Python数据分析与展示：图像的手绘效果-5

图像的RGB色彩模式
red green blue 0-255

图像：由像素组成的二维矩阵，每个元素是一个rgb值

PIL pip install pillow

from PIL from Image

简单实例

为了看到图片效果，代码拆开显示

# -*- coding: utf-8 -*-

# @File    : image_demo.py
# @Date    : 2018-05-06

# pillow 5.1.0 -> 4.0.0

from PIL import Image
import numpy as np

bigsea.jpg

# 读取图片
img = Image.open("images/bigsea.jpg")
print(img)
# 

# 转为多维数组
a = np.array(img)
print(a.shape, a.dtype)
# (750, 1200, 3) uint8

b = [255, 255, 255 ] - a

# 转为图像
im = Image.fromarray(b.astype("uint8"))

# 保存
im.save("images/bigsea1.jpg")

bigsea1.jpg

# 彩色图片转灰色
c = np.array(img.convert("L"))
print(c.shape, c.dtype)
# (750, 1200) uint8

d = 255 - c  # 取反

im2 = Image.fromarray(d.astype("uint8"))

im2.save("images/bigsea2.jpg")

bigsea2.jpg

# 区间变换
e = (100/255)*c + 150  

im3 = Image.fromarray(e.astype("uint8"))

im3.save("images/bigsea3.jpg")

bigsea3.jpg

# 像素平方
f = 255 * (c/255)*2 

im4 = Image.fromarray(f.astype("uint8"))

im4.save("images/bigsea4.jpg")

bigsea4.jpg

图像的手绘效果

# -*- coding: utf-8 -*-

# @File    : 图像手绘效果.py
# @Date    : 2018-05-06

from PIL import Image
import numpy as np

a = np.asarray(Image.open('images/bigsea.jpg').convert('L')).astype('float')

depth = 10.  # (0-100)
grad = np.gradient(a)  # 取图像灰度的梯度值
grad_x, grad_y = grad  # 分别取横纵图像梯度值
grad_x = grad_x * depth / 100.
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('images/beijingHD.jpg')

beijingHD.jpg