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Python+Qt掌纹识别

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前言

这篇博客针对<<Python+Qt掌纹识别>>编写代码，代码整洁，规则，易读。学习与应用推荐首选。

文章目录

一、所需工具软件

二、使用步骤

1. 引入库

2. 代码实现

3. 运行结果

三、在线协助

一、所需工具软件

1. Python

2. Qt, OpenCV

二、使用步骤

1.引入库

import cv2
import cv2 as cv
import numpy as np
from PyQt5 import QtWidgetsfrom PyQt5 import QtWidgets, QtCore, QtGui
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *

2. 代码实现

代码如下:

class myWin(QtWidgets.QWidget, Ui_Dialog):def __init__(self):super(myWin, self).__init__()self.setupUi(self)def openFileButton(self):imgName, imgType  = QFileDialog.getOpenFileName(self,"打开文件","./","files(*.*)")img = cv2.imread(imgName)cv2.imwrite("temp/original.jpg", img)height, width, pixels = img.shapeprint("width,height",width,height)print("self.label.width()",self.label.width())print("self.label.height()",self.label.height())if width>(self.label.width()):rheight=(self.label.width()*height)*widthrwidth=self.label.width()print("rwidth-if,rheight-if", width, rheight)elif height>(self.label.height()):rwidth=(self.label.height()*width)/heightrheight=self.label.height()print("rwidth-elif,rheight-elfi", rwidth, rheight)elif ((self.label.height())-height)<((self.label.width())-width):rwidth=(self.label.height()*width)/heightrheight=self.label.height()print("rwidth-elif,rheight-elfi", rwidth, rheight)else:print("rheight,rwidth", height, width)rheight = heightrwidth = widthframe = cv2.resize(img, (int(rwidth), int(rheight)))print("rwidth-elif,rheight-elfi", rwidth, rheight)img2 = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)  # opencv读取的bgr格式图片转换成rgb格式_image = QtGui.QImage(img2[:], img2.shape[1], img2.shape[0], img2.shape[1] * 3, QtGui.QImage.Format_RGB888)jpg_out = QtGui.QPixmap(_image).scaled(rwidth, rheight) #设置图片大小self.label.setPixmap(jpg_out) #设置图片显示def saveFileButton(self):img = cv2.imread("temp/original.jpg")file_path = QFileDialog.getSaveFileName(self, "save file", "./save/test","jpg files (*.jpg);;all files(*.*)")print(file_path[0])cv2.imwrite(file_path[0], img)cv2.waitKey(0)cv2.destroyAllWindows()def fingerContrast(self):# 均值哈希算法def aHash(img):# 缩放为8*8img = cv2.resize(img, (8, 8), interpolation=cv2.INTER_CUBIC)# 转换为灰度图gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)# s为像素和初值为0，hash_str为hash值初值为''s = 0hash_str = ''# 遍历累加求像素和for i in range(8):for j in range(8):s = s + gray[i, j]# 灰度大于平均值为1相反为0生成图片的hash值for i in range(8):for j in range(8):if gray[i, j] > avg:hash_str = hash_str + '1'else:hash_str = hash_str + '0'return hash_str# 差值感知算法def dHash(img):# 缩放8*8img = cv2.resize(img, (9, 8), interpolation=cv2.INTER_CUBIC)# 转换灰度图gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)hash_str = ''# 每行前一个像素大于后一个像素为1，相反为0，生成哈希for i in range(8):for j in range(8):if gray[i, j] > gray[i, j + 1]:hash_str = hash_str + '1'else:hash_str = hash_str + '0'return hash_str# Hash值对比def cmpHash(hash1, hash2):n = 0# hash长度不同则返回-1代表传参出错if len(hash1) != len(hash2):return -1# 遍历判断for i in range(len(hash1)):# 不相等则n计数+1，n最终为相似度if hash1[i] != hash2[i]:n = n + 1return nimport ospath = "palmDataBase/"file_list = os.listdir(path)for file in file_list:img1 = cv2.imread('temp/original.jpg')BasePath="palmDataBase/" + str(file)print("BasePath: ", BasePath)img2 = cv2.imread(BasePath)print("img2: ",img2)print(hash2)n = cmpHash(hash1, hash2)print('均值哈希算法相似度：' + str(n))print('差值哈希算法相似度：' + str(n))result='相似度：' + str(100-n)+", 通过"if n < 5:print("file:",file)self.textEdit.setPlainText(result)self.textEdit_2.setPlainText("匹配成功名称："+file)print("n: ",n)if width > (self.label.width()):rheight = (self.label.width() * height) * widthrwidth = self.label.width()print("rwidth-if,rheight-if", width, rheight)elif height > (self.label.height()):rwidth = (self.label.height() * width) / heightrheight = self.label.height()print("rwidth-elif,rheight-elfi", rwidth, rheight)elif ((self.label.height()) - height) < ((self.label.width()) - width):rwidth = (self.label.height() * width) / heightrheight = self.label.height()print("rwidth-elif,rheight-elfi", rwidth, rheight)else:print("rheight,rwidth", height, width)rheight = heightrwidth = widthframe = cv2.resize(img2, (int(rwidth), int(rheight)))print("rwidth-elif,rheight-elfi", rwidth, rheight)img2 = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)  # opencv读取的bgr格式图片转换成rgb格式_image = QtGui.QImage(img2[:], img2.shape[1], img2.shape[0], img2.shape[1] * 3,QtGui.QImage.Format_RGB888)jpg_out = QtGui.QPixmap(_image).scaled(rwidth, rheight)  # 设置图片大小self.label_2.setPixmap(jpg_out)  # 设置图片显示breakelse:print("n: ", n)self.textEdit.setPlainText("相似度太低，不通过")self.textEdit_2.setPlainText(" ")self.label_2.setPixmap(QPixmap(""))if __name__=="__main__":app=QtWidgets.QApplication(sys.argv)Widget=myWin()Widget.showMaximized();Widget.show()sys.exit(app.exec_())