Parcurcik's questions

我在编写游戏时遇到了问题。逻辑已准备就绪，即按钮随机生成 6 个点。（下图）必须使其有图像，而不是出现带有“目标”字样的按钮。按钮是通过定时器编写的，代码如下：

        {
            isHit = false;
            btn_click.Enabled = true;
            btn_click.BackColor = System.Drawing.Color.Transparent;

            locationNum = rnd.Next(1, 7);


            switch (locationNum)
            {
                case 1:
                    btn_click.Left = 186;
                    btn_click.Top = 297;
                    break;

                case 2:
                    btn_click.Left = 43;
                    btn_click.Top = 327;
                    break;

                case 3:
                    btn_click.Left = 325;
                    btn_click.Top = 333;
                    break;

                case 4:
                    btn_click.Left = 60;
                    btn_click.Top = 402;
                    break;

                case 5:
                    btn_click.Left = 309;
                    btn_click.Top = 406;
                    break;

                case 6:
                    btn_click.Left = 187;
                    btn_click.Top = 450;
                    break;

                default:
                    break;
            }
        }

.

要上传到 GitHub，您需要删除 .idea 和pycache 文件夹，但将它们添加到 gitignore.txt 不起作用。

如何将“端口范围”表格向下移动？

const sendMessage = () => {
        alert('Please wait for the scanning!');
    }

html {
            font-family: Verdana, "sans-serif";
        }

        body {
            min-height: 100vh;
            background: black no-repeat;
        }

        h1 {
            text-align: center;
            color: white;
            text-shadow: 0 3px 5px rgba(150, 150, 150, 0.8);
        }

        #root {
            display: flex;
            flex-direction: column;
            align-items: center;
        }

        #messages {
            width: 70%;
        }

        .message {
            background-color: white;
            width: 100%;
            padding: 20px;
            border-radius: 10px;
            -webkit-transition: 0.3s;
            -moz-transition: 0.3s;
            transition: 0.3s;
            -webkit-box-shadow: 0px 5px 5px 0px rgba(0, 0, 0, 0.1);
            -moz-box-shadow: 0px 5px 5px 0px rgba(0, 0, 0, 0.1);
            box-shadow: 0px 5px 5px 0px rgba(0, 0, 0, 0.1);
            box-sizing: border-box;
            margin-bottom: 10px;
        }

        .message:hover {
            -webkit-transition: 0.3s;
            -moz-transition: 0.3s;
            transition: 0.3s;
            -webkit-box-shadow: 0 5px 5px 0 rgba(0, 0, 0, 0.5);
            -moz-box-shadow: 0 5px 5px 0 rgba(0, 0, 0, 0.5);
            box-shadow: 0 5px 5px 0 rgba(0, 0, 0, 0.5);
        }

        .message__created {
            font-size: 12px;
            color: darkgrey;
            text-align: right;
        }

        .message__text {
            font-size: 20px;
            color: black;
            margin-top: 5px;
        }

        .message__ratings {
            display: flex;
            justify-content: space-between;
            font-size: 16px;
            font-weight: 400;
            margin-top: 5px;
        }

        .form {
            width: 70%;
            margin-bottom: 20px;
        }

        .form__button {
            text-align: center;
            margin-top: 150px;
            background-color: white;
            cursor: pointer;
        }

        .form__input, .form__button {
            box-sizing: border-box;
            width: 100%;
            font-size: 18px;
            outline: none;
            border: none;
            padding: 20px;
            border-radius: 15px;
            -webkit-transition: 0.3s;
            -moz-transition: 0.3s;
            transition: 0.3s;
            -webkit-box-shadow: 0px 5px 5px 0px rgba(0, 0, 0, 0.1);
            -moz-box-shadow: 0px 5px 5px 0px rgba(0, 0, 0, 0.1);
            box-shadow: 0px 5px 5px 0px rgba(0, 0, 0, 0.1);
        }

        .form__input:focus, .form__button:hover {
            -webkit-transition: 0.3s;
            -moz-transition: 0.3s;
            transition: 0.3s;
            -webkit-box-shadow: 0 5px 5px 0 rgba(0, 0, 0, 0.5);
            -moz-box-shadow: 0 5px 5px 0 rgba(0, 0, 0, 0.5);
            box-shadow: 0 5px 5px 0 rgba(0, 0, 0, 0.5);
        }

<div>
    <h1>Port Scanner</h1>
    <div id="root">
        <div class="form">
            <input id="message_text" class="form__input" type="text"
                   placeholder="IP adress"/>
            <input id="message_text1" class="form__input" type="text"
                   placeholder="Range of ports"/>
            <div class="form__button" onclick="sendMessage()">Scan</div>
        </div>
        <div id="messages">

