aboutsummaryrefslogtreecommitdiffstats
path: root/examples/external/opencv/webcam_pattern_detection.py
blob: 0c55a13336ce92e4aefad8c8a415a13e24aff9f5 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
# Copyright (C) 2022 The Qt Company Ltd.
# SPDX-License-Identifier: LicenseRef-Qt-Commercial OR BSD-3-Clause

import os
import sys
import time

import cv2
from PySide6.QtCore import Qt, QThread, Signal, Slot
from PySide6.QtGui import QAction, QImage, QKeySequence, QPixmap
from PySide6.QtWidgets import (QApplication, QComboBox, QGroupBox,
                               QHBoxLayout, QLabel, QMainWindow, QPushButton,
                               QSizePolicy, QVBoxLayout, QWidget)


"""This example uses the video from a  webcam to apply pattern
detection from the OpenCV module. e.g.: face, eyes, body, etc."""


class Thread(QThread):
    updateFrame = Signal(QImage)

    def __init__(self, parent=None):
        QThread.__init__(self, parent)
        self.trained_file = None
        self.status = True
        self.cap = True

    def set_file(self, fname):
        # The data comes with the 'opencv-python' module
        self.trained_file = os.path.join(cv2.data.haarcascades, fname)

    def run(self):
        self.cap = cv2.VideoCapture(0)
        while self.status:
            cascade = cv2.CascadeClassifier(self.trained_file)
            ret, frame = self.cap.read()
            if not ret:
                continue

            # Reading frame in gray scale to process the pattern
            gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

            detections = cascade.detectMultiScale(gray_frame, scaleFactor=1.1,
                                                  minNeighbors=5, minSize=(30, 30))

            # Drawing green rectangle around the pattern
            for (x, y, w, h) in detections:
                pos_ori = (x, y)
                pos_end = (x + w, y + h)
                color = (0, 255, 0)
                cv2.rectangle(frame, pos_ori, pos_end, color, 2)

            # Reading the image in RGB to display it
            color_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

            # Creating and scaling QImage
            h, w, ch = color_frame.shape
            img = QImage(color_frame.data, w, h, ch * w, QImage.Format_RGB888)
            scaled_img = img.scaled(640, 480, Qt.KeepAspectRatio)

            # Emit signal
            self.updateFrame.emit(scaled_img)
        sys.exit(-1)


class Window(QMainWindow):
    def __init__(self):
        super().__init__()
        # Title and dimensions
        self.setWindowTitle("Patterns detection")
        self.setGeometry(0, 0, 800, 500)

        # Main menu bar
        self.menu = self.menuBar()
        self.menu_file = self.menu.addMenu("File")
        exit = QAction("Exit", self, triggered=qApp.quit)  # noqa: F821
        self.menu_file.addAction(exit)

        self.menu_about = self.menu.addMenu("&About")
        about = QAction("About Qt", self, shortcut=QKeySequence(QKeySequence.HelpContents),
                        triggered=qApp.aboutQt)  # noqa: F821
        self.menu_about.addAction(about)

        # Create a label for the display camera
        self.label = QLabel(self)
        self.label.setFixedSize(640, 480)

        # Thread in charge of updating the image
        self.th = Thread(self)
        self.th.finished.connect(self.close)
        self.th.updateFrame.connect(self.setImage)

        # Model group
        self.group_model = QGroupBox("Trained model")
        self.group_model.setSizePolicy(QSizePolicy.Preferred, QSizePolicy.Expanding)
        model_layout = QHBoxLayout()

        self.combobox = QComboBox()
        for xml_file in os.listdir(cv2.data.haarcascades):
            if xml_file.endswith(".xml"):
                self.combobox.addItem(xml_file)

        model_layout.addWidget(QLabel("File:"), 10)
        model_layout.addWidget(self.combobox, 90)
        self.group_model.setLayout(model_layout)

        # Buttons layout
        buttons_layout = QHBoxLayout()
        self.button1 = QPushButton("Start")
        self.button2 = QPushButton("Stop/Close")
        self.button1.setSizePolicy(QSizePolicy.Preferred, QSizePolicy.Expanding)
        self.button2.setSizePolicy(QSizePolicy.Preferred, QSizePolicy.Expanding)
        buttons_layout.addWidget(self.button2)
        buttons_layout.addWidget(self.button1)

        right_layout = QHBoxLayout()
        right_layout.addWidget(self.group_model, 1)
        right_layout.addLayout(buttons_layout, 1)

        # Main layout
        layout = QVBoxLayout()
        layout.addWidget(self.label)
        layout.addLayout(right_layout)

        # Central widget
        widget = QWidget(self)
        widget.setLayout(layout)
        self.setCentralWidget(widget)

        # Connections
        self.button1.clicked.connect(self.start)
        self.button2.clicked.connect(self.kill_thread)
        self.button2.setEnabled(False)
        self.combobox.currentTextChanged.connect(self.set_model)

    @Slot()
    def set_model(self, text):
        self.th.set_file(text)

    @Slot()
    def kill_thread(self):
        print("Finishing...")
        self.button2.setEnabled(False)
        self.button1.setEnabled(True)
        self.th.cap.release()
        cv2.destroyAllWindows()
        self.status = False
        self.th.terminate()
        # Give time for the thread to finish
        time.sleep(1)

    @Slot()
    def start(self):
        print("Starting...")
        self.button2.setEnabled(True)
        self.button1.setEnabled(False)
        self.th.set_file(self.combobox.currentText())
        self.th.start()

    @Slot(QImage)
    def setImage(self, image):
        self.label.setPixmap(QPixmap.fromImage(image))


if __name__ == "__main__":
    app = QApplication()
    w = Window()
    w.show()
    sys.exit(app.exec())