学校网站建设过程嘉兴网站建设制作
背景需求
前期用青蛙PNG图片做了点状边框
【教学类-102-03】自制剪纸图案（留白边、沿线剪）03——Python制作白色描边和黑点虚线间隔（透明png图片）-CSDN博客文章浏览阅读898次，点赞39次，收藏3次。【教学类-102-03】自制剪纸图案（留白边、沿线剪）03——Python制作白色描边和黑点虚线间隔（透明png图片）https://blog.csdn.net/reasonsummer/article/details/147002991?spm=1011.2415.3001.5331
【教学类-102-04】自制剪纸图案（留白边、沿线剪）04——Python制作白色描边和黑线虚线间隔（透明png图片）-CSDN博客文章浏览阅读350次，点赞10次，收藏2次。【教学类-102-04】自制剪纸图案（留白边、沿线剪）04——Python制作白色描边和黑线虚线间隔（透明png图片）https://blog.csdn.net/reasonsummer/article/details/147022408?spm=1011.2415.3001.5331
但是我前期大部分图片都是用PS填充（255,255,255）白色背景，并没有把背景变成PNG透明。
因此需要
1、先识别255,255,255的图像坐标（10-01）
2、把255,255,255的地方改成透明色"RGBA"（10-02）
3、根据透明部分与非透明部分交界线，添加点状虚线（10-03）或线状虚线（10-04）。
代码一：点状虚线
'''
先把白色背景改成透明，然后在添加点状虚线
剪纸外轮廓描边虚线点制作（黑点）沿线剪——平均边缘点子的距离（最终效果）
deepseek 阿夏
20250407
'''from PIL import Image, ImageDraw
import os
import math# 先把图片被色部分变成透明'''图片透明
'''
from PIL import Image
import osdef process_image(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:# 红色new_data.append((255, 0, 0, 0))else:new_data.append(item)img.putdata(new_data)return imgpath = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'
in_folder = path+r'\10_01蛋糕白背景'
input_folder = path+r'\10_02蛋糕透明背景'
os.makedirs(input_folder,exist_ok=True)for file_name in os.listdir(in_folder):if file_name.endswith(".png") or file_name.endswith(".jpg") or file_name.endswith(".jpeg"):input_file_path = os.path.join(in_folder, file_name)input_file_path = os.path.join(input_folder, file_name)processed_image = process_image(input_file_path)processed_image.save(input_file_path)# 搜索变# 白边宽度（像素）
white_border_width = 30
# 黑点直径（像素）
dot_size = 10
# 黑点间距（像素）
dot_spacing = dot_size*2 # 增加间距确保均匀分布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.sizefor 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+dyif 0 <= nx < width and 0 <= ny < height:if pixels[nx, ny][3] == 0: # 邻域透明edge_pixels.append((x, y))breakreturn edge_pixelsdef 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+dyif 0 <= nx < width and 0 <= ny < height:expanded_pixels.add((nx, ny))return expanded_pixelsdef 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 = Nonefor y in range(height):for x in range(width):if (x,y) in border_pixels:start_point = (x,y)breakif start_point:breakif not start_point:return []# 使用Moore-Neighbor追踪算法获取轮廓contour = []current = start_pointprevious = (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 = Falsestart_dir = (directions.index((previous[0]-current[0], previous[1]-current[1])) + 1) % 8for i in range(8):dir_idx = (start_dir + i) % 8dx, 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 = currentcurrent = neighborfound = Truebreakif not found or current == start_point:breakreturn contourdef 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 = 0segments = []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, length))total_length += length# 计算需要绘制的点数num_dots = int(total_length / dot_spacing)if num_dots == 0:num_dots = 1# 均匀分布点step = total_length / num_dotscurrent_dist = 0segment_idx = 0remaining_seg = segments[0][2]for _ in range(num_dots):# 找到当前点所在线段while current_dist > remaining_seg and segment_idx < len(segments)-1:current_dist -= remaining_segsegment_idx += 1remaining_seg = segments[segment_idx][2]p1, p2, seg_len = segments[segment_idx]ratio = current_dist / seg_lenx = p1[0] + ratio * (p2[0] - p1[0])y = p1[1] + ratio * (p2[1] - p1[1])# 绘制黑点draw.ellipse([(x - dot_size/2, y - dot_size/2),(x + dot_size/2, y + dot_size/2)], fill=(0, 0, 0, 255))current_dist += stepreturn dot_layerdef process_image(input_path, output_path):"""处理单个图像"""original = Image.open(input_path).convert('RGBA')original_copy = original.copy()width, height = original.size# 获取边缘并扩展白边edge_pixels = get_edge_pixels(original)border_pixels = expand_edge_pixels(edge_pixels, white_border_width, width, height)# 获取精确的外轮廓contour = get_contour_pixels(border_pixels, width, height)# 创建白边图层white_border = Image.new('RGBA', (width, height), (255, 255, 255, 255))mask = Image.new('L', (width, height), 0)mask_pixels = mask.load()for x, y in border_pixels:mask_pixels[x, y] = 255white_border.putalpha(mask)# 合成白边result = Image.alpha_composite(original, white_border)# 绘制均匀分布的黑点dot_layer = draw_uniform_dots(original, contour, dot_size, dot_spacing)result = Image.alpha_composite(result, dot_layer)# 覆盖原始图像result = Image.alpha_composite(result, original_copy)result.save(output_path, format='PNG')print(f"Processed: {os.path.basename(input_path)}")def process_images(input_folder, output_folder):"""批量处理图像"""if not os.path.exists(output_folder):os.makedirs(output_folder)for filename in os.listdir(input_folder):if filename.lower().endswith('.png'):input_path = os.path.join(input_folder, filename)output_path = os.path.join(output_folder, filename)process_image(input_path, output_path)if __name__ == '__main__':path = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'# input_folder = os.path.join(path, '10 蛋糕白背景')output_folder = os.path.join(path, '10_03蛋糕点虚线')process_images(input_folder, output_folder)效果图：
代码；2：线条虚线
'''
先把白色背景改成透明，然后在添加线条虚线
剪纸外轮廓描边虚线点制作（黑点）沿线剪——平均边缘点子的距离（最终效果）
deepseek 阿夏
20250407
'''
'''
剪纸外轮廓描边虚线制作（黑色虚线）沿线剪——最终稳定版
确保显示虚线边框且无多余连接线
'''from PIL import Image, ImageDraw
import os
import math
import numpy as np# 图片透明
from PIL import Image
import osdef process_image(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:# 红色new_data.append((255, 0, 0, 0))else:new_data.append(item)img.putdata(new_data)return imgpath = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'
in_folder = path+r'\10_01蛋糕白背景'
input_folder = path+r'\10_02蛋糕透明背景'
os.makedirs(input_folder,exist_ok=True)for file_name in os.listdir(in_folder):if file_name.endswith(".png") or file_name.endswith(".jpg") or file_name.endswith(".jpeg"):input_file_path = os.path.join(in_folder, file_name)input_file_path = os.path.join(input_folder, file_name)processed_image = process_image(input_file_path)processed_image.save(input_file_path)# 白边宽度（像素）
white_border_width = 20
# 虚线参数
dash_length = 20 # 每段虚线长度（像素）
dash_gap = 20 # 虚线间距（像素）
dash_width = 10 # 虚线粗细（像素）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 = set()pixels = image.load()width, height = image.sizefor y in range(height):for x in range(width):if pixels[x, y][3] > 0: # 不透明像素# 检查8邻域for dx, dy in [(-1,-1),(-1,0),(-1,1),(0,-1),(0,1),(1,-1),(1,0),(1,1)]:nx, ny = x+dx, y+dyif 0 <= nx < width and 0 <= ny < height:if pixels[nx, ny][3] == 0: # 邻域透明edge_pixels.add((x, y))breakreturn list(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+dyif 0 <= nx < width and 0 <= ny < height:expanded_pixels.add((nx, ny))return expanded_pixelsdef get_contour_pixels(border_pixels, width, height):"""获取白边区域的外轮廓像素（确保完整轮廓）"""# 创建一个二维数组来标记边界像素border_map = np.zeros((height, width), dtype=bool)for x, y in border_pixels:border_map[y, x] = True# 找到起始点（最左上角的边界像素）start_point = Nonefor y in range(height):for x in range(width):if border_map[y, x]:start_point = (x, y)breakif start_point:breakif not start_point:return []# 使用改进的Moore-Neighbor追踪算法contour = []current = start_pointprevious = (current[0]-1, current[1]) # 假设从左侧开始# 8邻域方向定义（顺时针顺序）directions = [(0, -1), (1, -1), (1, 0), (1, 1),(0, 1), (-1, 1), (-1, 0), (-1, -1)]# 追踪完整轮廓max_iterations = width * height * 2 # 防止无限循环iterations = 0while iterations < max_iterations:iterations += 1contour.append(current)# 找到下一个边界点found = Falsestart_dir = (directions.index((previous[0]-current[0], previous[1]-current[1])) + 1) % 8for i in range(8):dir_idx = (start_dir + i) % 8dx, dy = directions[dir_idx]neighbor = (current[0]+dx, current[1]+dy)if 0 <= neighbor[0] < width and 0 <= neighbor[1] < height:if border_map[neighbor[1], neighbor[0]]:# 