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main.py

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+import sys
+
+import cv2
+from PyQt5.QtCore import pyqtSignal
+from PyQt5.QtCore import QThread
+from PyQt5.QtWidgets import QFileDialog, QMessageBox
+from PyQt5 import QtWidgets, QtGui
+import numpy as np
+
+import model
+import utils
+from GUI import Ui_MainWindow
+import tensorflow.compat.v1 as tf
+
+
+def cnn(picture_name):
+    picture_name = cv2.imread(picture_name)
+    image = cv2.resize(picture_name, (utils.IMAGE_WIDTH, utils.IMAGE_HEIGHT))
+
+    normalizer_image = image / 255.0 - 0.5
+
+    image = np.array(normalizer_image)
+
+    x, _, _, result = model.get_model(is_train=False, keep_prob=1)
+
+    with tf.Session() as sess:
+        pics = []
+        saver = tf.train.Saver()
+        saver.restore(sess, "./result/result.ckpt")
+        pics.append(image)
+        # 概率
+        prediction = sess.run(result, feed_dict={x: pics})
+        # 类别
+        pred_result = np.argmax(prediction)
+    return pred_result, prediction
+
+
+class dpv_thread(QThread):  # 检测的线程
+    img_breakSignal = pyqtSignal(int)
+
+    def __init__(self, parent=None):
+        super(dpv_thread, self).__init__()
+
+    def run(self):
+        global picture_name, pred_result, prediction
+        pred_result, prediction = cnn(picture_name)
+        self.img_breakSignal.emit(prediction)
+
+
+class HelmetWindow(QtWidgets.QMainWindow, Ui_MainWindow):
+    def __init__(self):
+        super(HelmetWindow, self).__init__()
+        self.setupUi(self)
+        self.setWindowTitle("花花检测")  # 设置窗口程序标题
+        self.setStyleSheet("#MainWindow{background-color:lightskyblue}")
+
+        self.read_img.clicked.connect(self.Read_img)
+        self.start_detect.clicked.connect(self.Start_detect)
+        self.show_img.setScaledContents(True)
+        self.DPV_thread = dpv_thread()  # 实例化检测
+        self.DPV_thread.img_breakSignal.connect(self.Show_text)
+
+    def Read_img(self):
+        global picture_name
+        picture_name, imgType = QFileDialog.getOpenFileName(self, "打开图片", "", "*.jpg;;*.png;;All Files(*)")
+        jpg = QtGui.QPixmap(picture_name).scaled(self.show_img.width(), self.show_img.height())
+        self.show_img.setPixmap(jpg)
+        print(picture_name)
+        if picture_name == '':
+            return '图片打开失败'
+
+    def Start_detect(self):
+        self.DPV_thread.start()
+
+    def Show_text(self):
+        global pred_result, prediction
+        if pred_result == 0:
+            show = ('桃花： %.2f' % prediction[:, 0])
+        elif pred_result == 1:
+            show = ('梅花： %.2f' % prediction[:, 1])
+        elif pred_result == 2:
+            show = ('牡丹： %.2f' % prediction[:, 2])
+        elif pred_result == 3:
+            show = ('牵牛花： %.2f' % prediction[:, 3])
+        elif pred_result == 4:
+            show = ('玫瑰： %.2f' % prediction[:, 4])
+        elif pred_result == 5:
+            show = ('茉莉： %.2f' % prediction[:, 5])
+        else:
+            show = ('蒲公英： %.2f' % prediction[:, 6])
+        self.show_text.append(show)
+
+    def closeEvent(self, event):  # 关闭窗口响应函数，在这里面弹出确认框，并销毁线程
+        reply = QMessageBox.question(self,
+                                     '本程序',
+                                     "是否要退出程序？",
+                                     QMessageBox.Yes | QMessageBox.No,
+                                     QMessageBox.No)
+        if reply == QMessageBox.Yes:
+            event.accept()
+        else:
+            event.ignore()
+
+    def mousePressEvent(self, QMouseEvent):
+        if self.isMaximized():
+            self.showNormal()
+        else:
+            self.showMaximized()
+
+
+if __name__ == '__main__':
+    app = QtWidgets.QApplication(sys.argv)
+    ui = HelmetWindow()
+    ui.show()
+    sys.exit(app.exec_())