        </div>
    </div>
</div>

我正在实现一个 Web 应用程序，但是在服务器上显示 html 时遇到了一些问题。这是 index.html 文件预览的样子。

<!DOCTYPE html>
<html style="font-size: 16px;">
  <head>
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <meta charset="utf-8">
    <meta name="keywords" content="Port Scanner">
    <meta name="description" content="">
    <title>Port Scanner</title>
    <link rel="stylesheet" href="nicepage.css" media="screen">
<link rel="stylesheet" href="Главная.css" media="screen">
    <script class="u-script" type="text/javascript" src="jquery.js" defer=""></script>
    <script class="u-script" type="text/javascript" src="nicepage.js" defer=""></script>
    <meta name="generator" content="Nicepage 4.12.5, nicepage.com">
    <link id="u-theme-google-font" rel="stylesheet" href="https://fonts.googleapis.com/css?family=Roboto:100,100i,300,300i,400,400i,500,500i,700,700i,900,900i|Open+Sans:300,300i,400,400i,500,500i,600,600i,700,700i,800,800i">
    <link id="u-page-google-font" rel="stylesheet" href="https://fonts.googleapis.com/css?family=Abril+Fatface:400|Architects+Daughter:400">
    
    
    
    <script type="application/ld+json">{
        "@context": "http://schema.org",
        "@type": "Organization",
        "name": ""
}</script>
    <meta name="theme-color" content="#478ac9">
    <meta property="og:title" content="Главная">
    <meta property="og:type" content="website">
  </head>
  <body data-home-page="index.html" data-home-page-title="Главная" class="u-body u-xl-mode">
    <section class="u-black u-clearfix u-section-1" id="sec-5016">
      <div class="u-clearfix u-sheet u-sheet-1">
        <h1 class="u-align-center u-custom-font u-text u-text-1">Port Scanner<br>
        </h1>
        <p class="u-align-center u-custom-font u-text u-text-2">IP adress</p>
        <div class="u-shape u-shape-rectangle u-white u-shape-1"></div>
        <p class="u-align-center u-custom-font u-text u-text-3">Range of ports</p>
        <div class="u-shape u-shape-rectangle u-white u-shape-2"></div>
        <p class="u-align-center u-custom-font u-text u-text-body-color u-text-4">SCAN</p>
        <a href="https://nicepage.com/joomla-page-builder" class="u-border-2 u-border-white u-btn u-btn-round u-button-style u-radius-50 u-white u-btn-1">SCAN</a>
      </div>
    </section>
    <section class="u-clearfix u-section-2" id="sec-c87d">
      <div class="u-clearfix u-sheet u-sheet-1"></div>
    </section>
    
    
    
    <section class="u-backlink u-clearfix u-grey-80">
      <a class="u-link" href="https://nicepage.com/website-templates" target="_blank">
        <span>Website Templates</span>
      </a>
      <p class="u-text">
        <span>created with</span>
      </p>
      <a class="u-link" href="" target="_blank">
        <span>Website Builder Software</span>
      </a>. 
    </section>
  </body>
</html>

但是，当我转到服务器时，会出现： upd 控制台：

upd2 应用结构

输出是 ['XXXXXX'] 格式，我怎样才能使它成为 XXXXXX 格式，没有括号和撇号？

letters = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'E', 'H', 'K', 'M', 'O', 'P', 'T', 'X', 'Y']


def decode_batch(out):
    ret = []
    for j in range(out.shape[0]):
        out_best = list(np.argmax(out[j, 2:], 1))
        out_best = [k for k, g in itertools.groupby(out_best)]
        outstr = ''
        for c in out_best:
            if c < len(letters):
                outstr += letters[c]
        ret.append(outstr)
    return ret


paths = 'model1_nomer.tflite'
interpreter = tf.lite.Interpreter(model_path=paths)
interpreter.allocate_tensors()
# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
img = resized
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img = cv2.resize(img, (128, 64))
img = img.astype(np.float32)
img /= 255
img1 = img.T
img1.shape
X_data1 = np.float32(img1.reshape(1, 128, 64, 1))
input_index = (interpreter.get_input_details()[0]['index'])
interpreter.set_tensor(input_details[0]['index'], X_data1)
interpreter.invoke()
net_out_value = interpreter.get_tensor(output_details[0]['index'])
pred_texts = decode_batch(net_out_value)
if a != pred_texts:
    a = pred_texts
    print(a)
else:
    None

该类通过haar级联检测车牌号，也直接显示在应用程序中。

我需要以某种方式将a带有车号的变量输出到预先准备好的表格QLineEdit中。

下面的方法不起作用，程序崩溃。

class PredictNumber(QThread):
    ImageUpdate = pyqtSignal(QImage)
    NuberUpdate = pyqtSignal(QTextLine)

    def run(self):
        self.ThreadActive = True
        capture = cv2.VideoCapture(0)
        a = None
        while self.ThreadActive:
            face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')
            ret, frame = capture.read()
            if ret:
                image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
                with_cascade = face_cascade.detectMultiScale(image, 1.3, 7)
                for i, (x, y, w, h) in enumerate(with_cascade):
                    roi_color = image[y:y + h, x:x + w]
                    r = 300.0 / roi_color.shape[1]
                    dim = (400, int(roi_color.shape[0] * r))
                    resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
                    w_resized = resized.shape[0]
                    h_resized = resized.shape[1]
                    image[380:380 + w_resized, 235:235 + h_resized] = resized
                    letters = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'E', 'H', 'K', 'M', 'O',
                               'P', 'T', 'X', 'Y']

