def pretreate_image(im, image_name):
"""对图像进行预处理
:param im:
需要预处理的图像
:return:
无
"""
threshold = 180
image_binary = image_binaryzation(im, threshold)
image_binary_pixels = list(image_binary.getdata())
im_rgb = im.convert('RGB')
list_rgb_pixels = list(im_rgb.getdata())
image_rgb_pixels = list_rgb_pixels.copy()
width, height = im.size
remove_noise(image_rgb_pixels, image_binary_pixels, width, height)
im_rgb.putdata(image_rgb_pixels)
im_rgb.save(image_name + "_without_noise.jpg")
list_pixels_for_statistic = image_rgb_pixels.copy() # 用于统计的像素list，接下来要将背景色像数去掉
remove_background_pixels(list_pixels_for_statistic)
# pixels_statistic = {}
pixels_statistic_largest_4 = {} # 图中最多的的四种颜色 / The 4 colors with the largest area
least_color_value = 0 # 四种颜色中，最小那种颜色的面积 / The area of the color with the minimal area
for color in list_pixels_for_statistic:
# if color not in pixels_statistic:
area = list_pixels_for_statistic.count(color)
# pixels_statistic.setdefault(color, area)
if len(pixels_statistic_largest_4) < 4:
pixels_statistic_largest_4.setdefault(color, area)
least_color_key, least_color_value = CustomDataStructureUtil.get_min(pixels_statistic_largest_4)
else:
if color not in pixels_statistic_largest_4:
if area > least_color_value:
pixels_statistic_largest_4.pop(least_color_key)
pixels_statistic_largest_4.setdefault(color, area)
least_color_key, least_color_value = CustomDataStructureUtil.get_min(pixels_statistic_largest_4)
print(CustomDataStructureUtil.get_min(pixels_statistic_largest_4)[1])
print(pixels_statistic_largest_4)
largest_colors = list(pixels_statistic_largest_4.keys())
image_pixels = image_rgb_pixels.copy()
for large_color in largest_colors:
get_single_color_image(im_rgb.copy(), image_pixels.copy(), large_color, width, height)
def get_color_ration(pixels_statistic):
"""计算图中最主要的四种颜色的分布 / Get the 4 main colors' ratio in image
一幅4字的彩色验证码中，我们把占图片比例最多的四种颜色，根据面积由大到小排列为：first, second, third, fourth
考虑到噪点和干扰线，四个字颜色分布可能为
Type_A - 4个字分为4种不同颜色：first : second ∈ [1, 1.5) && second : third ∈ [1,1.5)
Type_B - 4个字分为3种不同颜色，其中2个字颜色一样： first : second ∈ [1.5, 2.5) && second : third ∈ [1, 1.5)
Type_C - 4个字分为2种不同颜色，每种颜色2个字： first:second ∈ [1, 1.5) && second : third ∈ [3.5, ∞)
Type_D - 4个字分为2种不同颜色，其中1种颜色3个字，1种颜色1个字： first : second ∈ [2.5, 3.5)
Type_E - 4个字颜色相同： first : second ∈ [3.5, ∞)
:param
pixels_statistic: 像数统计结果 / The result of the statistic of pixel
:return:
string color_ratio_type:
"""
if isinstance(pixels_statistic, dict):
pixels_statistic_temp = pixels_statistic.copy()
first = CustomDataStructureUtil.get_max(pixels_statistic_temp)
pixels_statistic_temp.pop(first[0])
second = CustomDataStructureUtil.get_max(pixels_statistic_temp)
pixels_statistic_temp.pop(second[0])
rotia_first_second = first[1] / second[1]
if 1 <= rotia_first_second < 1.5:
third = CustomDataStructureUtil.get_max(pixels_statistic_temp)
pixels_statistic_temp.pop(third[0])
rotia_second_third = second[1] / third[1]
if 1 <= rotia_second_third < 1.5:
return ColorRatioType.__TYPE_A__
elif rotia_second_third > 3.5:
return ColorRatioType.__TYPE_C__
elif 1.5 <= rotia_first_second < 2.5:
return ColorRatioType.__TYPE_B__
elif 2.5 <= rotia_first_second < 3.5:
return ColorRatioType.__TYPE_D__
elif 3.5 <= rotia_first_second:
return ColorRatioType.__TYPE_E__
