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import shutil
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import threading
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import sys
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import cv2
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import numpy as np
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from PyQt5.QtGui import *
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from PyQt5.QtCore import *
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from PyQt5.QtWidgets import *
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import os.path as osp
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class MainWindow(QTabWidget):
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def __init__(self):
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# 初始化界面
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super().__init__()
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self.load_custom_font()
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self.setWindowTitle('华东师范大学校园卡检测系统')
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self.resize(1200, 800)
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self.setWindowIcon(QIcon("images/UI/ECNU.png"))
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# 图片读取进程
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self.cab=None
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self.stopEvent = threading.Event()
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self.stopEvent.clear()
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self.output_size = 1000
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self.img2predict = ""
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self.initUI()
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self.webcam=False
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self.reset_vid()
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def load_custom_font(self):
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# 加载自定义字体文件
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font_id = QFontDatabase.addApplicationFont('font/OPPOSans-H-2.ttf')
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if font_id != -1:
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self.font_family = QFontDatabase.applicationFontFamilies(font_id)[0]
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else:
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self.font_family = '楷体' # 备用字体
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def initUI(self):
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# 图片检测子界面
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font_title = QFont(self.font_family, 16)
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font_main = QFont(self.font_family, 14)
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# 图片识别界面, 两个按钮，上传图片和显示结果
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img_detection_widget = QWidget()
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img_detection_layout = QVBoxLayout()
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img_detection_title = QLabel("图片检测功能")
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img_detection_title.setFont(font_title)
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mid_img_widget = QWidget()
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mid_img_layout = QHBoxLayout()
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self.left_img = QLabel()
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self.right_img = QLabel()
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self.left_img.setPixmap(QPixmap("images/UI/touxiang.png"))
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self.right_img.setPixmap(QPixmap("images/UI/touxiang2.png"))
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self.left_img.setAlignment(Qt.AlignCenter)
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self.right_img.setAlignment(Qt.AlignCenter)
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mid_img_layout.addWidget(self.left_img)
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mid_img_layout.addStretch(0)
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mid_img_layout.addWidget(self.right_img)
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mid_img_widget.setLayout(mid_img_layout)
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up_img_button = QPushButton("上传图片")
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det_img_button = QPushButton("开始检测")
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up_img_button.clicked.connect(self.upload_img)
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det_img_button.clicked.connect(self.detect_img)
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up_img_button.setFont(font_main)
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det_img_button.setFont(font_main)
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up_img_button.setStyleSheet("QPushButton{color:white}"
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"QPushButton:hover{background-color: rgb(2,110,180);}"
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"QPushButton{background-color:rgb(48,124,208)}"
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"QPushButton{border:2px}"
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"QPushButton{border-radius:5px}"
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"QPushButton{padding:5px 5px}"
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"QPushButton{margin:5px 5px}")
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det_img_button.setStyleSheet("QPushButton{color:white}"
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"QPushButton:hover{background-color: rgb(2,110,180);}"
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"QPushButton{background-color:rgb(48,124,208)}"
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"QPushButton{border:2px}"
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"QPushButton{border-radius:5px}"
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"QPushButton{padding:5px 5px}"
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"QPushButton{margin:5px 5px}")
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img_detection_layout.addWidget(img_detection_title, alignment=Qt.AlignCenter)
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img_detection_layout.addWidget(mid_img_widget, alignment=Qt.AlignCenter)
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img_detection_layout.addWidget(up_img_button)
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img_detection_layout.addWidget(det_img_button)
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img_detection_widget.setLayout(img_detection_layout)
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# 视频识别界面
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vid_detection_widget = QWidget()
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vid_detection_layout = QVBoxLayout()
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vid_title = QLabel("视频检测功能")
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vid_title.setFont(font_title)
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self.vid_img = QLabel()
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self.vid_img.setPixmap(QPixmap("images/UI/logo.png"))
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vid_title.setAlignment(Qt.AlignCenter)
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self.vid_img.setAlignment(Qt.AlignCenter)
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self.webcam_detection_btn = QPushButton("摄像头实时监测")
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self.mp4_detection_btn = QPushButton("视频文件检测")
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self.vid_stop_btn = QPushButton("停止检测")
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self.webcam_detection_btn.setFont(font_main)
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self.mp4_detection_btn.setFont(font_main)
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self.vid_stop_btn.setFont(font_main)
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self.webcam_detection_btn.setStyleSheet("QPushButton{color:white}"
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"QPushButton:hover{background-color: rgb(2,110,180);}"
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"QPushButton{background-color:rgb(48,124,208)}"
