>>> from PIL import Image
>>> import numpy as np
>>> a=np.array(Image.open("myLogo.png"))
>>> print (a.shape, a.dtype)
(640, 640, 4) uint8
>>> b=[255,255,255,510]-a
>>> d=Image.fromarray(b.astype("uint8"))
>>> d.save("test.png")
# "L" 表示变为灰度值
>>> s=np.array( Image.open("source2.png").convert("L") )
>>> b=255-s
>>> im = Image.fromarray(b.astype("uint8"))
>>> im.save("test2.jpg")
>>> e = s*(100/255)+150 #区间变换
>>> im3 = Image.fromarray(e.astype("uint8"))
>>> im3.save("test4.jpg")
>>> f=255*(s/255)**2
>>> im4 = Image.fromarray(f.astype("uint8"))
>>> im4.save("test5.jpg")
>>> from PIL import Image
>>> import numpy as np
>>> a=np.asarray(Image.open("source2.png").convert("L").astype("float"))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Image' object has no attribute 'astype'
>>> a=np.asarray(Image.open("source2.png").convert("L")).astype("float")
>>> depth = 10. #(0-100)
>>> grad = np.gradient(a) #取图像灰度梯度值
>>> grad_x, grad_y = grade #分别取横纵图像梯度值
>>> grad_x *= depth/100
>>> 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 轴的影响
>>> dy = np.cos( vec_el)*np.sin(vec_az) #光源对 y 轴的影响
>>> dz = np.sin(vec_el) #光源对 z 轴的影响
>>>
>>> b = 255 * (dx*uni_x + dy*uni_y + dz*uni_z) #光源归一化
>>> b = b.clip(0,255)
>>>
>>> im = Image.fromarray(b.astype("uint8")) #重构图像
>>> im.save("test110.jpg")
>>> import matplotlib.pyplot as plt
>>> import matplotlib
>>>
>>> matplotlib.rcParams['font.family']='SimHei' #黑体
>>> plt.ylabel('纵轴(值)')
>>> plt.savefig('test', dpi=600)
>>> plt.show()
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> a = np.arange(0, 5.0, 0.2)
>>> plt.xlabel('横轴:时间', fontproperties='SimHei', fontsize=20)
>>> plt.ylabel('纵轴:振幅', fontproperties='SimHei', fontsize=20)
>>> plt.plot(a, np.cos(2 * np.pi * a), 'r--')
>>> plt.show()
