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背景需求：
用Python对透明背景png图案的制作拓展白色描边，制作点状虚线
from PIL import Image, ImageDraw
import os# 距离图片边缘的距离（留多少白边）
bianju = 10
# 留白线的粗细（剪切边的粗细）
bianju2 = 2
# 圆点的大小
dot_size = 5
# 圆点之间的间隔
dot_spacing = 5def detect_edges(image):"""检测图像的边缘。如果像素透明，则标记为边缘。"""if image.mode != 'RGBA':image = image.convert('RGBA')width, height = image.sizeedges = Image.new('L', (width, height), 0)draw = ImageDraw.Draw(edges)pixels = image.load()for y in range(1, height - 1):for x in range(1, width - 1):r, g, b, a = pixels[x, y]if a == 0:continueneighbors = [pixels[x-1, y], pixels[x+1, y],pixels[x, y-1], pixels[x, y+1]]for nr, ng, nb, na in neighbors:if na == 0:draw.point((x, y), fill=255)breakreturn edgesdef expand_edges(edges, distance):"""扩展图像的边缘。根据给定的距离，将边缘像素扩展到指定范围。"""expanded_edges = Image.new('L', edges.size, 0)draw = ImageDraw.Draw(expanded_edges)pixels = edges.load()for y in range(edges.height):for x in range(edges.width):if pixels[x, y] > 0:for dy in range(-distance, distance + 1):for dx in range(-distance, distance + 1):nx, ny = x + dx, y + dyif 0 <= nx < edges.width and 0 <= ny < edges.height:draw.point((nx, ny), fill=255)return expanded_edgesdef process_images(input_folder, output_folder):"""处理输入文件夹中的所有PNG图像，并将结果保存到输出文件夹中。"""if not os.path.exists(output_folder):os.makedirs(output_folder)for filename in os.listdir(input_folder):if filename.endswith(".png"):image_path = os.path.join(input_folder, filename)image = Image.open(image_path).convert('RGBA')edges = detect_edges(image)expanded_edges = expand_edges(edges, bianju)result = Image.new('RGBA', image.size, (255, 255, 255, 0))red_fill = Image.new('RGBA', image.size, (255, 255, 255, 255))masked_red_fill = Image.composite(red_fill, Image.new('RGBA', image.size), expanded_edges)final_result = Image.alpha_composite(image, masked_red_fill)temp_image = Image.new('RGBA', final_result.size, (0, 0, 0, 0))draw = ImageDraw.Draw(temp_image)pixels = final_result.load()# 用于交替绘制黑白圆点的计数器dot_counter = 0for y in range(1, final_result.height - 1, dot_spacing):for x in range(1, final_result.width - 1, dot_spacing):r, g, b, a = pixels[x, y]if a == 0:continue# 检查是否是边缘像素neighbors = [pixels[x-1, y], pixels[x+1, y],pixels[x, y-1], pixels[x, y+1]]edge_found = Falsefor nr, ng, nb, na in neighbors:if na == 0:edge_found = Truebreakif edge_found:# 交替绘制黑白圆点if dot_counter % 2 == 0:draw.ellipse([x - dot_size//2, y - dot_size//2,x + dot_size//2, y + dot_size//2], fill=(0, 0, 0))else:draw.ellipse([x - dot_size//2, y - dot_size//2,x + dot_size//2, y + dot_size//2], fill=(255, 255, 255))dot_counter += 1final_result = Image.alpha_composite(final_result, temp_image)final_result = Image.alpha_composite(final_result, image)output_path = os.path.join(output_folder, filename)final_result.save(output_path)print(f"Processed {filename} and saved to {output_path}")if __name__ == '__main__':path = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'input_folder = path + r'\01_01原图'output_folder = path + r'\01_02边图'os.makedirs(output_folder, exist_ok=True)process_images(input_folder, output_folder)
换了一张边距充分的图片也是一样的结果
黑白圆点不平均，
、
代码展示
from PIL import Image, ImageDraw
import os
import math
