У меня есть изображение лица с пупырышками, и я хочу обнаружить все пупырышки, и я хочу нарисовать ограничивающую рамку на каждом пупырышке. Как я могу это сделать? Извините, я новичок в программировании на Python.
Я использую алгоритм KNN для классификации.
У меня есть главное окно, которое показывает ОРИГИНАЛЬНОЕ ИЗОБРАЖЕНИЕ и ОБРАБОТАННОЕ ИЗОБРАЖЕНИЕ. На обработанном изображении появится ограничительная рамка.
Вот мои коды: у меня есть 2 файла Python. Где я должен поместить код для ограничительной рамки и каков код этой функции?
Это для главного окна:
import os
import sys
import cv2
import datetime
import numpy as np
from time import sleep
from PyQt5 import QtCore, QtGui, QtWidgets
from color_recognition_api import color_histogram_feature_extraction
from color_recognition_api import knn_classifier
PATH="./training.data"
class Ui_MainWindow(object):
def __init__(self):
print("Initializing ....")
if os.path.isfile(PATH) and os.access(PATH, os.R_OK):
print ('training data is ready, classifier is loading...')
else:
print ('training data is being created...')
open('training.data', 'w')
color_histogram_feature_extraction.training()
print ('training data is ready, classifier is loading...')
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(640, 480)
self.centralWidget = QtWidgets.QWidget(MainWindow)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.centralWidget.sizePolicy().hasHeightForWidth())
self.centralWidget.setSizePolicy(sizePolicy)
self.centralWidget.setObjectName("centralWidget")
self.groupBox = QtWidgets.QGroupBox(self.centralWidget)
self.groupBox.setGeometry(QtCore.QRect(10, 10, 621, 441))
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().hasHeightForWidth())
self.groupBox.setSizePolicy(sizePolicy)
self.groupBox.setFlat(False)
self.groupBox.setCheckable(False)
self.groupBox.setObjectName("groupBox")
self.gridLayout = QtWidgets.QGridLayout(self.groupBox)
self.gridLayout.setContentsMargins(11, 11, 11, 11)
self.gridLayout.setSpacing(6)
self.gridLayout.setObjectName("gridLayout")
self.pushButton = QtWidgets.QPushButton(self.groupBox)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.pushButton.sizePolicy().hasHeightForWidth())
self.pushButton.setSizePolicy(sizePolicy)
self.pushButton.setObjectName("pushButton")
self.gridLayout.addWidget(self.pushButton, 0, 0, 1, 1)
self.lineEdit = QtWidgets.QLineEdit(self.groupBox)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.lineEdit.sizePolicy().hasHeightForWidth())
self.lineEdit.setSizePolicy(sizePolicy)
self.lineEdit.setMaxLength(255)
self.lineEdit.setObjectName("lineEdit")
self.gridLayout.addWidget(self.lineEdit, 0, 1, 1, 2)
self.pushButton_2 = QtWidgets.QPushButton(self.groupBox)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.pushButton_2.sizePolicy().hasHeightForWidth())
self.pushButton_2.setSizePolicy(sizePolicy)
self.pushButton_2.setObjectName("pushButton_2")
self.gridLayout.addWidget(self.pushButton_2, 1, 0, 1, 1)
self.label_2 = QtWidgets.QLabel(self.groupBox)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.label_2.sizePolicy().hasHeightForWidth())
self.label_2.setSizePolicy(sizePolicy)
self.label_2.setFrameShape(QtWidgets.QFrame.WinPanel)
self.label_2.setFrameShadow(QtWidgets.QFrame.Plain)
self.label_2.setTextFormat(QtCore.Qt.AutoText)
self.label_2.setAlignment(QtCore.Qt.AlignCenter)
self.label_2.setObjectName("label_2")
self.gridLayout.addWidget(self.label_2, 2, 2, 1, 1)
self.label = QtWidgets.QLabel(self.groupBox)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.label.sizePolicy().hasHeightForWidth())
self.label.setSizePolicy(sizePolicy)
self.label.setFrameShape(QtWidgets.QFrame.WinPanel)
self.label.setFrameShadow(QtWidgets.QFrame.Plain)
self.label.setTextFormat(QtCore.Qt.AutoText)
self.label.setAlignment(QtCore.Qt.AlignCenter)
self.label.setObjectName("label")
self.gridLayout.addWidget(self.label, 2, 0, 1, 2)
MainWindow.setCentralWidget(self.centralWidget)
self.statusBar = QtWidgets.QStatusBar(MainWindow)
self.statusBar.setObjectName("statusBar")
MainWindow.setStatusBar(self.statusBar)
self.retranslateUi(MainWindow)
self.dialog = QtWidgets.QFileDialog(MainWindow)
self.dialog.setFileMode(QtWidgets.QFileDialog.AnyFile)
self.fname = None
self.image = None
self.pushButton.clicked.connect(self.pushButton_clicked)
self.pushButton_2.clicked.connect(self.pushButton2_clicked)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def retranslateUi(self, MainWindow):
_translate = QtCore.QCoreApplication.translate
MainWindow.setWindowTitle(_translate("MainWindow", "Acne Detection and Classifier"))
self.groupBox.setTitle(_translate("MainWindow", "Image Processing"))
self.pushButton.setText(_translate("MainWindow", "Browse .."))
