refactoring

lab2_1/lab2_1.py

@@ -1,65 +1,51 @@
 import os
 import sys
+import traceback
+
 import cv2
 import numpy as np
 from matplotlib import pyplot as plt
 
 
-def menu():
+SOURCE_IMAGE = "test.jpg"
-    print("Выберите пункт меню:\n1.Linear filter\n2.Blur\n3.Median blur\n4.GaussianBlur\n5.Erode")
-    print("6.Dilate\n7.MORPH_OPERATIONS\n8.Sobel\n9.Laplacian\n10.Canny\n11.CalcHist\n12.EqualizeHist")
-    print("13.Save\n14.Add Figure\n15.Del Figure\n16.Exit")
 
 
-def main():
+def filter_linear(image):
-    image1 = cv2.imread("D:\\MACH\\LAB_2\\image0.jpg")
-    image2 = image1.copy()
-    im = image1.copy()
-    while True:
-        menu()
-        try:
-            s = int(input())
-            if s == 1:
-                image2 = image1.copy()
     kernel = np.array([[-0.1, 0.2, -0.1], [0.2, 3.0, 0.2], [-0.1, 0.2, -0.1]])
-                image2 = cv2.filter2D(image2, -1, kernel)
+    cv2.imshow("Исходное изображение", image)
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Результат", cv2.filter2D(image.copy(), -1, kernel))
-                cv2.imshow("Result_Image", image2)
+
-                cv2.waitKey(0)
+
-            if s == 2:
+def filter_blur(image):
-                image2 = image1.copy()
+    cv2.imshow("Исходное изображение", image)
-                image2 = cv2.blur(image2, (5, 5))
+    cv2.imshow("Результат", cv2.blur(image.copy(), (5, 5)))
-                cv2.imshow("Image_load", image1)
+
-                cv2.imshow("Result_Image", image2)
+
-                cv2.waitKey(0)
+def filter_median_blur(image):
-            if s == 3:
+    cv2.imshow("Исходное изображение", image)
-                image2 = image1.copy()
+    cv2.imshow("Результат", cv2.medianBlur(image.copy(), 5))
-                image2 = cv2.medianBlur(image2, 5)
+
-                cv2.imshow("Image_load", image1)
+
-                cv2.imshow("Result_Image", image2)
+def filter_gauss_blur(image):
-                cv2.waitKey(0)
+    cv2.imshow("Исходное изображение", image)
-            if s == 4:
+    cv2.imshow("Результат", cv2.GaussianBlur(image.copy(), (9, 9), cv2.BORDER_DEFAULT))
-                image2 = image1.copy()
+
-                image2 = cv2.GaussianBlur(image2, (9, 9), cv2.BORDER_DEFAULT)
+
-                cv2.imshow("Image_load", image1)
+def filter_erode(image):
-                cv2.imshow("Result_Image", image2)
+    cv2.imshow("Исходное изображение", image)
-                cv2.waitKey(0)
+    cv2.imshow("Результат", cv2.erode(image.copy(), np.ones((11, 11))))
-            if s == 5:
+
-                image2 = image1.copy()
+
-                image2 = cv2.erode(image2, np.ones((11, 11)))
+def filter_dilate(image):
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Исходное изображение", image)
-                cv2.imshow("Result_Image", image2)
+    cv2.imshow("Результат", cv2.dilate(image.copy(), np.ones((11, 11))))
-                cv2.waitKey(0)
+
-            if s == 6:
+
-                image2 = image1.copy()
+def filter_morph(image):
-                image2 = cv2.dilate(image2, np.ones((11, 11)))
+    # TODO переписать
-                cv2.imshow("Image_load", image1)
+    image2 = image.copy()
-                cv2.imshow("Result_Image", image2)
-                cv2.waitKey(0)
-            if s == 7:
-                image2 = image1.copy()
     image3 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Image_load", image)
     kernel = np.ones((6, 6), np.uint8)
     image3 = cv2.morphologyEx(image3, cv2.MORPH_OPEN, kernel, iterations=1)
     cv2.imshow("MORPH_OPEN", image3)
@@ -76,86 +62,101 @@ def main():
     image3 = cv2.morphologyEx(image3, cv2.MORPH_BLACKHAT, kernel, iterations=1)
