利用Python将图片批量转化成素描图的过程记录(光源图片)

正常图片转化成素描图片无非对图片像素的处理，矩阵变化而已。目前很多拍照修图App都有这一功能，核心代码不超30行。如下利用 Python 实现读取一张图片并将其转化成素描图片。至于批处理也简单，循环读取文件夹里的图片处理即可。具体代码可以去我的 GitHub 下载。

程序

Method 1

def plot_sketch(origin_picture, out_picture) :
 a = np.asarray(Image.open(origin_picture).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 + 1.0)
 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(out_picture)
 print("转换成功，请查看 ： ", out_picture)

Method 2

def plot_sketch2(origin_picture, out_picture, alpha=1.0):
 img = Image.open(origin_picture)
 blur = 20
 img1 = img.convert('L')  # 图片转换成灰色
 img2 = img1.copy()
 img2 = ImageOps.invert(img2)
 for i in range(blur):  # 模糊度
  img2 = img2.filter(ImageFilter.BLUR)
 width, height = img1.size
 for x in range(width):
  for y in range(height):
a = img1.getpixel((x, y))
b = img2.getpixel((x, y))
img1.putpixel((x, y), min(int(a*255/(256-b*alpha)), 255))
 img1.save(out_picture)

完整代码

from PIL import Image, ImageFilter, ImageOps
import numpy as np
import os

def plot_sketch(origin_picture, out_picture) :
 a = np.asarray(Image.open(origin_picture).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 + 1.0)
 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(out_picture)
 print("转换成功，请查看 ： ", out_picture)

def plot_sketch2(origin_picture, out_picture, alpha=1.0):
 img = Image.open(origin_picture)
 blur = 20
 img1 = img.convert('L')  # 图片转换成灰色
 img2 = img1.copy()
 img2 = ImageOps.invert(img2)
 for i in range(blur):  # 模糊度
  img2 = img2.filter(ImageFilter.BLUR)
 width, height = img1.size
 for x in range(width):
  for y in range(height):
a = img1.getpixel((x, y))
b = img2.getpixel((x, y))
img1.putpixel((x, y), min(int(a*255/(256-b*alpha)), 255))
 img1.save(out_picture)

if __name__ == '__main__':
 origin_picture = "pictures/5.jpg"
 out_picture = "sketchs/sketch.jpg"
 plot_sketch(origin_picture, out_picture)
 origin_path = "./pictures"
 out_path = "./sketchs"
 dirs = os.listdir(origin_path)
 for file in dirs:
  origin_picture = origin_path + "/" + file
  out_picture = out_path + "/" + "sketch_of_" + file
  plot_sketch2(origin_picture, out_picture)