# 导入绘图库
from PIL import Image
#导入科学计算库
import numpy as np
#封装一个图像处理工具类
class TestNumpy(object):
def photo2paint(self,img_url):
#读取图片，asarray()转矩阵 convert(‘L‘)转变成像素化 astype()转元素类型
my_photo = np.asarray(Image.open(img_url).convert(‘L‘)).astype(‘float‘)
print(my_photo)
print(my_photo.dtype)
print(my_photo.shape)
print(my_photo.size)
print(‘矩阵是 {} 维度‘.format(my_photo.ndim))
print(‘元素 {} 字节‘.format(my_photo.itemsize))
#设置灰度阈值 范围是(0-100)
depth = 10
#将灰度系数映射到numpy
grad = np.gradient(my_photo)
#获取坐标
grad_x,grad_y = grad
#分别处理，淡化灰度
grad_x = grad_x * depth / 300
grad_y = grad_y * depth / 300
#设置阿尔法值
#设置坐标范围
A = np.sqrt(grad_x**2 + grad_y**2 + 1)
#重新赋值，进行光源化处理，避免像素缺失
uni_x = grad_x/A
uni_y = grad_y/A
uni_z = 1/A
#灰度光源设置 角度/弧度
vec_el = np.pi/2.2
vec_az = np.pi/4
#设置x轴和y轴
dx = np.cos(vec_el) * np.cos(vec_az) #余玄
dy = np.cos(vec_el) * np.sin(vec_az)
#设置z轴
dz = np.sin(vec_el)
#设置byte值
b = 255 * (dx*uni_x+dy*uni_y+dz*uni_z)
#光源归一化
b = b.clip(0,255)
#声明图像类对象
im = Image.fromarray(b.astype(‘uint8‘))
#保存图像
im.save(‘./test_new.jpg‘)
if __name__ == "__main__":
tn = TestNumpy()
tn.photo2paint(‘./test_numpy.jpg‘)
