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class3.py
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class3.py
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import cv2 as cv
import numpy as np
import os
from matplotlib import pyplot as plt
from CutLicensePlate import CutLicensePlate
from SplitLicensePlate import SplitLicensePlate
from ListFile import get_file_list
def cut_lp(input_img):
"""
从图中找出车牌
"""
cutLicensePlate = CutLicensePlate(input_img)
# 轮廓 list
contours = cutLicensePlate.find_rectangle_contour()
# 最合理的车牌轮廓
rsn_rectangle = cutLicensePlate.screen_contours(contours)
# 在输入图片上框出车牌, 并切割出车牌, 提取字符轮廓
draw_img, cut_img = cutLicensePlate.cut_license_plate(rsn_rectangle)
return draw_img, cut_img
def split_lp(input_img):
"""
拆分字符
"""
splitLicensePlate = SplitLicensePlate(input_img)
# 获取 row_sum 和 col_sum
row_sum, col_sum = splitLicensePlate.col_and_row_sum()
bin_img = splitLicensePlate.bin_img
bgr_bin_img = splitLicensePlate.gray2bgr(bin_img)
# 分割字符
color_chars, bin_chars = splitLicensePlate.split_chars(row_sum, col_sum)
bgr_bin_chars = []
for bin_char in bin_chars:
bgr_bin_chars.append(splitLicensePlate.gray2bgr(bin_char))
return bin_img, bgr_bin_img, row_sum, col_sum, color_chars, bin_chars, bgr_bin_chars
if __name__ == "__main__":
# 获取 III 类车牌列表
imgs = []
get_file_list("III类车牌", imgs)
tmp_dir = "III类车牌预处理"
res_dir = "III类车牌结果"
# 创建临时目录
if os.path.isdir(tmp_dir):
print(f"\"{tmp_dir}\"目录已存在")
else:
os.makedirs(tmp_dir)
print(f"创建\"{tmp_dir}\"目录保存图片")
# 创建结果目录
if os.path.isdir(res_dir):
print(f"\"{res_dir}\"目录已存在")
else:
os.makedirs(res_dir)
print(f"\"{res_dir}\"目录已存在")
for img in imgs:
try:
draw_img, cut_img = cut_lp(img)
print(f"在图片{img}中找到了车牌！")
img_name = img.split("/")[1].split(".")[0]
cut_img_name = img_name + ".jpg"
draw_img_name = img_name + "范围.jpg"
# 保存结果
cv.imwrite(f"{tmp_dir}/{cut_img_name}", cut_img)
cv.imwrite(f"{res_dir}/{cut_img_name}", cut_img)
cv.imwrite(f"{res_dir}/{draw_img_name}", draw_img)
cv.imshow("draw_img", draw_img)
cv.imshow("cut_img", cut_img)
cv.waitKey(0)
cv.destroyAllWindows()
except IndexError:
print(f"在图片{img}中没找到车牌!")
cut_imgs = []
get_file_list(tmp_dir, cut_imgs)
for cut_img in cut_imgs:
bin_img, bgr_bin_img, row_sum, col_sum, color_chars, bin_chars, bgr_bin_chars = split_lp(
cut_img)
plt.figure(1)
# row_sum
plt.subplot(2, 2, 1)
plt.barh(range(len(row_sum)), row_sum)
plt.ylim(len(row_sum) - 1, 0)
plt.title("row_sum")
# col_sum
plt.subplot(2, 2, 4)
plt.bar(range(len(col_sum)), col_sum)
plt.xlim(0, len(col_sum) - 1)
plt.title("col_sum")
# bin_img
plt.subplot(2, 2, 2)
plt.imshow(bgr_bin_img)
plt.title("bin_img")
# 保存结果
# plt.savefig(f"{res_dir}/{img_name}累加直方图.jpg")
# 分割字符
plt.figure(2)
# 绘图
n = len(color_chars)
if n != 7:
print("分割的图像可能有误")
else:
print(f"分割{img}成功")
for i in range(n):
plt.subplot(2, n, i + 1)
plt.imshow(cv.cvtColor(color_chars[i], cv.COLOR_BGR2RGB))
plt.subplot(2, n, i + n + 1)
plt.imshow(bgr_bin_chars[i])
# 保存结果
# plt.savefig(f"{res_dir}/{img_name}分割结果.jpg")
# 显示
plt.show()