import numpy as np
from skimage import measure# 参数配置
WHITE_BORDER_WIDTH = 5 # 白色边缘宽度
DOT_SIZE = 5 # 圆点直径
DOT_SPACING = 10 # 圆点间距（像素）
DOT_OFFSET = 3 # 圆点向外偏移量def precise_edge_detection(image):"""使用更精确的边缘检测算法"""if image.mode != 'RGBA':image = image.convert('RGBA')# 转换为numpy数组处理arr = np.array(image)alpha = arr[:,:,3]# 使用sobel算子检测边缘from scipy import ndimagesobel_x = ndimage.sobel(alpha, axis=0)sobel_y = ndimage.sobel(alpha, axis=1)edge_mask = np.hypot(sobel_x, sobel_y) > 0# 转换为PIL图像edge_image = Image.fromarray((edge_mask * 255).astype(np.uint8))return edge_imagedef create_white_border(edge_image, width):"""创建白色边缘区域"""from scipy import ndimagearr = np.array(edge_image)distance = ndimage.distance_transform_edt(arr == 0)white_border = (distance <= width) & (distance > 0)return Image.fromarray((white_border * 255).astype(np.uint8))def get_smooth_contour(white_border):"""使用Marching Squares算法获取平滑轮廓"""arr = np.array(white_border) > 0contours = measure.find_contours(arr, 0.5)if not contours:return []# 取最长的轮廓main_contour = max(contours, key=len)# 简化轮廓点from scipy.interpolate import splprep, splevtck, u = splprep(main_contour.T, u=None, s=0.0, per=1)u_new = np.linspace(u.min(), u.max(), len(main_contour)//2)x_new, y_new = splev(u_new, tck, der=0)return list(zip(x_new, y_new))def distribute_dots_on_contour(contour, image_size):"""在轮廓上均匀分布圆点"""if not contour:return []# 计算轮廓总长度total_length = 0lengths = []for i in range(len(contour)):x1, y1 = contour[i]x2, y2 = contour[(i+1)%len(contour)]segment_length = math.hypot(x2-x1, y2-y1)lengths.append(segment_length)total_length += segment_length# 计算需要的圆点数量num_dots = int(total_length / DOT_SPACING)if num_dots < 1:return []# 均匀分布点dot_positions = []target_length = 0current_segment = 0accumulated_length = 0for _ in range(num_dots):# 找到目标位置所在的线段while accumulated_length + lengths[current_segment] < target_length:accumulated_length += lengths[current_segment]current_segment = (current_segment + 1) % len(contour)# 计算在线段上的位置segment_start = contour[current_segment]segment_end = contour[(current_segment+1)%len(contour)]ratio = (target_length - accumulated_length) / lengths[current_segment]x = segment_start[0] * (1-ratio) + segment_end[0] * ratioy = segment_start[1] * (1-ratio) + segment_end[1] * ratio# 计算法线方向（向外）dx = segment_end[0] - segment_start[0]dy = segment_end[1] - segment_start[1]nx = -dy / math.hypot(dx, dy)ny = dx / math.hypot(dx, dy)# 向外偏移dot_x = x + nx * DOT_OFFSETdot_y = y + ny * DOT_OFFSET# 确保在图像范围内dot_x = max(DOT_SIZE//2, min(dot_x, image_size[0] - DOT_SIZE//2 - 1))dot_y = max(DOT_SIZE//2, min(dot_y, image_size[1] - DOT_SIZE//2 - 1))dot_positions.append((dot_x, dot_y))target_length += total_length / num_dotsif target_length > total_length:target_length -= total_lengthreturn dot_positionsdef process_image(image_path, output_path):"""处理单个图像"""try:image = Image.open(image_path).convert('RGBA')except:print(f"无法打开图像: {image_path}")return# 第一步：精确边缘检测edges = precise_edge_detection(image)# 第二步：创建白色边缘white_border = create_white_border(edges, WHITE_BORDER_WIDTH)# 创建白色边缘图像white_image = Image.new('RGBA', image.size, (0,0,0,0))white_draw = ImageDraw.Draw(white_image)white_draw.bitmap((0,0), white_border.convert('L'), fill=(255,255,255,255))# 