这篇教程利用Python将图片批量转化成素描图的过程记录写得很实用，希望能帮到您。
前言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 1def 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 2def 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, ImageOpsimport numpy as npimport osdef 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)
结果
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