self.lineEdit.setText(_translate("MainWindow", "File Location"))
self.pushButton_2.setText(_translate("MainWindow", "Start"))
self.label_2.setText(_translate("MainWindow", "<Processed Image>"))
self.label.setText(_translate("MainWindow", "<Original Image>"))
def pushButton_clicked(self):
try:
if self.dialog.exec_():
self.showImage(self.dialog.selectedFiles())
except Exception as error:
print(error)
def pushButton2_clicked(self):
if self.pushButton_2.text() == "Start":
self.pushButton_2.setText("Reset")
try:
color_histogram_feature_extraction.color_histogram_of_test_image(self.image)
prediction = knn_classifier.main('training.data', 'test.data')
print(prediction)
self.pushButton_2.setText("Start")
except Exception as error:
print(error)
else:
self.pushButton_2.setText("Start")
def showImage(self, files):
for file in files:
#print(file)
self.fname = file
self.lineEdit.setText(file)
self.image = cv2.imread(file, cv2.IMREAD_COLOR)
qimage = QtGui.QImage(file)
pixmap = QtGui.QPixmap.fromImage(qimage)
self.label.setPixmap(pixmap)
self.label.setScaledContents(True)
self.label_2.setPixmap(pixmap)
self.label_2.setScaledContents(True)
self.label.show()
self.label_2.show()
#sleep(10)
if __name__ == "__main__":
app = QtWidgets.QApplication(sys.argv)
app.setStyle("cleanlooks")
mainWindow = QtWidgets.QMainWindow()
ui = Ui_MainWindow()
ui.setupUi(mainWindow)
#mainWindow.showFullScreen()
mainWindow.show()
sys.exit(app.exec_())
Это для извлечения функции цветовой гистограммы:
from PIL import Image
import os
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import itemfreq
from color_recognition_api import knn_classifier as knn_classifier
def color_histogram_of_test_image(test_src_image):
# load the image
image = test_src_image
chans = cv2.split(image)
colors = ('b', 'g', 'r')
features = []
feature_data = ''
counter = 0
for (chan, color) in zip(chans, colors):
counter = counter + 1
hist = cv2.calcHist([chan], [0], None, [256], [0, 256])
features.extend(hist)
# find the peak pixel values for R, G, and B
elem = np.argmax(hist)
if counter == 1:
blue = str(elem)
elif counter == 2:
green = str(elem)
elif counter == 3:
red = str(elem)
feature_data = red + ',' + green + ',' + blue
# print(feature_data)
with open('test.data', 'w') as myfile:
myfile.write(feature_data)
def color_histogram_of_training_image(img_name):
# detect image color by using image file name to label training data
if 'blackheads' in img_name:
data_source = 'blackheads'
elif 'cysts' in img_name:
data_source = 'cysts'
elif 'nodules' in img_name:
data_source = 'nodules'
elif 'papules' in img_name:
data_source = 'papules'
elif 'pustules' in img_name:
data_source = 'pustules'
elif 'whiteheads' in img_name:
data_source = 'whiteheads'
# load the image
image = cv2.imread(img_name)
chans = cv2.split(image)
colors = ('b', 'g', 'r')
features = []
feature_data = ''
counter = 0
for (chan, color) in zip(chans, colors):
counter = counter + 1
hist = cv2.calcHist([chan], [0], None, [256], [0, 256])
features.extend(hist)
# find the peak pixel values for R, G, and B
elem = np.argmax(hist)
if counter == 1:
blue = str(elem)
elif counter == 2:
green = str(elem)
elif counter == 3:
red = str(elem)
feature_data = red + ',' + green + ',' + blue
with open('training.data', 'a') as myfile:
myfile.write(feature_data + ',' + data_source + '\n')
def training():
# blackheads color training images
for f in os.listdir('./training_dataset/blackheads'):
print(f)
color_histogram_of_training_image('./training_dataset/blackheads/' + f)
# cysts color training images
for f in os.listdir('./training_dataset/cysts'):
print(f)
color_histogram_of_training_image('./training_dataset/cysts/' + f)
# nodules color training images
for f in os.listdir('./training_dataset/nodules'):
print(f)
color_histogram_of_training_image('./training_dataset/nodules/' + f)
# papules color training images
for f in os.listdir('./training_dataset/papules'):
print(f)
color_histogram_of_training_image('./training_dataset/papules/' + f)
# pustules color training images
for f in os.listdir('./training_dataset/pustules'):
print(f)
color_histogram_of_training_image('./training_dataset/pustules/' + f)
# whiteheads color training images
for f in os.listdir('./training_dataset/whiteheads'):
print(f)
color_histogram_of_training_image('./training_dataset/whiteheads/' + f)