合并图像result = Image.alpha_composite(image, white_image)# 第三步：获取平滑轮廓contour = get_smooth_contour(white_border)if contour:# 第四步：在轮廓上均匀分布圆点dot_positions = distribute_dots_on_contour(contour, image.size)# 绘制圆点draw = ImageDraw.Draw(result)for i, (x, y) in enumerate(dot_positions):if i % 2 == 0:draw.ellipse([x-DOT_SIZE//2, y-DOT_SIZE//2,x+DOT_SIZE//2, y+DOT_SIZE//2], fill=(0, 0, 0, 255)) # 黑点else:draw.ellipse([x-DOT_SIZE//2, y-DOT_SIZE//2,x+DOT_SIZE//2, y+DOT_SIZE//2], fill=(255, 255, 255, 255)) # 白点# 保存结果result.save(output_path)print(f"处理完成: {output_path}")def process_folder(input_folder, output_folder):"""处理文件夹中的所有PNG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__':input_folder = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸\01_01原图'output_folder = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸\01_02边图'process_folder(input_folder, output_folder)
我试了无数次修改，这个黑点子始终是逆时针旋转90度
换一个问法继续测试
第1次修改
'''
094把内部边缘线变成点状
deepseek 阿夏
20250405
'''from PIL import Image, ImageDraw
import os# 白边宽度（像素）
white_border_width = 20
# 黑点直径（像素）
dot_size = 5
# 黑点间距（像素）
dot_spacing = 5def 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:param image: 输入的RGBA图像:return: 边缘像素坐标列表"""edge_pixels = []pixels = image.load()width, height = image.sizefor y in range(height):for x in range(width):if pixels[x, y][3] > 0: # 如果当前像素不透明# 检查4邻域像素neighbors = [(x-1, y), (x+1, y),(x, y-1), (x, y+1)]for nx, ny in neighbors:if 0 <= nx < width and 0 <= ny < height:if pixels[nx, ny][3] == 0: # 如果邻域像素透明edge_pixels.append((x, y))breakreturn edge_pixelsdef expand_edge_pixels(edge_pixels, distance):"""扩展边缘像素坐标到指定距离:param edge_pixels: 原始边缘像素坐标列表:param distance: 扩展距离（像素）:return: 扩展后的像素坐标集合"""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 + dyexpanded_pixels.add((nx, ny))return expanded_pixelsdef draw_dots_on_border(image, original_edge_pixels, border_pixels):"""在原始边缘与白边交界处绘制黑点:param image: 原始图像:param original_edge_pixels: 原始边缘像素坐标:param border_pixels: 白边区域像素坐标集合:return: 带有点状边框的图像"""# 创建一个透明图层用于绘制点dot_layer = Image.new('RGBA', image.size, (0, 0, 0, 0))draw = ImageDraw.Draw(dot_layer)# 找出需要绘制黑点的位置（原始边缘与白边交界处）dots_to_draw = []for x, y in original_edge_pixels:if (x, y) in border_pixels:dots_to_draw.append((x, y))# 按照间距绘制黑点for i in range(0, len(dots_to_draw), dot_spacing):x, y = dots_to_draw[i]draw.ellipse([(x - dot_size//2, y - dot_size//2),(x + dot_size//2, y + dot_size//2)], fill=(0, 0, 0, 255))return dot_layerdef process_image(input_path, output_path):"""处理单个图像:param input_path: 输入图像路径:param output_path: 输出图像路径"""# 打开原始图像original = Image.open(input_path).convert('RGBA')width, height = original.size# 获取原始图像的边缘像素original_edge_pixels = get_edge_pixels(original)# 扩展边缘像素创建白边区域border_pixels = expand_edge_pixels(original_edge_pixels, white_border_width)# 创建白边图层white_border = Image.new('RGBA', (width, height), (255, 255, 255, 255))# 创建蒙版mask = Image.new('L', (width, height), 0)mask_pixels = mask.load()for x, y in border_pixels:if 0 <= x < width and 0 <= y < height:mask_pixels[x, y] = 255white_border.putalpha(mask)# 将白边与原始图像合成result = Image.alpha_composite(original, white_border)# 在白边与原始图像交界处绘制黑点dot_layer = draw_dots_on_border(original, original_edge_pixels, border_pixels)result = Image.alpha_composite(result, dot_layer)# 保存结果result.save(output_path, format='PNG')print(f"Processed and saved to {output_path}")def process_images(input_folder, output_folder):"""处理文件夹中的所有PNG图像:param input_folder: 输入文件夹路径:param output_folder: 输出文件夹路径"""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, '03_01正方形原图')output_folder = os.path.join(path, '03_02正方形边图')os.makedirs(output_folder, exist_ok=True)process_images(input_folder, output_folder)青蛙的黑点在青蛙外轮廓上（我需要的是白色描边的外侧
第2次修改
'''
095把白色拓展边缘全部做成点状
deepseek 阿夏
20250405
'''from PIL import Image, ImageDraw
import os
import math# 距离图片边缘的距离（留多少白边）
bianju = 20 # 增加白边宽度到20磅
# 黑点的直径
dot_size = 5
# 黑点之间的间距
dot_spacing = 5def detect_edges(image):"""检测图像的边缘。如果像素透明，则标记为边缘。:param image: 输入的图像:return: 包含边缘信息的图像"""if image.mode != 'RGBA':image = image.convert('RGBA')width, height = image.sizeedges = Image.new('L', (width, height), 0)draw = ImageDraw.Draw(edges)pixels = image.load()for y in range(1, height - 1):for x in range(1, width - 1):r, g, b, a = pixels[x, y]if a == 0:continueneighbors = [pixels[x-1, y], pixels[x+1, y],pixels[x, y-1], pixels[x, y+1]]for nr, ng, nb, na in neighbors:if na == 0:draw.point((x, y), fill=255)breakreturn edgesdef expand_edges(edges, distance):"""扩展图像的边缘。根据给定的距离，将边缘像素扩展到指定范围。:param edges: 包含边缘信息的图像:param distance: 扩展的距离:return: 扩展后的边缘图像"""expanded_edges = Image.new('L', edges.size, 0)draw = ImageDraw.Draw(expanded_edges)pixels = edges.load()for y in range(edges.height):for x in range(edges.width):if pixels[x, y] > 0:for dy in range(-distance, distance + 1):for dx in range(-distance, distance + 1):nx, ny = x + dx, y + dyif 0 <= nx < edges.width and 0 <= ny < edges.height:draw.point((nx, ny), fill=255)return expanded_edgesdef draw_dotted_border(image, edge_mask):"""在图像的边缘区域绘制点状边框:param image: 原始图像:param edge_mask: 边缘区域掩膜:return: 带有点状边框的图像"""# 创建一个透明图层用于绘制点dot_layer = Image.new('RGBA', image.size, (0, 0, 0, 0))draw = ImageDraw.Draw(dot_layer)pixels = edge_mask.load()width, height = edge_mask.size# 计算点的步长（直径+间距）step = dot_size + dot_spacing# 遍历图像，在边缘区域绘制点for y in range(0, height, step):for x in range(0, width, step):if 0 <= x < width and 0 <= y < height and pixels[x, y] > 0:# 绘制一个黑点draw.ellipse([(x - dot_size//2, y - dot_size//2),(x + dot_size//2, y + dot_size//2)], fill=(0, 0, 0, 255))return dot_layerdef process_images(input_folder, output_folder):"""处理输入文件夹中的所有PNG图像，并将结果保存到输出文件夹中。:param input_folder: 输入文件夹路径:param output_folder: 输出文件夹路径"""if not os.path.exists(output_folder):os.makedirs(output_folder)for filename in os.listdir(input_folder):if filename.endswith(".png"):image_path = os.path.join(input_folder, filename)image = Image.open(image_path).convert('RGBA')# 检测图像的边缘edges = detect_edges(image)# 扩展边缘像素，扩展距离为bianjuexpanded_edges = expand_edges(edges, bianju)# 创建一个白色边缘层white_border = Image.new('RGBA', image.size, (255, 255, 255, 255))# 将白色边缘应用到扩展边缘区域white_border.putalpha(expanded_edges)# 将原始图像与白色边缘合成result_with_white_border = Image.alpha_composite(image, white_border)# 在边缘区域绘制点状边框dot_border = draw_dotted_border(image, expanded_edges)# 将点状边框与结果合成final_result = Image.alpha_composite(result_with_white_border, dot_border)# 保存结果（保持透明背景）output_path = os.path.join(output_folder, filename)final_result.save(output_path, format='PNG')print(f"Processed {filename} and saved to {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, '03_01正方形原图')output_folder = os.path.join(path, '03_02正方形边图')os.makedirs(output_folder, exist_ok=True)process_images(input_folder, output_folder)它把白色描边20磅的位置全部填充了点子