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"QPushButton{border:2px}"
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"QPushButton{border-radius:5px}"
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"QPushButton{padding:5px 5px}"
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"QPushButton{margin:5px 5px}")
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self.mp4_detection_btn.setStyleSheet("QPushButton{color:white}"
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"QPushButton:hover{background-color: rgb(2,110,180);}"
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"QPushButton{background-color:rgb(48,124,208)}"
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"QPushButton{border:2px}"
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"QPushButton{border-radius:5px}"
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"QPushButton{padding:5px 5px}"
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"QPushButton{margin:5px 5px}")
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self.vid_stop_btn.setStyleSheet("QPushButton{color:white}"
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"QPushButton:hover{background-color: rgb(2,110,180);}"
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"QPushButton{background-color:rgb(48,124,208)}"
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"QPushButton{border:2px}"
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"QPushButton{border-radius:5px}"
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"QPushButton{padding:5px 5px}"
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"QPushButton{margin:5px 5px}")
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self.webcam_detection_btn.clicked.connect(self.open_cam)
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self.mp4_detection_btn.clicked.connect(self.open_mp4)
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self.vid_stop_btn.clicked.connect(self.close_vid)
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# 添加组件到布局上
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vid_detection_layout.addWidget(vid_title)
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vid_detection_layout.addWidget(self.vid_img)
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vid_detection_layout.addWidget(self.webcam_detection_btn)
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vid_detection_layout.addWidget(self.mp4_detection_btn)
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vid_detection_layout.addWidget(self.vid_stop_btn)
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vid_detection_widget.setLayout(vid_detection_layout)
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self.left_img.setAlignment(Qt.AlignCenter)
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self.addTab(img_detection_widget, '图片检测')
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self.addTab(vid_detection_widget, '视频检测')
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self.setTabIcon(0, QIcon('images/UI/logo.png'))
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self.setTabIcon(1, QIcon('images/UI/logo.png'))
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# 上传图片
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def upload_img(self):
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fileName, fileType = QFileDialog.getOpenFileName(self, 'Choose file', '', '*.jpg *.png *.tif *.jpeg')
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if fileName:
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suffix = fileName.split(".")[-1]
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save_path = osp.join("images/tmp", "original_image." + suffix)
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shutil.copy(fileName, save_path)
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# 应该调整一下图片的大小，然后统一放在一起
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im0 = cv2.imread(save_path)
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new_height = 400 * im0.shape[0] / im0.shape[1]
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im0 = cv2.resize(im0, (400, int(new_height)), interpolation=cv2.INTER_CUBIC)
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cv2.imwrite("images/tmp/compressed_image.jpg", im0)
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self.img2predict = "images/tmp/compressed_image.jpg"
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self.left_img.setPixmap(QPixmap("images/tmp/compressed_image.jpg"))
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# 上传图片之后右侧的图片重置，
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self.right_img.setPixmap(QPixmap("images/UI/touxiang2.png"))
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def find_campus_card(self,bgr_image):
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# 预处理图像，对图像进行压缩，便于之后处理
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image_height, image_width = bgr_image.shape[:2]
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# 掩膜匹配白色区域
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hsv = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2HSV)
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lower_white = np.array([0, 0, 170])
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upper_white = np.array([180, 80, 255])
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mask = cv2.inRange(hsv, lower_white, upper_white)
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# 开运算去除噪声
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kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
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mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
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# 高斯滤波,减少噪声和增强主要结构
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blur_mask = cv2.GaussianBlur(mask, (3, 3), 0)
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gradx = cv2.Sobel(blur_mask, cv2.CV_16SC1, 1, 0)
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grady = cv2.Sobel(blur_mask, cv2.CV_16SC1, 0, 1)
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# canny边缘检测
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edges = cv2.Canny(gradx, grady, 50, 150)
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contours, _ = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_TC89_L1)
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best_contour = None
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best_rect = None
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best_ratio_diff = float('inf')
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desired_ratio = 2.5
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min_area = 0.05 * image_width * image_height
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for contour in contours:
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epsilon = 0.02 * cv2.arcLength(contour, True)
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approx = cv2.approxPolyDP(contour, epsilon, True)
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# 获取最小外接矩形
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rect = cv2.minAreaRect(approx)
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(width, height) = rect[1]
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if width == 0 or height == 0:
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continue
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# 计算长宽比
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if width < height:
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ratio = height / width
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else:
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ratio = width / height
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# 计算矩形面积
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area = width * height
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# 计算与期望比例的差异
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ratio_diff = abs(ratio - desired_ratio)
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# 更新最优轮廓
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if ratio_diff < best_ratio_diff and area >= min_area:
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best_contour = approx
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best_rect = rect
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best_ratio_diff = ratio_diff
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if best_rect is not None:
