from PIL import Image
import numpy as np
a= np.array(Image.open("C:/Users/Jaryn Yang/Pictures/1.jpg"))
b = [255,255 ,255] -a
im = Image.fromarray(b.astype('uint8'))
im.save("C:/Users/Jaryn Yang/Pictures/2.jpg")
convert('L')将彩色图片变为灰度值图片;
手绘图像风格
from PIL import Image
import numpy as np
a= np.array(Image.open("C:/Users/Jaryn Yang/Desktop/1.jpg").convert('L')).astype('float')
depth = 10. #(0-100) 深度值 立体效果
grad = np.gradient(a) #图像灰度的梯度值
grad_x,grad_y = grad #横纵图像的梯度值
grad_x = grad_x*depth/100. #根据深度调整梯度值 除100进行归一化
grad_y = grad_y*depth/100.
A = np.sqrt(grad_x**2+grad_y**2+1)
uni_x = grad_x/A
uni_y = grad_y/A
uni_z = 1./A
vec_el = np.pi/2.2 #光源的俯视角度,弧度值
vec_az = np.pi/4. #光源的方位角度,弧度值
dx = np.cos(vec_el)*np.cos(vec_az) #光源对x轴影响
dy = np.cos(vec_el)*np.sin(vec_az) #y
dz = np.sin(vec_el) #z
b=255*(dx*uni_x+dy*uni_y+dz*uni_z) #梯度变回灰度
b=b.clip(0,255)
im = Image.fromarray(b.astype('uint8')) #重构图像
im.show()
灰度实际上代表图像的明暗变化,梯度表示明暗变化率