.copy())
#l_out = l_out[text_arr]
# plt.subplot(1,3,1)
# plt.imshow(l_normal.color)
# plt.subplot(1,3,2)
# plt.imshow(l_bg.color)
# plt.subplot(1,3,3)
# plt.imshow(l_out)
# plt.show()
if l_out is None:
# poisson recontruction produced
# imperceptible text. In this case,
# just do a normal blend:
layers[-1] = l_bg
return self.merge_down(layers,blends).color
'''for i in range(l_out.shape[0]):
for j in range(l_out.shape[1]):
l_out[i][j][:] = (text_arr[i][j] > 0)*l_out[i][j][:]'''
#l_out = np.concatenate((l_out, (255*text_arr).reshape(text_arr.shape[0],text_arr.shape[1],1)),axis=-1)
#l_out = np.concatenate((l_out, (text_arr.shape[0],text_arr.shape[1],1)),axis=-1)
l_out_4d = np.zeros((l_out.shape[0], l_out.shape[1],4))
l_out_4d[:,:,:3]= l_out
l_out_4d[:,:,3] = text_arr#255*np.ones((l_out.shape[0], l_out.shape[1]))#text_arr
cv.imwrite("test.png",l_out_4d)
#l_out_4d /= 255
plt.imshow(cv.cvtColor(bg_arr,cv.COLOR_BGR2RGB))
plt.show()
plt.imshow(text_arr, cmap='binary')
plt.show()
plt.imshow(l_out_4d/255)
plt.title("l_out_4d")
plt.show()
return l_out_4d
def process(self, text_arr, bg_arr, min_h):
"""
text_arr : one alpha mask : nxm, uint8
bg_arr : background image: nxmx3, uint8
min_h : height of the smallest character (px)
return text_arr blit onto bg_arr.
text_arr: одна альфа-маска: nxm, uint8
bg_arr: фоновое изображение: nxmx3, uint8
min_h: высота самого маленького символа (px)
вернуть text_arr blit на bg_arr.
"""
# decide on a color for the text:
# выбрать цвет для текста:
l_text, fg_col, bg_col = self.color_text(text_arr, min_h, bg_arr)
bg_col = np.mean(np.mean(bg_arr, axis=0), axis=0)
l_bg = Layer(alpha=255 * np.ones_like(text_arr, 'uint8'), color=bg_col)
l_text.alpha = l_text.alpha * np.clip(0.88 + 0.1 * np.random.randn(),
0.72, 1.0)
layers = [l_text]
blends = []
# add border:
# добавить границу:
if np.random.rand() < self.p_border:
if min_h <= 15: bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
border_a = self.border(l_text.alpha, size=bsz)
l_border = Layer(border_a,
self.color_border(l_text.color, l_bg.color))
layers.append(l_border)
blends.append('normal')
# add shadow:
# добавить тень:
if np.random.rand() < self.p_drop_shadow:
# shadow gaussian size:
# теневой размер по Гауссу:
if min_h <= 15: bsz = 1
elif 15 < min_h < 30: bsz = 3
else: bsz = 5
# shadow angle:
# угол тени:
theta = np.pi / 4 * np.random.choice([1, 3, 5, 7
]) + 0.5 * np.random.randn()
# shadow shift:
# теневой сдвиг:
if min_h <= 15: shift = 2
elif 15 < min_h < 30: shift = 7 + np.random.randn()
else: shift = 15 + 3 * np.random.randn()
# opacity:
# непрозрачность:
op = 0.50 + 0.1 * np.random.randn()
shadow = self.drop_shadow(l_text.alpha, theta, shift, 3 * bsz, op)
l_shadow = Layer(shadow, 0)
layers.append(l_shadow)
blends.append('normal')
l_bg = Layer(alpha=255 * np.ones_like(text_arr, 'uint8'), color=bg_col)
layers.append(l_bg)
blends.append('normal')
l_normal = self.merge_down(layers, blends)
# now do poisson image editing:
# теперь выполняем редактирование пуассоновских изображений:
l_bg = Layer(alpha=255 * np.ones_like(text_arr, 'uint8'), color=bg_arr)
l_out = blit_images(l_normal.color, l_bg.color.copy())
# plt.subplot(1,3,1)
# plt.imshow(l_normal.color)
# plt.subplot(1,3,2)
# plt.imshow(l_bg.color)
# plt.subplot(1,3,3)
# plt.imshow(l_out)
# plt.show()
if l_out is None:
# poisson recontruction produced
# imperceptible text. In this case,
# just do a normal blend:
# Пуассоново восстановление произведено # незаметный текст. В этом случае,
# просто сделайте нормальное смешивание:
layers[-1] = l_bg
return self.merge_down(layers, blends).color
return l_out
