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import numpy as np
from PIL import Image
# img = r'C:\Users\Administrator\Desktop\Upload\d825cc1e-6518-afd5-1b02-ed88a7a72806.jpg'
# out_img = r'C:\Users\Administrator\Desktop\Upload\d825cc1e-6518-afd5-1b02-ed88a7a72806_xiangao1.jpg'
img = r ' C: \ Users \ Administrator \ Desktop \ Demo \ demo3_in_out.png '
out_img = r ' C: \ Users \ Administrator \ Desktop \ Demo \ demo3_in_out_f.png '
array = np . asarray ( Image . open ( img ) . convert ( ' L ' ) ) . astype ( np . float64 )
# 根据灰度变化来模拟人类视觉的明暗程度
depth = 10 # 预设虚拟深度值为10 范围为0-100
# 提取x y方向梯度值 解构赋给grad_x, grad_y
grad_x , grad_y = np . gradient ( array )
# 利用像素之间的梯度值和虚拟深度值对图像进行重构
grad_x = grad_x * depth / 100
grad_y = grad_y * depth / 100
# 梯度归一化 定义z深度为1. 将三个梯度绝对值转化为相对值，
dis = np . sqrt ( grad_x * * 2 + grad_y * * 2 + 1.0 )
uni_x = grad_x / dis
uni_y = grad_y / dis
uni_z = 1.0 / dis
# 光源俯视角度和光源方位角度
vec_el = np . pi / 2.2
vec_az = np . pi / 4
# 光源对x、y、z轴的影响
dx = np . cos ( vec_el ) * np . cos ( vec_az )
dy = np . cos ( vec_el ) * np . sin ( vec_az )
dz = np . sin ( vec_el )
# 光源归一化
out = 255 * ( uni_x * dx + uni_y * dy + uni_z * dz )
out = out . clip ( 0 , 255 )
img = Image . fromarray ( out . astype ( np . uint8 ) )
img . save ( out_img )