第3次修改
'''
096内外黑色小点子
deepseek 阿夏
20250405
'''from PIL import Image, ImageDraw
import os# 白边宽度（像素）
white_border_width = 20
# 黑点直径（像素）
dot_size = 5
# 黑点间距（像素）
dot_spacing = 5def 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:param image: 输入的RGBA图像:return: 边缘像素坐标列表"""edge_pixels = []pixels = image.load()width, height = image.sizefor y in range(height):for x in range(width):if pixels[x, y][3] > 0: # 如果当前像素不透明# 检查4邻域像素neighbors = [(x-1, y), (x+1, y),(x, y-1), (x, y+1)]for nx, ny in neighbors:if 0 <= nx < width and 0 <= ny < height:if pixels[nx, ny][3] == 0: # 如果邻域像素透明edge_pixels.append((x, y))breakreturn edge_pixelsdef expand_edge_pixels(edge_pixels, distance):"""扩展边缘像素坐标到指定距离:param edge_pixels: 原始边缘像素坐标列表:param distance: 扩展距离（像素）:return: 扩展后的像素坐标集合"""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 + dyexpanded_pixels.add((nx, ny))return expanded_pixelsdef get_outer_edge_pixels(border_pixels, width, height):"""获取白边区域的外边缘像素（与透明区域接触的一侧）:param border_pixels: 白边区域的所有像素:param width: 图像宽度:param height: 图像高度:return: 外边缘像素列表"""outer_edge = set()border_set = border_pixelsfor x, y in border_set:# 检查8邻域是否有透明像素neighbors = [(x-1, y-1), (x, y-1), (x+1, y-1),(x-1, y), (x+1, y),(x-1, y+1), (x, y+1), (x+1, y+1)]for nx, ny in neighbors:if (0 <= nx < width and 0 <= ny < height) and (nx, ny) not in border_set:outer_edge.add((x, y))breakreturn list(outer_edge)def draw_dots_on_outer_edge(image, outer_edge_pixels):"""在白边外侧边缘绘制黑点:param image: 原始图像:param outer_edge_pixels: 外边缘像素坐标:return: 带有点状边框的图像"""# 创建一个透明图层用于绘制点dot_layer = Image.new('RGBA', image.size, (0, 0, 0, 0))draw = ImageDraw.Draw(dot_layer)# 按照间距绘制黑点for i in range(0, len(outer_edge_pixels), dot_spacing):x, y = outer_edge_pixels[i]draw.ellipse([(x - dot_size//2, y - dot_size//2),(x + dot_size//2, y + dot_size//2)], fill=(0, 0, 0, 255))return dot_layerdef process_image(input_path, output_path):"""处理单个图像:param input_path: 输入图像路径:param output_path: 输出图像路径"""# 打开原始图像original = Image.open(input_path).convert('RGBA')width, height = original.size# 获取原始图像的边缘像素original_edge_pixels = get_edge_pixels(original)# 扩展边缘像素创建白边区域border_pixels = expand_edge_pixels(original_edge_pixels, white_border_width)# 获取白边区域的外边缘像素（靠近透明区域的一侧）outer_edge_pixels = get_outer_edge_pixels(border_pixels, width, height)# 创建白边图层white_border = Image.new('RGBA', (width, height), (255, 255, 255, 255))# 创建蒙版mask = Image.new('L', (width, height), 0)mask_pixels = mask.load()for x, y in border_pixels:if 0 <= x < width and 0 <= y < height:mask_pixels[x, y] = 255white_border.putalpha(mask)# 将白边与原始图像合成result = Image.alpha_composite(original, white_border)# 在白边外侧绘制黑点dot_layer = draw_dots_on_outer_edge(original, outer_edge_pixels)result = Image.alpha_composite(result, dot_layer)# 保存结果result.save(output_path, format='PNG')print(f"Processed and saved to {output_path}")def process_images(input_folder, output_folder):"""处理文件夹中的所有PNG图像:param input_folder: 输入文件夹路径:param output_folder: 输出文件夹路径"""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, '03_01正方形原图')output_folder = os.path.join(path, '03_02正方形边图')os.makedirs(output_folder, exist_ok=True)process_images(input_folder, output_folder)白色描边的外侧和内侧都是黑点子