     cv2.imshow("MORPH_BLACKHAT", image3)
     image3 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
-                cv2.waitKey(0)
+
-            if s == 8:
+
-                image2 = image1.copy()
+def filter_sobel(image):
+    image2 = image.copy()
     image3 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
     image3 = cv2.GaussianBlur(image3, (3, 3), 0)
     im3 = cv2.Sobel(image3, cv2.CV_64F, 1, 0, ksize=5)
     im4 = cv2.Sobel(image3, cv2.CV_64F, 0, 1, ksize=5)
     im5 = cv2.Sobel(image3, cv2.CV_8UC1, 0, 1, ksize=5)
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Image_load", image)
     cv2.imshow("Result_Image_X", im3)  # x
     cv2.imshow("Result_Image_Y", im4)  # y
     cv2.imshow("Result_Gradient", im5)  # gradient
-                cv2.waitKey(0)
+
-            if s == 9:
+
-                image2 = image1.copy()
+def filter_laplacian(image):
+    image2 = image.copy()
     image3 = cv2.cvtColor(image2, cv2.COLOR_RGB2GRAY)
     image3 = cv2.GaussianBlur(image3, (3, 3), 0)
     im3 = cv2.Laplacian(image3, cv2.CV_64F)
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Image_load", image)
-                cv2.imshow("Result_Image", im3)  # x
+    cv2.imshow("Result_Image", im3)
-                cv2.waitKey(0)
+
-            if s == 10:
+
-                image2 = image1.copy()
+def filter_canny(image):
-                image3 = cv2.cvtColor(image2, cv2.COLOR_RGB2GRAY)
+    image2 = image.copy()
     image3 = cv2.blur(image2, (5, 5))
     image3 = cv2.Canny(image3, 100, 100)
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Image_load", image)
-                cv2.imshow("Result_Image", image3)  # x
+    cv2.imshow("Result_Image", image3)
-                cv2.waitKey(0)
+
-            if s == 11:
+
-                image2 = image1.copy()
+def filter_calc_hist(image):
+    image2 = image.copy()
     color = ('b', 'g', 'r')
-                cv2.imshow("Image_load", image1)
+    cv2.imshow("Image_load", image)
     for i, col in enumerate(color):
         histr = cv2.calcHist([image2], [i], None, [256], [0, 256])
         plt.plot(histr, color=col)
         plt.xlim([0, 256])
     plt.show()
     plt.close()
-                cv2.waitKey(0)
-            if s == 12:
-                image2 = image1.copy()
-                image2 = cv2.cvtColor(image2, cv2.COLOR_RGB2GRAY)
-                image2 = cv2.equalizeHist(image2)
-                cv2.imshow("Image_load", image1)
-                cv2.imshow("Result_Image", image2)
-                cv2.waitKey(0)
-            if s == 13:
-                cv2.imshow("Image_load", image1)
-                cv2.imshow("Result_Image", image2)
-                cv2.imwrite("D:\\im1.jpg", image1)
-                cv2.imwrite("D:\\im2.jpg", image2)
-                cv2.waitKey(0)
-            if s == 14:
-                image2 = image1.copy()
-                cv2.imshow("Image_load", image1)
-                image2 = cv2.line(image2, (15, 15), (270, 270), (76, 187, 23), 10)  # линия
-                image2 = cv2.rectangle(image2, (20, 20), (100, 100), (0, 0, 255), 10)  # нарисуем четырехугольник
-                image2 = cv2.circle(image2, (100, 100), 40, (0, 255, 0), 10)  # нарисуем круг
-                cv2.imshow("Result_Image", image2)
-                image1 = image2
-                cv2.waitKey(0)
-            if s == 15:
-                cv2.imwrite("1.jpg", im)
-                cv2.imwrite("2.jpg", image1)
-                img = cv2.imread("1.jpg")
-                mask = cv2.imread("2.jpg", 0)
-                res = cv2.bitwise_and(img, img, mask=mask)
-                image2 = res.copy()
-                image1 = res.copy()
-                cv2.imshow("Result_Image", res)
 
