【教学类-102-09】剪纸图案全套代码08——Python点状虚线优化版本03（原图放大白背景）+制作1图2图6图24图

背景需求

前期在“留白边”过程中，发现AI的图片本身很大，顶格，无法实现很宽的描边和点状虚线、也无法让点状虚线与边线保持空隙（留白边），顶格的裁剪会沿线剪不能剪出完整一条（少点纸屑，便于整理）

【教学类-102-08】剪纸图案全套代码08——Python点状虚线优化版本02（有空隙）+制作1图2图6图24图-优快云博客文章浏览阅读746次，点赞15次，收藏6次。【教学类-102-08】剪纸图案全套代码08——Python点状虚线优化版本02（有空隙）+制作1图2图6图24图https://blog.youkuaiyun.com/reasonsummer/article/details/147155698?spm=1011.2415.3001.5331

代码展示

'''
先把255白背景图片背景部分白色放大，然后（蝴蝶)做成透明图，及点状虚线,透明\切边\统一大小,保存1图2图4图24图,虚线与上下左右有空隙
deepseek,阿夏
20250412
'''
from PIL import Image, ImageDraw
import os
import math

print('------0、基本信息-----')
#  主路径b
path = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'
a='11'
b='蝴蝶'

# 白边宽度（像素）
# white_border_width = 20
white_border_width = 40
# 黑点直径（像素）
# dot_size = 10
dot_size = 10
# 黑点间距（像素）
dot_spacing = dot_size * 2  # 增加间距确保均匀分布
# 白色背景放大
# bb=200
bb=3000

# 白边参数设置
transparent_edge = 50  # 裁剪时不保留额外透明边距（这个没有用）
# 图片大小
# target_width = 1400   # 统一宽度
# target_height = 1400  # 统一高度

target_width = 2000   # 统一宽度
target_height = 2000  # 统一高度

# 定义文件夹路径
in_folder = os.path.join(path,f'{a}_01{b}白背景')  # 原始图片（白背景）
big_folder = os.path.join(path, f'{a}_02{b}放大背景')  # 放大背景输出

transparent_folder = os.path.join(path, f'{a}_03{b}透明背景')  # 透明背景输出
output_folder = os.path.join(path, f'{a}_04{b}虚线轮廓')  # 最终输出

input_folder = output_folder  # 原始图片文件夹
cropped_folder = os.path.join(path,f'{a}_05{b}虚线切边') # 裁剪后的透明图片
final=f'{a}_06{b}虚线切边统一图'# 1000*1000统一图
resized_folder = os.path.join(path,f'{final}')

# 创建输出文件夹
os.makedirs(output_folder,exist_ok=True)
os.makedirs(big_folder,exist_ok=True)
os.makedirs(cropped_folder, exist_ok=True)
os.makedirs(resized_folder, exist_ok=True)
os.makedirs(transparent_folder, exist_ok=True)
os.makedirs(output_folder, exist_ok=True)

print('------1、白色PNG背景放大一点-----')
# 遍历输入文件夹中的所有PNG文件
for filename in os.listdir(in_folder):
    if filename.lower().endswith('.png'):
        # 打开原始图片
        input_path = os.path.join(in_folder, filename)
        with Image.open(input_path) as img:
            original_width, original_height = img.size
            
            # 创建新画布（长宽各+200，白色背景）
            new_width = original_width + bb
            new_height = original_height + bb
            new_image = Image.new('RGB', (new_width, new_height), (255, 255, 255))
            
            # 计算粘贴位置（居中）
            paste_x = (new_width - original_width) // 2
            paste_y = (new_height - original_height) // 2
            