我感觉无论如何白色描边都会遮挡青蛙外轮廓，所以需要把原图青蛙最后覆盖在最上面，这样就能挡住内侧的黑点子。
第4次修改
'''
097把原图覆盖在最上面
deepseek 阿夏
20250405
'''from PIL import Image, ImageDraw
import os# 白边宽度（像素）
white_border_width = 20
# 黑点直径（像素）
dot_size = 5
# 黑点间距（像素）
dot_spacing = 5def 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:param image: 输入的RGBA图像:return: 边缘像素坐标列表"""edge_pixels = []pixels = image.load()width, height = image.sizefor y in range(height):for x in range(width):if pixels[x, y][3] > 0: # 如果当前像素不透明# 检查4邻域像素neighbors = [(x-1, y), (x+1, y),(x, y-1), (x, y+1)]for nx, ny in neighbors:if 0 <= nx < width and 0 <= ny < height:if pixels[nx, ny][3] == 0: # 如果邻域像素透明edge_pixels.append((x, y))breakreturn edge_pixelsdef expand_edge_pixels(edge_pixels, distance):"""扩展边缘像素坐标到指定距离:param edge_pixels: 原始边缘像素坐标列表:param distance: 扩展距离（像素）:return: 扩展后的像素坐标集合"""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 + dyexpanded_pixels.add((nx, ny))return expanded_pixelsdef get_outer_edge_pixels(border_pixels, width, height):"""获取白边区域的外边缘像素（与透明区域接触的一侧）:param border_pixels: 白边区域的所有像素:param width: 图像宽度:param height: 图像高度:return: 外边缘像素列表"""outer_edge = set()border_set = border_pixelsfor x, y in border_set:# 检查8邻域是否有透明像素neighbors = [(x-1, y-1), (x, y-1), (x+1, y-1),(x-1, y), (x+1, y),(x-1, y+1), (x, y+1), (x+1, y+1)]for nx, ny in neighbors:if (0 <= nx < width and 0 <= ny < height) and (nx, ny) not in border_set:outer_edge.add((x, y))breakreturn list(outer_edge)def draw_dots_on_outer_edge(image, outer_edge_pixels):"""在白边外侧边缘绘制黑点:param image: 原始图像:param outer_edge_pixels: 外边缘像素坐标:return: 带有点状边框的图像"""# 创建一个透明图层用于绘制点dot_layer = Image.new('RGBA', image.size, (0, 0, 0, 0))draw = ImageDraw.Draw(dot_layer)# 按照间距绘制黑点for i in range(0, len(outer_edge_pixels), dot_spacing):x, y = outer_edge_pixels[i]draw.ellipse([(x - dot_size//2, y - dot_size//2),(x + dot_size//2, y + dot_size//2)], fill=(0, 0, 0, 255))return dot_layerdef process_image(input_path, output_path):"""处理单个图像:param input_path: 输入图像路径:param output_path: 输出图像路径"""# 打开原始图像并保留副本original = Image.open(input_path).convert('RGBA')original_copy = original.copy() # 创建原始图像的副本用于最后覆盖width, height = original.size# 获取原始图像的边缘像素original_edge_pixels = get_edge_pixels(original)# 扩展边缘像素创建白边区域border_pixels = expand_edge_pixels(original_edge_pixels, white_border_width)# 获取白边区域的外边缘像素（靠近透明区域的一侧）outer_edge_pixels = get_outer_edge_pixels(border_pixels, width, height)# 创建白边图层white_border = Image.new('RGBA', (width, height), (255, 255, 255, 255))# 创建蒙版mask = Image.new('L', (width, height), 0)mask_pixels = mask.load()for x, y in border_pixels:if 0 <= x < width and 0 <= y < height:mask_pixels[x, y] = 255white_border.putalpha(mask)# 将白边与原始图像合成result = Image.alpha_composite(original, white_border)# 在白边外侧绘制黑点dot_layer = draw_dots_on_outer_edge(original, outer_edge_pixels)result = Image.alpha_composite(result, dot_layer)# 