def moire_fringe(img, degree):
#img = cv2.cvtColor(img.astype(np.uint8), cv2.COLOR_RGB2RGBA).astype(np.uint32)
degree = min(max(degree, 1), 16)
height, width, _ = img.shape
center = height / 2, width / 2
r_idx_array, c_idx_array = np.where(img[:, :, 0] < 256)
r_idx_array = r_idx_array.reshape(height, width)
c_idx_array = c_idx_array.reshape(height, width)
offset_x = r_idx_array - center[0]
offset_y = c_idx_array - center[1]
radian = np.arctan2(offset_y, offset_x)
radius = np.sqrt(offset_x**2 + offset_y**2)
x = radius * np.cos(radian + degree * radius)
y = radius * np.sin(radian + degree * radius)
#不能使用uint
x = np.minimum(np.maximum(x.astype(np.int32), 0), width - 1)
y = np.minimum(np.maximum(y.astype(np.int32), 0), height - 1)
#x = x.flatten()
#y = y.flatten()
dst_img = img[y, x, :]
return inosculate(img, dst_img, 128) # 对生成的图像和源图像进行色彩混合
def magic(bg_img, fg_img, transparency, _contrast):
'''
@效果：将两张图像合成为魔术图
@param bg_img: 背景图像
@param fg_img: 前景图像
@param transparency: 前景透明度 [0, 255]
@param _contrast: 前景图与背景图的对比度[-100, 100]
@return: instance of Image
'''
bg_img = interleaving(bg_img)
bg_img = contrast(bg_img, _contrast)
return inosculate(bg_img, fg_img, transparency)
def magic(bg_img, fg_img, transparency, _contrast):
'''
@效果：将两张图像合成为魔术图
@param bg_img: 背景图像
@param fg_img: 前景图像
@param transparency: 前景透明度 [0, 255]
@param _contrast: 前景图与背景图的对比度[-100, 100]
@return: instance of Image
'''
bg_img = interleaving(bg_img)
bg_img = contrast(bg_img, _contrast)
return inosculate(bg_img, fg_img, transparency)
def moire_fringe(img, degree):
'''
@效果：摩尔纹，对图像进行摩尔纹特效处理
@param img: instance of Image
@param degree: 强度，大小范围[1, 16]
@return: instance of Image
'''
degree = min(max(degree, 1), 16)
if img.mode != "RGBA":
img = img.convert("RGBA")
width, height = img.size
center = width / 2, height / 2 # 中心点
pix = img.load()
dst_img = Image.new("RGBA", (width, height))
dst_pix = dst_img.load()
for w in xrange(width):
for h in xrange(height):
offset_x = w - center[0]
offset_y = h - center[1]
radian = math.atan2(offset_y, offset_x) # 角度
radius = math.sqrt(offset_x ** 2 + offset_y ** 2) # 半径
x = int(radius * math.cos(radian + degree * radius))
y = int(radius * math.sin(radian + degree * radius))
x = min(max(x, 0), width - 1)
y = min(max(y, 0), height - 1)
dst_pix[w, h] = pix[x, y]
return inosculate(img, dst_img, 128) # 对生成的图像和源图像进行色彩混合
