毕业设计 python opencv实现车牌识别 颜色判断

主要代码参考https://blog.csdn.net/wzh191920/article/details/79589506

GitHub：https://github.com/yinghualuowu

答辩通过了，补完~

该部分代码还包括缩小边界

def img_color(card_imgs):
    colors = []
    for card_index, card_img in enumerate(card_imgs):

        green = yello = blue = black = white = 0
        card_img_hsv = cv2.cvtColor(card_img, cv2.COLOR_BGR2HSV)
        # 有转换失败的可能，原因来自于上面矫正矩形出错
        if card_img_hsv is None:
            continue
        row_num, col_num = card_img_hsv.shape[:2]
        card_img_count = row_num * col_num

        for i in range(row_num):
            for j in range(col_num):
                H = card_img_hsv.item(i, j, 0)
                S = card_img_hsv.item(i, j, 1)
                V = card_img_hsv.item(i, j, 2)
                if 11 < H <= 34 and S > 34:
                    yello += 1
                elif 35 < H <= 99 and S > 34:
                    green += 1
                elif 99 < H <= 124 and S > 34:
                    blue += 1

                if 0 < H < 180 and 0 < S < 255 and 0 < V < 46:
                    black += 1
                elif 0 < H < 180 and 0 < S < 43 and 221 < V < 225:
                    white += 1
        color = "no"

        limit1 = limit2 = 0
        if yello * 2 >= card_img_count:
            color = "yello"
            limit1 = 11
            limit2 = 34  # 有的图片有色偏偏绿
        elif green * 2 >= card_img_count:
            color = "green"
            limit1 = 35
            limit2 = 99
        elif blue * 2 >= card_img_count:
            color = "blue"
            limit1 = 100
            limit2 = 124  # 有的图片有色偏偏紫
        elif black + white >= card_img_count * 0.7:
            color = "bw"
        colors.append(color)
        card_imgs[card_index] = card_img

        if limit1 == 0:
            continue
        xl, xr, yh, yl = accurate_place(card_img_hsv, limit1, limit2, color)
        if yl == yh and xl == xr:
            continue
        need_accurate = False
        if yl >= yh:
            yl = 0
            yh = row_num
            need_accurate = True
        if xl >= xr:
            xl = 0
            xr = col_num
            need_accurate = True

        if color =="green":
            card_imgs[card_index] = card_img
        else:
            card_imgs[card_index] = card_img[yl:yh, xl:xr] if color != "green" or yl < (yh - yl) // 4 else card_img[
                                                                                                            yl - (
                                                                                                                        yh - yl) // 4:yh,
                                                                                                            xl:xr]

        if need_accurate:
            card_img = card_imgs[card_index]
            card_img_hsv = cv2.cvtColor(card_img, cv2.COLOR_BGR2HSV)
            xl, xr, yh, yl = accurate_place(card_img_hsv, limit1, limit2, color)
            if yl == yh and xl == xr:
                continue
            if yl >= yh:
                yl = 0
                yh = row_num
            if xl >= xr:
                xl = 0
                xr = col_num
        if color =="green":
            card_imgs[card_index] = card_img
        else:
            card_imgs[card_index] = card_img[yl:yh, xl:xr] if color != "green" or yl < (yh - yl) // 4 else card_img[
                                                                                                            yl - (
                                                                                                                        yh - yl) // 4:yh,
                                                                                                            xl:xr]

    return  colors,card_imgs

accrate_place部分

def accurate_place(card_img_hsv, limit1, limit2, color):
    row_num, col_num = card_img_hsv.shape[:2]
    xl = col_num
    xr = 0
    yh = 0
    yl = row_num
    row_num_limit = 21
    col_num_limit = col_num * 0.8 if color != "green" else col_num * 0.5  # 绿色有渐变
    for i in range(row_num):
        count = 0
        for j in range(col_num):
            H = card_img_hsv.item(i, j, 0)
            S = card_img_hsv.item(i, j, 1)
            V = card_img_hsv.item(i, j, 2)
            if limit1 < H <= limit2 and 34 < S and 46 < V:
                count += 1
        if count > col_num_limit:
            if yl > i:
                yl = i
            if yh < i:
                yh = i
    for j in range(col_num):
        count = 0
        for i in range(row_num):
            H = card_img_hsv.item(i, j, 0)
            S = card_img_hsv.item(i, j, 1)
            V = card_img_hsv.item(i, j, 2)
            if limit1 < H <= limit2 and 34 < S and 46 < V:
                count += 1
        if count > row_num - row_num_limit:
            if xl > j:
                xl = j
            if xr < j:
                xr = j
    return xl, xr, yh, yl