+
+def filter_equalize_hist(image):
+    cv2.imshow("Исходное изображение", image)
+    cv2.imshow("Результат", cv2.equalizeHist(cv2.cvtColor(image.copy(), cv2.COLOR_RGB2GRAY)))
+
+
+functions_list = {
+    "lf": {"func": filter_linear, "help": "Linear filter"},
+    "bl": {"func": filter_blur, "help": "Blur"},
+    "mb": {"func": filter_median_blur, "help": "Median blur"},
+    "gb": {"func": filter_gauss_blur, "help": "GaussianBlur"},
+    "er": {"func": filter_erode, "help": "Erode"},
+    "di": {"func": filter_dilate, "help": "Dilate"},
+    "mo": {"func": filter_morph, "help": "MORPH_OPERATIONS"},
+    "so": {"func": filter_sobel, "help": "Sobel"},
+    "la": {"func": filter_laplacian, "help": "Laplacian"},
+    "ca": {"func": filter_canny, "help": "Canny"},
+    "cl": {"func": filter_calc_hist, "help": "CalcHist"},
+    "eh": {"func": filter_equalize_hist, "help": "EqualizeHist"},
+    "q": {"func": lambda image: sys.exit(0), "help": "Exit"},
+}
+
+
+def print_help():
+    print("Доступные функции:")
+    for k in functions_list:
+        print(f"    {k} - {functions_list[k]['help']}")
+
+
+def main():
+    image1 = cv2.imread(SOURCE_IMAGE)
+    while True:
+        try:
+            cmd = input(">> ")
+            if cmd == "":
+                continue
+            elif cmd == "?":
+                print_help()
+            else:
+                if cmd in functions_list:
+                    try:
+                        functions_list[cmd]["func"](image=image1.copy())
                         cv2.waitKey(0)
-                os.remove("1.jpg")
-                os.remove("2.jpg")
-            if s == 16:
                         cv2.destroyAllWindows()
-                sys.exit(0)
+                    except Exception:
-        except ValueError:
+                        print("Произошла ошибка при выполнении функции")
-            print("Неверный пункт меню!!!! Выберите другое!")
+                        traceback.print_exc()
+                else:
+                    print("Функция не найдена! введите '?' для получения справки")
+
+        except Exception:
+            traceback.print_exc()
 
 
 if __name__ == "__main__":

lab2_2/lab2_2.py

@@ -2,12 +2,16 @@ import sys
 import cv2
 import numpy
 from PyQt5.QtGui import QImage, QPixmap
-from PyQt5.QtWidgets import QWidget, QApplication, QLabel, QVBoxLayout, QHBoxLayout, QPushButton, QFileDialog,QComboBox,QMessageBox
+from PyQt5.QtWidgets import QWidget, QApplication, QLabel, QVBoxLayout, QHBoxLayout, QPushButton, QFileDialog, \
+    QComboBox, QMessageBox
 from PyQt5.QtCore import Qt
 from matplotlib import pyplot as plt
+
+
 class Example(QWidget):
     def __init__(self):
         super().__init__()
+        self.image2 = None
         self.image = None
         self.label = QLabel()
         self.initUI()
@@ -22,7 +26,6 @@ class Example(QWidget):
         btn_procesar = QPushButton('Сохранить изображение')
         btn_procesar.clicked.connect(self.saveImage)
 
-
         f = open("Operate.txt", "r")
         attr = f.read().splitlines()
         f.close()
@@ -43,7 +46,8 @@ class Example(QWidget):
         self.show()
 
     def openImage(self):
-        self.filename, _ = QFileDialog.getOpenFileName(None, 'Buscar Imagen', '.', 'Image Files (*.png *.jpg *.jpeg *.bmp)')
+        self.filename, _ = QFileDialog.getOpenFileName(None, 'Buscar Imagen', '.',
+                                                       'Image Files (*.png *.jpg *.jpeg *.bmp)')
         if self.filename:
             with open(self.filename, "rb") as file:
                 data = numpy.array(bytearray(file.read()))
@@ -51,16 +55,11 @@ class Example(QWidget):
                 self.mostrarImagen(self.image)
             self.image2 = self.image
 