                    def decode_batch(out):
                        ret = []
                        for j in range(out.shape[0]):
                            out_best = list(np.argmax(out[j, 2:], 1))
                            out_best = [k for k, g in itertools.groupby(out_best)]
                            outstr = ''
                            for c in out_best:
                                if c < len(letters):
                                    outstr += letters[c]
                            ret.append(outstr)
                        return ret

                    paths = 'model1_nomer.tflite'
                    interpreter = tf.lite.Interpreter(model_path=paths)
                    interpreter.allocate_tensors()
                    # Get input and output tensors.
                    input_details = interpreter.get_input_details()
                    output_details = interpreter.get_output_details()
                    img = resized
                    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
                    img = cv2.resize(img, (128, 64))
                    img = img.astype(np.float32)
                    img /= 255
                    img1 = img.T
                    img1.shape
                    X_data1 = np.float32(img1.reshape(1, 128, 64, 1))
                    input_index = (interpreter.get_input_details()[0]['index'])
                    interpreter.set_tensor(input_details[0]['index'], X_data1)
                    interpreter.invoke()
                    net_out_value = interpreter.get_tensor(output_details[0]['index'])
                    pred_texts = decode_batch(net_out_value)
                    if a != pred_texts:
                        a = pred_texts
                conv_to_qt = QTextLine(a)
                convert_to_qt_format = QImage(image.data, image.shape[1], image.shape[0], QImage.Format_RGB888)
                self.ImageUpdate.emit(convert_to_qt_format)
                self.NuberUpdate.emit(conv_to_qt)
# Class Main
self.PredictNumber.NuberUpdate.connect(self.number_update_slot)
    def number_update_slot(self, number):
        self.ui.predicted_number.setText(number)

如何用0 секунд, 0 минут,0 часов制作秒表
此代码仅显示计算机上设置的当前时间。

    self.timer = QtCore.QTimer()
    self.timer.setInterval(100)
    self.timer.timeout.connect(self.displayTime)

    def start_timer(self):
        self.timer.start()

    def displayTime(self):
        self.ui.TimerMenu.setText(QtCore.QDateTime.currentDateTime().toString('hh:mm:ss'))

如何通过神经网络（函数）从网络摄像头（函数camera_on，
以及）“传递”帧？control_timernetwork

class PredictNumber:
    face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')

    def network(self, image_video):
        ret, frame = image_video.read()
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        plaques = face_cascade.detectMultiScale(gray, 1.3, 5)
        for i, (x, y, w, h) in enumerate(plaques):
            roi_color = frame[y:y + h, x:x + w]
            r = 400.0 / roi_color.shape[1]
            dim = (400, int(roi_color.shape[0] * r))
            resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
            w_resized = resized.shape[0]
            h_resized = resized.shape[1]
            frame[100:100 + w_resized, 100:100 + h_resized] = resized
        return resized 

    def camera_on(self):
        ret, image = self.cap.read()
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        height, width, channel = image.shape
        step = channel * width
        img = QImage(image.data, width, height, step, QImage.Format_RGB888)
        image_video = PredictNumber.network(self, img) 
# Таким образом не работает, 
происходит вылет программы.
        self.ui.Cam.setPixmap(QPixmap.fromImage(image_video))
        self.ui.Cam.setScaledContents(True)

    def control_timer(self):
        if not self.timer.isActive():
            self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
            self.timer.start(0)

UPD：重写并将相机移动到单独的类

为了避免将格式从 cv 转换为 QT image，我这样做了，添加了级联，但程序仍然崩溃：

class Worker1(QThread):
    ImageUpdate = pyqtSignal(QImage)
    face_cascade = cv2.CascadeClassifier('cascade/haarcascade_russian_plate_number.xml')
    def run(self):
        self.ThreadActive = True
        Capture = cv2.VideoCapture(0)
        while self.ThreadActive:
            ret, frame = Capture.read()
            if ret:
                image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
                flipped_image = cv2.flip(image, 1)
                with_cascade = faceCascade.detectMultiScale(flipped_image, 1.3, 7)
                for (x, y, w, h) in with_cascade:
                    roi_color = ret[y:y + h, x:x + w]
                    r = 300.0 / roi_color.shape[1]
                    dim = (400, int(roi_color.shape[0] * r))
                    resized = cv2.resize(roi_color, dim, interpolation=cv2.INTER_AREA)
                convert_to_qt_format = QImage(resized.data, resized.shape[1], fresized.shape[0], QImage.Format_RGB888)
                self.ImageUpdate.emit(convert_to_qt_format)

在这里，该类被初始化，并在按下按钮时启动。

        self.Worker1 = Worker1()
        self.Worker1.ImageUpdate.connect(self.image_update_slot)
        self.ui.Camera_btn.clicked.connect(self.Worker1.start)

这是一个用于更新相机的插槽。最后一行根据小部件制作相机大小

    def image_update_slot(self, Image):
        self.ui.Cam.setPixmap(QPixmap.fromImage(Image))
        self.ui.Cam.setScaledContents(True)