-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathclass3.py
120 lines (108 loc) · 3.79 KB
/
class3.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
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()