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# 获取最小外接矩形的顶点
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box = cv2.boxPoints(best_rect)
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box = np.intp(box)
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# 在图像上绘制矩形
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cv2.drawContours(bgr_image, [box], 0, (0, 0, 255), 2)
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angle = best_rect[2]
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if best_rect[1][0] < best_rect[1][1]:
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angle -= 90
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return bgr_image, box, angle
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else:
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return bgr_image, None,None
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def background_remove(self,afterimg, box):
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# 创建一个与原始图像大小相同的掩膜图像，初始为全白（255）
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mask = np.ones_like(afterimg) * 0
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# 将矩形区域填充为黑色
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cv2.drawContours(mask, [box], 0, (255, 255, 255), -1)
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# 将掩膜图像与原始图像进行按位与操作，保留矩形区域为彩色，其他区域变为黑色
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result = cv2.bitwise_and(afterimg, mask)
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return result
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def rotate_image(self,image, angle):
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# 获取图像中心点
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center = tuple(np.array(image.shape[1::-1]) / 2)
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# 计算旋转矩阵
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rotation_matrix = cv2.getRotationMatrix2D(center, angle, 1.0)
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# 进行仿射变换
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rotated_image = cv2.warpAffine(image, rotation_matrix, image.shape[1::-1], flags=cv2.INTER_LINEAR)
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return rotated_image
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def detect_img(self):
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source = self.img2predict
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if source == "":
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QMessageBox.warning(self, "请上传", "请先上传图片再进行检测")
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else:
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bgr_image = cv2.imread(source)
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processed_image, box, rotation_angle = self.find_campus_card(bgr_image)
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cv2.imwrite("images/tmp/find_card_image.jpg", processed_image)
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if box is not None:
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background_remove_img = self.background_remove(processed_image, box)
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rotated_image = self.rotate_image(background_remove_img, rotation_angle)
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cv2.imwrite("images/tmp/result_image.jpg", rotated_image)
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self.left_img.setPixmap(QPixmap("images/tmp/find_card_image.jpg"))
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self.right_img.setPixmap(QPixmap("images/tmp/result_image.jpg"))
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else:
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self.right_img.setPixmap(QPixmap("images/UI/error2.png"))
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def open_cam(self):
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self.webcam_detection_btn.setEnabled(False) # 禁用检测按钮
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self.mp4_detection_btn.setEnabled(False) # 禁用 MP4 检测按钮
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self.vid_stop_btn.setEnabled(True) # 启用停止按钮
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self.cap = cv2.VideoCapture(0)
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self.webcam=True
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th = threading.Thread(target=self.process_video) # 创建一个新的线程
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th.start() # 启动新线程
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def open_mp4(self):
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fileName, fileType = QFileDialog.getOpenFileName(self, 'Choose file', '', '*.mp4 *.avi *.mov')
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if fileName:
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self.webcam_detection_btn.setEnabled(False)
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self.mp4_detection_btn.setEnabled(False)
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self.vid_stop_btn.setEnabled(True) # 启用停止按钮
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self.cap = cv2.VideoCapture(fileName)
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th = threading.Thread(target=self.process_video) # 创建一个新的线程
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th.start() # 启动新线程
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def process_video(self):
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while True:
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ret, frame = self.cap.read()
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if self.webcam:
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frame = cv2.flip(frame, 1)
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if ret:
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new_height = 400 * frame.shape[0] / frame.shape[1]
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frame = cv2.resize(frame, (400, int(new_height)), interpolation=cv2.INTER_CUBIC)
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processed_image, box, rotation_angle = self.find_campus_card(frame)
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cv2.imwrite("images/tmp/processed_video_image.jpg", processed_image)
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self.vid_img.setPixmap(QPixmap("images/tmp/processed_video_image.jpg"))
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if self.stopEvent.is_set() == True:
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self.stopEvent.clear()
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break
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def closeEvent(self, event):
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reply = QMessageBox.question(self,'退出',"是否退出？",QMessageBox.Yes | QMessageBox.No,QMessageBox.No)
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if reply == QMessageBox.Yes:
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self.close()
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event.accept()
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else:
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event.ignore()
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# 界面重置
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def reset_vid(self):
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self.webcam=False
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self.webcam_detection_btn.setEnabled(True)
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self.mp4_detection_btn.setEnabled(True)
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self.vid_img.setPixmap(QPixmap("images/UI/logo.png"))
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# 视频重置
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def close_vid(self):
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if self.cap:
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self.cap.release()
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self.stopEvent.set()
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self.reset_vid()
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if __name__ == "__main__":
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app = QApplication(sys.argv)
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mainWindow = MainWindow()
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mainWindow.show()
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sys.exit(app.exec_()) |
