基于resnet和python的动物图像分类系统.zip

import torch from PyQt5.QtGui import * from PyQt5.QtCore import * from PyQt5.QtWidgets import * import sys import cv2 from PIL import Image import numpy as np import shutil from predict import predict class MainWindow(QTabWidget): # 初始化 def __init__(self): super().__init__() self.setWindowIcon(QIcon('images/logo.jpg')) self.setWindowTitle('动物识别系统') # todo 修改系统名称 # 模型初始化 self.model = torch.load("output/resnet18_e_best.pth") # todo 修改模型名称 self.to_predict_name = "horse.png" # todo 修改初始图片，这个图片要放在images目录下 self.class_names = ['猫', '牛', '狗', '马', '羊'] # todo 修改类名，这个数组在模型训练的开始会输出 self.resize(900, 700) self.initUI() # 界面初始化，设置界面布局 def initUI(self): main_widget = QWidget() main_layout = QHBoxLayout() font = QFont('黑体', 15) # 主页面，设置组件并在组件放在布局上 left_widget = QWidget() left_layout = QVBoxLayout() img_title = QLabel("样本") img_title.setFont(font) img_title.setAlignment(Qt.AlignCenter) self.img_label = QLabel() img_init = cv2.imread(self.to_predict_name) h, w, c = img_init.shape scale = 400 / h img_show = cv2.resize(img_init, (0, 0), fx=scale, fy=scale) cv2.imwrite("images/show.png", img_show) img_init = cv2.resize(img_init, (224, 224)) cv2.imwrite('images/target.png', img_init) self.img_label.setPixmap(QPixmap("images/show.png")) left_layout.addWidget(img_title) left_layout.addWidget(self.img_label, 1, Qt.AlignCenter) left_widget.setLayout(left_layout) right_widget = QWidget() right_layout = QVBoxLayout() btn_change = QPushButton(" 上传图片 ") btn_change.clicked.connect(self.change_img) btn_change.setFont(font) btn_predict = QPushButton(" 开始识别 ") btn_predict.setFont(font) btn_predict.clicked.connect(self.predict_img) label_result = QLabel(' 动物名称 ') self.result = QLabel("等待识别") label_result.setFont(QFont('黑体', 16)) self.result.setFont(QFont('黑体', 24)) right_layout.addStretch() right_layout.addWidget(label_result, 0, Qt.AlignCenter) right_layout.addStretch() right_layout.addWidget(self.result, 0, Qt.AlignCenter) right_layout.addStretch() right_layout.addStretch() right_layout.addWidget(btn_change) right_layout.addWidget(btn_predict) right_layout.addStretch() right_widget.setLayout(right_layout) main_layout.addWidget(left_widget) main_layout.addWidget(right_widget) main_widget.setLayout(main_layout) # 关于页面，设置组件并把组件放在布局上 about_widget = QWidget() about_layout = QVBoxLayout() about_title = QLabel('欢迎使用动物识别系统') # todo 修改欢迎词语 about_title.setFont(QFont('黑体', 18)) about_title.setAlignment(Qt.AlignCenter) about_img = QLabel() about_img.setPixmap(QPixmap('images/bj.png')) about_img.setAlignment(Qt.AlignCenter) label_super = QLabel("作者：by lhy in HFUT") # todo 更换作者信息 label_super.setFont(QFont('黑体', 12)) # label_super.setOpenExternalLinks(True) label_super.setAlignment(Qt.AlignRight) about_layout.addWidget(about_title) about_layout.addStretch() about_layout.addWidget(about_img) about_layout.addStretch() about_layout.addWidget(label_super) about_widget.setLayout(about_layout) # 添加注释 self.addTab(main_widget, '主页') self.addTab(about_widget, '关于') self.setTabIcon(0, QIcon('images/主页面.png')) self.setTabIcon(1, QIcon('images/关于.png')) # 上传并显示图片 def change_img(self): openfile_name = QFileDialog.getOpenFileName(self, 'chose files', '', 'Image files(*.jpg *.png *jpeg)') # 打开文件选择框选择文件 img_name = openfile_name[0] # 获取图片名称 if img_name == '': pass else: target_image_name = "images/tmp_up." + img_name.split(".")[-1] # 将图片移动到当前目录 shutil.copy(img_name, target_image_name) self.to_predict_name = target_image_name img_init = cv2.imread(self.to_predict_name) # 打开图片 h, w, c = img_init.shape scale = 400 / h img_show = cv2.resize(img_init, (0, 0), fx=scale, fy=scale) # 将图片的大小统一调整到400的高，方便界面显示 cv2.imwrite("images/show.png", img_show) img_init = cv2.resize(img_init, (224, 224)) # 将图片大小调整到224*224用于模型推理 cv2.imwrite('images/target.png', img_init) self.img_label.setPixmap(QPixmap("images/show.png")) self.result.setText("等待识别") # 预测图片 def predict_img(self): result_index = predict() result = self.class_names[result_index] # 获得对应的动物名称 self.result.setText(result) # 在界面上做显示 # 界面关闭事件，询问用户是否关闭 def closeEvent(self, event): reply = QMessageBox.question(self, '退出', "是否要退出程序？", QMessageBox.Yes | QMessageBox.No, QMessageBox.No) if reply == QMessageBox.Yes: self.close() event.accept() else: event.ignore() if __name__ == "__main__": app = QApplication(sys.argv) x = MainWindow() x.show() sys.exit(app.exec_())