最后将原始图像覆盖在最上层result = Image.alpha_composite(result, original_copy)# 保存结果result.save(output_path, format='PNG')print(f"Processed and saved to {output_path}")def process_images(input_folder, output_folder):"""处理文件夹中的所有PNG图像:param input_folder: 输入文件夹路径:param output_folder: 输出文件夹路径"""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, '03_01正方形原图')output_folder = os.path.join(path, '03_02正方形边图')os.makedirs(output_folder, exist_ok=True)process_images(input_folder, output_folder)青蛙外形完整了，白色描边旁边也有黑点子了。
但是黑色点子分布不均匀
第4次修改
'''
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
20250405
'''from PIL import Image, ImageDraw
import os
import math# 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, '03_01正方形原图')output_folder = os.path.join(path, '03_02正方形边图')process_images(input_folder, output_folder)
遍历所有png图片
最终代码
'''
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
20250405
'''from PIL import Image, ImageDraw
import os
import math# 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, '03_01正方形原图')output_folder = os.path.join(path, '03_02正方形边图')process_images(input_folder, output_folder)
切掉上下左右白边+统一大小（1000*1000）
'''
图片处理流程：
1. 裁剪透明白边，保存透明PNG
2. 对裁剪后的图片统一尺寸，保存透明PNG
deepseek、阿夏
20250405
'''import os
from PIL import Image# 全局设置
path = r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'
input_folder = path + r'\03_02正方形边图' # 原始图片文件夹
cropped_folder = path + r'\03_03切边图透明' # 裁剪后的透明图片
resized_folder = path + r'\03_04统一图' # 统一尺寸后的图片# 创建输出文件夹
os.makedirs(cropped_folder, exist_ok=True)
os.makedirs(resized_folder, exist_ok=True)# 参数设置
transparent_edge = 40 # 裁剪时不保留额外透明边距
target_width = 1000 # 统一宽度
target_height = 1000 # 统一高度def find_content_boundary(image):"""找到图像中非透明内容的精确边界:param image: PIL Image对象(RGBA模式):return: (left, top, right, bottom) 内容边界坐标"""if image.mode != 'RGBA':image = image.convert('RGBA')width, height = image.sizepixels = image.load()left, right = width, 0top, bottom = height, 0for y in range(height):for x in range(width):if pixels[x, y][3] > 0: # 非透明像素if x < left: left = xif x > right: right = xif y < top: top = yif y > bottom: bottom = yreturn left, top, right+1, bottom+1 # +1确保包含边界像素def crop_to_content(image):"""精确裁剪到非透明内容边界"""boundary = find_content_boundary(image)return image.crop(boundary)def resize_with_transparency(image, target_size):"""保持透明背景调整图像尺寸:param image: 已裁剪的图片:param target_size: (width, height)目标尺寸:return: 调整尺寸后的图像"""# 计算缩放比例（保持宽高比）width_ratio = target_size[0] / image.widthheight_ratio = target_size[1] / image.heightscale_ratio = min(width_ratio, height_ratio)# 等比缩放new_width = int(image.width * scale_ratio)new_height = int(image.height * scale_ratio)resized = image.resize((new_width, new_height), Image.LANCZOS)# 创建新透明画布new_image = Image.new('RGBA', target_size, (0, 0, 0, 0))# 计算居中位置x_offset = (target_size[0] - new_width) // 2y_offset = (target_size[1] - new_height) // 2# 粘贴缩放后的图像new_image.paste(resized, (x_offset, y_offset), resized)return new_imagedef process_images():"""完整的图片处理流程"""# 第一步：精确裁剪透明白边print("=== 开始裁剪透明白边 ===")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(cropped_folder, filename)try:img = Image.open(input_path).convert('RGBA')cropped = crop_to_content(img)cropped.save(output_path, format='PNG')print(f"裁剪完成: {filename}")except Exception as e:print(f"裁剪失败 {filename}: {str(e)}")# 第二步：统一已裁剪图片的尺寸print("\n=== 开始统一已裁剪图片的尺寸 ===")for filename in os.listdir(cropped_folder):if filename.lower().endswith('.png'):input_path = os.path.join(cropped_folder, filename)output_path = os.path.join(resized_folder, filename)try:img = Image.open(input_path).convert('RGBA')resized = resize_with_transparency(img, (target_width, target_height))resized.save(output_path, format='PNG')print(f"尺寸统一完成: {filename}")except Exception as e:print(f"尺寸调整失败 {filename}: {str(e)}")print("\n=== 处理完成 ===")print(f"裁剪后的图片保存在: {cropped_folder}")print(f"统一尺寸的图片保存在: {resized_folder}")if __name__ == '__main__':process_images()
切掉PNG透明图的白边（没有预留上下左右的边距，只有0，顶天立地）
统一PNG图片，大小1000*1000（没有预留上下左右的边距）
做成gif
'''
青蛙图片虚线描边后，做成gif动画，便于贴入CSDN
deepseek，阿夏
20250404
'''
size=1000
d=1000
c=20from PIL import Image
import osdef create_optimized_gif(input_folder, output_file, duration=d, max_size=size, colors=c, skip_frames=1):"""完整优化版本"""images = []for i, filename in enumerate(sorted(os.listdir(input_folder))):if i % (skip_frames + 1) != 0: # 跳过部分帧continueif filename.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif')):filepath = os.path.join(input_folder, filename)try:img = Image.open(filepath)# 调整尺寸if max_size:img.thumbnail((max_size, max_size), Image.LANCZOS)# 转换为P模式(调色板)并减少颜色if img.mode != 'P':img = img.convert('P', palette=Image.ADAPTIVE, colors=colors)images.append(img)except Exception as e:print(f"无法加载图片 {filename}: {e}")if not images:print("没有找到可用的图片文件")return# 保存为优化后的GIFimages[0].save(output_file,save_all=True,append_images=images[1:],duration=duration,loop=0,optimize=True,disposal=2)print(f"优化后的GIF已创建: {output_file} (大小: {os.path.getsize(output_file)/1024:.2f}KB)")if __name__ == "__main__":path=r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'input_folder = path+r"\03_04统一图" # 图片所在的文件夹output_file =path+ r"\Python青蛙切边虚线描边.gif" # 输出的GIF文件名# 创建GIF，每帧显示3秒(3000毫秒)create_optimized_gif( input_folder, output_file, duration=d, max_size=size, colors=c, skip_frames=1)# from PIL import Image
# import os# def create_gif(input_folder, output_file, duration=2000, loop=0):
# """
# 将文件夹中的图片合并为GIF# 参数:
# input_folder: 包含图片的文件夹路径
# output_file: 输出的GIF文件路径
# duration: 每帧显示时间(毫秒)，默认3000(3秒)
# loop: 循环次数，0表示无限循环
# """
# # 获取文件夹中所有图片文件
# images = []
# for filename in sorted(os.listdir(input_folder)):
# if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif')):
# filepath = os.path.join(input_folder, filename)
# try:
# img = Image.open(filepath)
# images.append(img)
# except Exception as e:
# print(f"无法加载图片 {filename}: {e}")# if not images:
# print("没有找到可用的图片文件")
# return# # 保存第一张图片以获取尺寸
# first_image = images[0]# # 保存为GIF
# first_image.save(
# output_file,
# save_all=True,
# append_images=images[1:],
# duration=duration,
# loop=loop
# )# print(f"GIF已成功创建: {output_file}")# # 使用示例
# if __name__ == "__main__":
# path=r'C:\Users\jg2yXRZ\OneDrive\桌面\20250401边缘线剪纸'
# input_folder = path+r"\02_02青蛙白色点图" # 图片所在的文件夹
# output_file =path+ r"\青蛙虚线描边.gif" # 输出的GIF文件名# # 创建GIF，每帧显示3秒(3000毫秒)
# create_gif(input_folder, output_file, duration=2000)