-            
-    
-
     def saveImage(self):
         filename = QFileDialog.getSaveFileName(self, "QFileDialog.getSaveFileName()", "", "Image Files (*.jpg)")
         img = self.image2
         cv2.imwrite(filename[0], img)
 
-
-
     def mostrarImagen(self, s):
         size = s.shape
         step = s.size / size[0]
@@ -75,7 +74,6 @@ class Example(QWidget):
         self.label.setPixmap(QPixmap.fromImage(img))
         self.resize(self.label.pixmap().size())
 
-
     def combobox(self, index):
         if index == 0:
             self.i0()
@@ -120,7 +118,6 @@ class Example(QWidget):
         if index == 20:
             self.i20()
 
-
     def i0(self):
         self.image2 = self.image
         self.mostrarImagen(self.image)
@@ -131,13 +128,11 @@ class Example(QWidget):
         self.image2 = cv2.filter2D(self.image2, -1, kernel)
         self.mostrarImagen(self.image2)
 
-    
     def i2(self):
         self.image2 = self.image
         self.image2 = cv2.blur(self.image2, (5, 5))
         self.mostrarImagen(self.image2)
 
-
     def i3(self):
         self.image2 = self.image
         self.image2 = cv2.medianBlur(self.image2, 5)
@@ -188,7 +183,6 @@ class Example(QWidget):
         self.image2 = cv2.morphologyEx(self.image2, cv2.MORPH_BLACKHAT, kernel, iterations=1)
         self.mostrarImagen(self.image2)
 
-
     def i12(self):
         self.image2 = self.image
         self.image2 = cv2.cvtColor(self.image2, cv2.COLOR_BGR2GRAY)
@@ -233,7 +227,6 @@ class Example(QWidget):
             plt.xlim([0, 256])
         plt.show()
 
-
     def i18(self):
         self.image2 = self.image
         self.image2 = cv2.cvtColor(self.image2, cv2.COLOR_RGB2GRAY)
@@ -265,6 +258,7 @@ class Example(QWidget):
         else:
             event.ignore()
 
+
 if __name__ == '__main__':
     app = QApplication(sys.argv)
     win = Example()

lab4/lab4.py

@@ -1,32 +1,22 @@
-#import numpy as np
+import random
-#import cv2 
-#img = cv2.imread("D:\MACH\LAB_4\crocodile\image_0001.jpg")
-#gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
-#sift = cv2.SIFT_create()
-#kp = sift.detect(gray,None)
-#img=cv2.drawKeypoints(gray,kp,img)
-#cv2.imshow("R",img)
-#cv2.waitKey(0)
-#cv2.destroyAllWindows()
 import sys
 import cv2
 import numpy as np
 import random
 import math
+from PyQt5.QtCore import Qt
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.metrics import accuracy_score
 from PyQt5.QtGui import QImage, QPixmap
 from PyQt5.QtWidgets import (QWidget, QApplication, QLabel, QVBoxLayout, QHBoxLayout, QPushButton, 
                              QFileDialog,QComboBox,QMessageBox,QTextBrowser)
-from PyQt5.QtCore import Qt
+
+
 class Example(QWidget):
     def __init__(self):
         super().__init__()
         self.image = None
         self.textbrowser = QTextBrowser()
-        self.initUI()
-
-    def initUI(self):
 
         self.btn_open = QPushButton('Изображения folder1')
         self.btn_open.clicked.connect(self.openImages1)
@@ -34,11 +24,9 @@ class Example(QWidget):
         self.btn_open1 = QPushButton('Изображения folder2')
         self.btn_open1.clicked.connect(self.openImages2)
 
-
         self.btn_ = QPushButton('Обучить и создать матрицы')
         self.btn_.clicked.connect(self.matrix_and_train)
 
-
         self.btn1 = QPushButton('Детектировать тестовые изображения')
         self.btn1.clicked.connect(self.detect_image)
 
@@ -49,7 +37,6 @@ class Example(QWidget):
         self.btn1.setVisible(False)
         self.btn2.setVisible(False)
 
