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bmp2svg.py
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#!/usr/bin/python
# -*- coding: UTF-8 -*-
'''
#apt-get install python-fontforge 字体包 ubuntu
#pip install pypotrace 矢量化potrace
'''
import os
import os.path
from PIL import ImageEnhance
def export(Location, paths, maxWidth, maxHeight):
# Begin SVG Template
write = '<?xml version="1.0" encoding="UTF-8" standalone="no"?>\n'
write += '<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd" >\n'
write += '<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" viewBox="0 0 ' + str(
maxWidth) + ' ' + str(maxHeight) + '">\n'
# write +=' <g transform="matrix(1 0 0 -1 0 819)">\n'
write += ' <g >\n'
write += ' <path fill="currentColor"\n'
write += 'd="'
write += paths
# End SVG Template
write += '"/>\n'
write += '</g>\n'
write += '</svg>'
# Write to file
file = open(Location, "w")
file.write(write)
file.close()
def bim2path(filePath, encoding):
paths = ''
import potrace
import numpy as np
from PIL import Image # #调用库
im = Image.open(filePath).convert('1') # #文件存在的路
if im:
maxWidth = im.size[0]
maxHeight = im.size[1]
data = np.array(im)
# Make a numpy array with a rectangle in the middle
# data = np.zeros ((32, 32), np.uint32)
# data[8:32 - 8, 8:32 - 8] = 1
# Create a bitmap from the array
bmp = potrace.Bitmap(data)
# Trace the bitmap to a path
turdsize = 10 # 通过去除其封闭区域低于给定阈值的所有曲线
# turnpolicy = potrace.TURNPOLICY_BLACK # 连接黑色（前景）组件
alphamax = 25 # 0.5 # 控制跟踪曲线的平滑度。当前默认值为1.0; 此参数的有用范围是从0.0（多边形）到1.3333（无角）。
opticurve = 1 # 通过降低贝塞尔曲线段的数量“简化”的最终曲线的布尔标志。Opticurve = 1打开优化，而opticurve = 0。
opttolerance = 0.2 # 0.1 # 定义误差的允许在这个简化的量。当前默认值为0.2。较大的值倾向于减少段的数量，但代价是精度较低。有用范围是0到无穷大
# turdsize = 10 # 通过去除其封闭区域低于给定阈值的所有曲线
# turnpolicy = potrace.TURNPOLICY_BLACK # 连接黑色（前景）组件
# alphamax = 1.3 # 0.5 # 控制跟踪曲线的平滑度。当前默认值为1.0; 此参数的有用范围是从0.0（多边形）到1.3333（无角）。
# opticurve = 1 # 通过降低贝塞尔曲线段的数量“简化”的最终曲线的布尔标志。Opticurve = 1打开优化，而opticurve = 0。
# opttolerance = 5.0 # 0.1 # 定义误差的允许在这个简化的量。当前默认值为0.2。较大的值倾向于减少段的数量，但代价是精度较低。有用范围是0到无穷大
progress_func = None # 进度条
path = bmp.trace(turdsize=turdsize,
alphamax=alphamax, opticurve=opticurve,
opttolerance=opttolerance)
# Iterate over path curves
i = 0
for curve in path:
i += 1
if i == 1:
continue
paths += ' M ' + '%.2f' % (curve.start_point[0]) + ' ' + '%.2f' % (curve.start_point[1])
for segment in curve:
if segment.is_corner:
end_point_x, end_point_y = segment.end_point
c_x, c_y = segment.c
paths += ' L ' + '%.2f' % (c_x) + ' ' + '%.2f' % (c_y)
paths += ' L ' + '%.2f' % (end_point_x) + ' ' + '%.2f' % (end_point_y)
else:
c1_x, c1_y = segment.c1
c2_x, c2_y = segment.c2
end_point_x, end_point_y = segment.end_point
paths += ' C ' + '%.2f' % (c1_x) + ' %.2f' % (c1_y) + ' %.2f' % (c2_x) + ' %.2f' % (
c2_y) + ' %.2f' % (end_point_x) + ' %.2f' % (end_point_y)
paths += ' Z '
# export('./result/' + encoding + '.svg', paths, maxWidth, maxHeight)
export('./zgd/' + encoding + '.svg', paths, maxWidth, maxHeight)
def generate_svg():
bmpPath = "result_ziti"
print("正在批量生成svg文件...")
list = os.listdir(bmpPath)
for i in range(0, len(list)):
path = os.path.join(bmpPath, list[i])
if os.path.isfile(path):
encoding = list[i].split(".")[0]
bim2path(path, encoding)
print(i)
print("生成完毕")
if __name__ == "__main__":
# 生成单张svg文件到svg_test文件夹，第一个参数是要转化的图片，第二个参数为生成的svg文件名称
bim2path("bmp_test/555.png", "123")
# 若要批量转换图片，则运行此函数，图片都放在batch_bmp中即可
# generate_svg()