桌面客户端点击加载图片，右侧显示加载图片压缩后图片，点击人脸识别按钮，右侧图片框出人脸范围,使用qt生成gui，给出完整python代码

以下是一个简单的使用Qt生成GUI的Python代码，实现了加载图片、压缩图片和人脸识别等功能：

import sys
import cv2
import numpy as np
from PyQt5.QtWidgets import QApplication, QWidget, QVBoxLayout, QHBoxLayout, QLabel, QPushButton, QFileDialog
from PyQt5.QtGui import QPixmap, QImage
from PyQt5.QtCore import Qt

class FaceRecognition(QWidget):
    def __init__(self):
        super().__init__()
        self.initUI()

    def initUI(self):
        # 初始化UI界面
        self.setWindowTitle('人脸识别')
        self.setGeometry(300, 300, 800, 500)

        # 创建控件
        self.label_original = QLabel('原图')
        self.label_original.setAlignment(Qt.AlignCenter)
        self.label_original.setFixedSize(300, 300)
        self.label_compressed = QLabel('压缩图')
        self.label_compressed.setAlignment(Qt.AlignCenter)
        self.label_compressed.setFixedSize(300, 300)
        self.label_result = QLabel('识别结果')
        self.label_result.setAlignment(Qt.AlignCenter)
        self.label_result.setFixedSize(300, 300)
        self.btn_load = QPushButton('加载图片')
        self.btn_compress = QPushButton('压缩图片')
        self.btn_recognize = QPushButton('人脸识别')

        # 创建布局
        layout_main = QHBoxLayout()
        layout_left = QVBoxLayout()
        layout_right = QVBoxLayout()
        layout_left.addWidget(self.label_original)
        layout_left.addWidget(self.btn_load)
        layout_left.addWidget(self.btn_compress)
        layout_right.addWidget(self.label_compressed)
        layout_right.addWidget(self.btn_recognize)
        layout_right.addWidget(self.label_result)
        layout_main.addLayout(layout_left)
        layout_main.addLayout(layout_right)
        self.setLayout(layout_main)

        # 绑定事件
        self.btn_load.clicked.connect(self.load_image)
        self.btn_compress.clicked.connect(self.compress_image)
        self.btn_recognize.clicked.connect(self.recognize_face)

    def load_image(self):
        # 加载图片
        fname, _ = QFileDialog.getOpenFileName(self, 'Open file', './')
        if fname:
            img = cv2.imread(fname)
            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
            h, w, ch = img.shape
            bytesPerLine = ch * w
            qimg = QImage(img.data, w, h, bytesPerLine, QImage.Format_RGB888)
            pixmap = QPixmap.fromImage(qimg)
            self.label_original.setPixmap(pixmap)

            # 保存原图
            self.image_original = img

    def compress_image(self):
        # 压缩图片
        if hasattr(self, 'image_original'):
            self.image_compressed = cv2.resize(self.image_original, (300, 300))
            h, w, ch = self.image_compressed.shape
            bytesPerLine = ch * w
            qimg = QImage(self.image_compressed.data, w, h, bytesPerLine, QImage.Format_RGB888)
            pixmap = QPixmap.fromImage(qimg)
            self.label_compressed.setPixmap(pixmap)

    def recognize_face(self):
        # 人脸识别
        if hasattr(self, 'image_compressed'):
            face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
            gray = cv2.cvtColor(self.image_compressed, cv2.COLOR_BGR2GRAY)
            faces = face_cascade.detectMultiScale(gray, 1.3, 5)
            for (x, y, w, h) in faces:
                cv2.rectangle(self.image_compressed, (x, y), (x + w, y + h), (0, 255, 0), 2)
            h, w, ch = self.image_compressed.shape
            bytesPerLine = ch * w
            qimg = QImage(self.image_compressed.data, w, h, bytesPerLine, QImage.Format_RGB888)
            pixmap = QPixmap.fromImage(qimg)
            self.label_result.setPixmap(pixmap)

if __name__ == '__main__':
    app = QApplication(sys.argv)
    ex = FaceRecognition()
    ex.show()
    sys.exit(app.exec_())

需要注意的是，上述代码中的人脸识别使用了OpenCV库的CascadeClassifier类，需要使用对应的训练数据文件haarcascade_frontalface_default.xml，可以在OpenCV官网下载。在代码中使用时需要将其放在与Python文件同一目录下。