-
         top_bar = QHBoxLayout()
         top_bar.addWidget(self.btn_open)
         top_bar.addWidget(self.btn_open1)
@@ -64,7 +51,6 @@ class Example(QWidget):
         self.spisok2 = list()
         self.spisok3 = list()
 
-
         self.train = list()
         self.matrix = list()
         self.resize(540, 574)
@@ -72,15 +58,16 @@ class Example(QWidget):
         self.show()
 
     def openImages1(self):
-        filenames1 = QFileDialog.getOpenFileNames(None, 'Открыть изображения', '.', 'Image Files (*.png *.jpg *.jpeg *.bmp)')
+        filenames1 = QFileDialog.getOpenFileNames(None, 'Открыть изображения', '.',
+                                                  'Image Files (*.png *.jpg *.jpeg *.bmp)')
         lk = filenames1[0]
         self.erroropened(lk, "1")
         self.mass(lk, 1)
         lk.clear()
 
-
     def openImages2(self):
-        filenames2 = QFileDialog.getOpenFileNames(None, 'Открыть изображения', '.', 'Image Files (*.png *.jpg *.jpeg *.bmp)')
+        filenames2 = QFileDialog.getOpenFileNames(None, 'Открыть изображения', '.',
+                                                  'Image Files (*.png *.jpg *.jpeg *.bmp)')
         lk = filenames2[0]
         self.erroropened(lk, "2")
         self.mass(lk, 2)
@@ -92,7 +79,6 @@ class Example(QWidget):
         else:
             q = QMessageBox.information(self, "Информация", "Вы не выбрали изображения!")
 
-
     def mass(self, p, s1):
         if s1 == 1:
             self.spisok3.clear()
@@ -109,7 +95,10 @@ class Example(QWidget):
             self.btn_open.setVisible(False)
             self.btn_open1.setVisible(False)
             self.btn_.setVisible(True)
-        q=QMessageBox.information(self,"Информация","Количество изображений тестовой категории: "+str(len(self.spisok))+"\nКоличество изображений основной категории: "+str(len(self.spisok2))+"\nОбщее количество изображений: "+str(int(len(self.spisok)+int(len(self.spisok2)))))
+        q = QMessageBox.information(self, "Информация", "Количество изображений тестовой категории: " + str(
+            len(self.spisok)) + "\nКоличество изображений основной категории: " + str(
+            len(self.spisok2)) + "\nОбщее количество изображений: " + str(
+            int(len(self.spisok) + int(len(self.spisok2)))))
 
     def matrix_and_train(self):
         for v in range(len(self.spisok3)):
@@ -130,7 +119,8 @@ class Example(QWidget):
         self.svm.train(train, cv2.ml.COL_SAMPLE, labels)
         self.svm.save("1.yml")
         self.textbrowser.append("Модель сохранена!")
-        close = QMessageBox.question(self,"Поздравляем!","Ваша модель натренирована!",QMessageBox.Yes | QMessageBox.No)
+        close = QMessageBox.question(self, "Поздравляем!", "Ваша модель натренирована!",
+                                     QMessageBox.Yes | QMessageBox.No)
         if close == QMessageBox.Yes:
             pass
         self.btn_.setVisible(False)
@@ -175,7 +165,7 @@ class Example(QWidget):
 
         # print(self.spisok3)
         for v in range(len(self.spisok2)):
-            lk=list()
+            lkst = list()
             img = cv2.imread(str(self.spisok2[v]))
             gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
             sift = cv2.SIFT_create()
@@ -200,7 +190,6 @@ class Example(QWidget):
         # accuracy = accuracy_score(len(self.spisok3), len(self.spisok3))
         # print('Model Accuracy:',accuracy)
 
-
     def closeEvent(self, event):
         close = QMessageBox.question(self, "Выход", "Вы хотите завершить работу?", QMessageBox.Yes | QMessageBox.No)
         if close == QMessageBox.Yes:
@@ -208,6 +197,7 @@ class Example(QWidget):
         else:
             event.ignore()
 
+
 if __name__ == '__main__':
     app = QApplication(sys.argv)
     win = Example()