109 lines
2.9 KiB
Python
109 lines
2.9 KiB
Python
from collections import defaultdict
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import numpy as np
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from PIL import Image
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def rgb_to_hex(rgb_colr):
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return '{:02x}{:02x}{:02x}'.format(*rgb_colr)
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def hex_to_rgb(hex_color):
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return tuple(int(hex_color[i:i + 2], 16) for i in (0, 2, 4))
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def get_colors(PIL_img, n):
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color_list = []
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img = PIL_img.convert('RGBA') # 确保图片是RGBA模式
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# 获取图片尺寸
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width, height = img.size
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for y in range(height):
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count = 0
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# 从左到右扫描
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for x in range(width):
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r, g, b, a = img.getpixel((x, y))
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if a != 0:
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count += 1
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if count <= n:
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color = (r, g, b)
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color_list.append(rgb_to_hex(color))
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else:
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count = 0
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count = 0
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# 从右到左扫描
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for x in range(width - 1, -1, -1):
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r, g, b, a = img.getpixel((x, y))
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if a != 0:
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count += 1
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if count <= n:
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color = (r, g, b)
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color_list.append(rgb_to_hex(color))
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else:
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count = 0
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return color_list
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def color_distance(c1, c2):
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(r1, g1, b1) = c1
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(r2, g2, b2) = c2
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return np.sqrt((r1 - r2) ** 2 + (g1 - g2) ** 2 + (b1 - b2) ** 2)
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def average_color(colors):
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r = int(np.mean([c[0] for c in colors]))
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g = int(np.mean([c[1] for c in colors]))
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b = int(np.mean([c[2] for c in colors]))
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return f"{r:02x}{g:02x}{b:02x}"
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def fuzzy_color_grouping(colors, threshold):
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groups = defaultdict(list)
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for color in colors:
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rgb = hex_to_rgb(color)
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placed = False
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for group_color in groups:
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if color_distance(rgb, hex_to_rgb(group_color)) < threshold:
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groups[group_color].append(rgb)
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placed = True
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break
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if not placed:
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groups[color].append(rgb)
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return groups
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def most_common_fuzzy_color(colors, threshold):
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groups = fuzzy_color_grouping(colors, threshold)
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largest_group = max(groups, key=lambda k: len(groups[k]))
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return average_color(groups[largest_group])
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def is_color_similar(color1, color2, threshold):
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return all(abs(c1 - c2) <= threshold for c1, c2 in zip(color1, color2))
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def find_similar_colors(image, color_string, threshold):
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# 转换颜色字符串为RGB元组
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target_color = tuple(int(color_string[i:i + 2], 16) for i in (0, 2, 4))
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# 创建一个同样大小的黑色背景图像
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output_image = Image.new('RGB', image.size, (0, 0, 0))
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pixels = image.load()
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output_pixels = output_image.load()
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# 遍历每个像素点，检查颜色是否接近目标颜色
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for x in range(image.width):
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for y in range(image.height):
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if is_color_similar(pixels[x, y], target_color, threshold):
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# 将接近的颜色设置为白色
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output_pixels[x, y] = (255, 255, 255)
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return output_image
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