检查是否回到了起点（完成一个完整轮廓）if neighbor == start_point and len(contour) > 3:return contour # 返回完整闭合轮廓previous = currentcurrent = neighborfound = Truebreakif not found:break # 无法找到下一个点return contourdef draw_uniform_dashes(image, contour, dash_length, dash_gap, dash_width):"""在轮廓上均匀绘制黑色虚线（正确处理闭合轮廓）"""dash_layer = Image.new('RGBA', image.size, (0, 0, 0, 0))draw = ImageDraw.Draw(dash_layer)if len(contour) < 2:return dash_layer# 计算轮廓总长度（包括闭合段）total_length = 0segments = []# 添加所有线段（包括最后一段连接起点和终点的线段）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, length))total_length += lengthif total_length == 0:return dash_layer# 计算虚线周期长度dash_cycle = dash_length + dash_gap# 计算需要绘制的虚线数量num_dashes = int(total_length / dash_cycle)if num_dashes == 0:num_dashes = 1# 均匀分布虚线current_pos = 0segment_idx = 0remaining_seg = segments[0][2]while current_pos < total_length and segment_idx < len(segments):# 找到当前虚线起点所在线段while current_pos > remaining_seg and segment_idx < len(segments)-1:current_pos -= remaining_segsegment_idx += 1remaining_seg = segments[segment_idx][2]# 计算虚线起点坐标p1, p2, seg_len = segments[segment_idx]ratio = min(current_pos / seg_len, 1.0) # 确保不超过1start_x = p1[0] + ratio * (p2[0] - p1[0])start_y = p1[1] + ratio * (p2[1] - p1[1])# 计算虚线终点位置end_pos = min(current_pos + dash_length, total_length)# 绘制虚线（可能跨越多个线段）remaining_dash = dash_lengthcurrent_seg = segment_idxcurrent_ratio = ratiopoints = [(start_x, start_y)]while remaining_dash > 0 and current_seg < len(segments):p1, p2, seg_len = segments[current_seg]available = seg_len * (1 - current_ratio) if current_seg == segment_idx else seg_lenif remaining_dash <= available:# 虚线终点在当前线段内end_ratio = current_ratio + remaining_dash / seg_lenend_x = p1[0] + end_ratio * (p2[0] - p1[0])end_y = p1[1] + end_ratio * (p2[1] - p1[1])points.append((end_x, end_y))breakelse:# 虚线延伸到下一线段points.append((p2[0], p2[1]))remaining_dash -= availablecurrent_seg += 1current_ratio = 0# 绘制虚线（确保至少有两个点）if len(points) > 1:draw.line(points, fill=(0, 0, 0, 255), width=dash_width)# 移动到下一个虚线起点current_pos += dash_cyclereturn dash_layerdef process_image(input_path, output_path):"""处理单个图像"""original = Image.open(input_path).convert('RGBA')original_copy = original.copy()width, height = original.size# 获取边缘并扩展白边edge_pixels = get_edge_pixels(original)border_pixels = expand_edge_pixels(edge_pixels, white_border_width, width, height)# 获取精确的外轮廓contour = get_contour_pixels(border_pixels, width, height)# 创建白边图层white_border = Image.new('RGBA', (width, height), (255, 255, 255, 255))mask = Image.new('L', (width, height), 0)mask_pixels = mask.load()for x, y in border_pixels:mask_pixels[x, y] = 255white_border.putalpha(mask)# 合成白边result = Image.alpha_composite(original, white_border)# 绘制均匀分布的黑色虚线dash_layer = draw_uniform_dashes(original, contour, dash_length, dash_gap, dash_width)result = Image.alpha_composite(result, dash_layer)# 覆盖原始图像result = Image.alpha_composite(result, original_copy)result.save(output_path, format='PNG')print(f"Processed: {os.path.basename(input_path)}")def process_images(input_folder, output_folder):"""批量处理图像"""if not os.path.exists(output_folder):os.makedirs(output_folder)for filename in os.listdir(input_folder):if filename.lower().endswith('.png'):input_path = os.path.join(input_folder, filename)output_path = os.path.join(output_folder, filename)process_image(input_path, output_path)if __name__ == '__main__':path = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'# input_folder = os.path.join(path, '04_01正方形虚线原图')output_folder = os.path.join(path, '10_04蛋糕线虚线')process_images(input_folder, output_folder)效果图
因为提供的白色背景原图，在PS图片时，魔棒选择容差50，选取相似白色，所以背景白色和蛋糕内部的白色都填充了255,255,255.因此生成的虚线图片，蛋糕内部也是透明的
如果放在白色纸上，这一点不明显，如果填充到彩色纸上，蛋糕内部也是白色。
所以下次AI做图和PS修图时，只考虑修背景部分，不考虑选取相似（内部）
说明：
虽然是Python自动生成，但是生成的时间很长，感觉63张用了30分钟（1024比较大，它要检测边缘，费时）
