66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
from PIL import Image
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def find_most_frequent_color(PIL_img, n):
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img = PIL_img.convert('RGBA') # 确保图片是RGBA模式
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# 初始化颜色统计字典
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color_count = {}
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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 == 255:
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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_count[color] = color_count.get(color, 0) + 1
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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 == 255:
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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_count[color] = color_count.get(color, 0) + 1
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else:
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count = 0
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# 找到出现次数最多的颜色
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most_frequent_color = max(color_count, key=color_count.get)
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# 返回像素点最多的颜色对应的字符串（格式化为十六进制）
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return '#{:02x}{:02x}{:02x}'.format(*most_frequent_color)
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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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color_string = color_string[1:]
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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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