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_())