            # 将原始图片粘贴到新画布上
            new_image.paste(img, (paste_x, paste_y), img if img.mode == 'RGBA' else None)
            
            # 保存结果
            big_path = os.path.join(big_folder, filename)
            new_image.save(big_path)


print('------2、白色PNG背景变成透明-----')
# 先把图片白色部分变成透明
def process_image_to_transparent(file_path):
    img = Image.open(file_path)
    img = img.convert("RGBA")
    datas = img.getdata()

    new_data = []
    for item in datas:
        if item[0] == 255 and item[1] == 255 and item[2] == 255:
            # 设置为完全透明
            new_data.append((255, 255, 255, 0))
        else:
            new_data.append(item)

    img.putdata(new_data)
    return img

# 第一步：将白背景转为透明背景
print("正在转换白背景为透明背景...")
for file_name in os.listdir(big_folder):
    if file_name.lower().endswith((".png", ".jpg", ".jpeg")):
        input_file_path = os.path.join(big_folder, file_name)
        output_file_path = os.path.join(transparent_folder, file_name)
        processed_image = process_image_to_transparent(input_file_path)
        processed_image.save(output_file_path)
        print(f"已处理: {file_name}")

print('------3、添加点状虚线轮廓-----')

def get_edge_pixels(image):
    """获取图像中不透明像素与透明像素交界的边缘像素坐标"""
    edge_pixels = []
    pixels = image.load()
    width, height = image.size
    
    for y in range(height):
        for x in range(width):
            if pixels[x, y][3] > 0:  # 不透明像素
                # 检查4邻域
                for dx, dy in [(-1,0),(1,0),(0,-1),(0,1)]:
                    nx, ny = x+dx, y+dy
                    if 0 <= nx < width and 0 <= ny < height:
                        if pixels[nx, ny][3] == 0:  # 邻域透明
                            edge_pixels.append((x, y))
                            break
    return edge_pixels

def expand_edge_pixels(edge_pixels, distance, width, height):
    """扩展边缘像素坐标到指定距离"""
    expanded_pixels = set()
    for x, y in edge_pixels:
        for dy in range(-distance, distance+1):
            for dx in range(-distance, distance+1):
                nx, ny = x+dx, y+dy
                if 0 <= nx < width and 0 <= ny < height:
                    expanded_pixels.add((nx, ny))
    return expanded_pixels

def get_contour_pixels(border_pixels, width, height):
    """获取白边区域的外轮廓像素（使用边缘追踪算法）"""
    # 找到起始点（最左上角的边界像素）
    start_point = None
    for y in range(height):
        for x in range(width):
            if (x,y) in border_pixels:
                start_point = (x,y)
                break
        if start_point:
            break
    
    if not start_point:
        return []
    
    # 使用Moore-Neighbor追踪算法获取轮廓
    contour = []
    current = start_point
    previous = (current[0]-1, current[1])  # 假设从左侧开始
    
    directions = [
        (0, -1), (1, -1), (1, 0), (1, 1),
        (0, 1), (-1, 1), (-1, 0), (-1, -1)
    ]
    
    while True:
        contour.append(current)
        # 找到下一个边界点
        found = False
        start_dir = (directions.index((previous[0]-current[0], previous[1]-current[1])) + 1) % 8
        for i in range(8):
            dir_idx = (start_dir + i) % 8
            dx, dy = directions[dir_idx]
            neighbor = (current[0]+dx, current[1]+dy)
            
            if 0 <= neighbor[0] < width and 0 <= neighbor[1] < height:
                if neighbor in border_pixels:
                    previous = current
                    current = neighbor
                    found = True
                    break
        
        if not found or current == start_point:
            break
    
    return contour

def draw_uniform_dots(image, contour, dot_size, dot_spacing):
    """在轮廓上均匀绘制黑点"""
    dot_layer = Image.new('RGBA', image.size, (0, 0, 0, 0))
    draw = ImageDraw.Draw(dot_layer)
    
    if not contour:
        return dot_layer
    
    # 计算轮廓总长度
    total_length = 0
    segments = []
    for i in range(len(contour)):
        p1 = contour[i]
        p2 = contour[(i+1)%len(contour)]
        dx = p2[0] - p1[0]
        dy = p2[1] - p1[1]
        length = math.sqrt(dx*dx + dy*dy)
        segments.append((p1, p2, lengt