python+opencv实现文字颜色识别与标定功能_Python

python+opencv实现文字颜色识别与标定功能

2022-01-05 00:20AI炮灰 Python

最近小编接了一个比较简单的图像处理的单子，今天小编给大家分享python+opencv实现文字颜色识别与标定功能的完整思路及代码，感兴趣的朋友一起看看吧

最近接了一个比较简单的图像处理的单子，花了一点时间随便写了一下：

数据集客户没有是自己随便创建的：

python+opencv实现文字颜色识别与标定功能

程序如下：

"""
    Code creation time:September 11, 2021
    Author:PanBo
    Realize function:It mainly realizes the recognition and calibration of fonts with different colors
"""
import numpy as np
import cv2 as cv
 
font = cv.FONT_HERSHEY_SIMPLEX
lower_red = np.array([0, 120, 120])
hight_red = np.array([10, 255, 255])
#
lower_black = np.array([0, 0, 0])
height_black = np.array([144, 144, 144])
 
lower_yellow = np.array([10, 230, 230])
height_yellow = np.array([35, 255, 255])
 
frame = cv.imread("test.png")
cv.namedWindow("test_image", cv.WINDOW_AUTOSIZE)
cv.imshow("test_image", frame)
 
img_hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
mask_red = cv.inRange(img_hsv, lower_red, hight_red)
mask_black = cv.inRange(img_hsv, lower_black, height_black)
mask_yellow = cv.inRange(img_hsv, lower_yellow, height_yellow)
 
cv.namedWindow("mask_red", cv.WINDOW_AUTOSIZE)
cv.imshow("mask_red", mask_red)
cv.namedWindow("mask_black", cv.WINDOW_AUTOSIZE)
cv.imshow("mask_black", mask_black)
cv.namedWindow("mask_yellow", cv.WINDOW_AUTOSIZE)
cv.imshow("mask_yellow", mask_yellow)
 
kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
mask_yellow = cv.morphologyEx(mask_yellow, cv.MORPH_OPEN, kernel)
cv.namedWindow("mask_yellow_open", cv.WINDOW_AUTOSIZE)
cv.imshow("mask_yellow_open", mask_yellow)
 
mask_yellow = cv.morphologyEx(mask_yellow, cv.MORPH_CLOSE, kernel)
cv.namedWindow("mask_yellow_close", cv.WINDOW_AUTOSIZE)
cv.imshow("mask_yellow_close", mask_yellow)
 
mask_black = cv.medianBlur(mask_black, 3)
mask_red = cv.medianBlur(mask_red, 3)
mask_yellow = cv.medianBlur(mask_yellow, 3)
# cv.imshow(" ", mask_green)
 
cnts1, hierarchy1 = cv.findContours(mask_black, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
cnts2, hierarchy2 = cv.findContours(mask_red, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
cnts3, hierarchy3 = cv.findContours(mask_yellow, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
 
for cnt in cnts1:
    (x, y, w, h) = cv.boundingRect(cnt)
    cv.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 0), 2)
    cv.putText(frame, "black", (x, y-5), font, 0.7, (0, 0, 25）,2）
for cnt in cnts2:
    (x, y, w, h) = cv.boundingRect(cnt)
    cv.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
    cv.putText(frame, "red", (x, y - 5), font, 0.7, (0, 0, 255), 2)
 
for cnt in cnts3:
    (x, y, w, h) = cv.boundingRect(cnt)
    cv.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
    cv.putText(frame, "yellow", (x, y - 5), font, 0.7, (0, 0, 255), 2)
 
cv.namedWindow("output", cv.WINDOW_AUTOSIZE)
cv.imshow("output", frame)
cv.waitKey(0)

首先给定字体颜色的上下阈值，然后提取出红色、黑色以及黄色的字体如下所示：

检测出原始图像中存在的红色字体的为四和五

python+opencv实现文字颜色识别与标定功能