add folder img

1/5.py

@@ -1,10 +1,9 @@
-import cv2
+import cv2 as cv
 
-if __name__ == "__main__":
-    lenna = cv2.imread(r"src.jpg")
-    print(type(lenna))
-    cv2.namedWindow("Lena", cv2.WINDOW_AUTOSIZE)
-    cv2.imshow("Lena", lenna)
-    cv2.waitKey(0)
-    cv2.destroyWindow("Lena")
-    cv2.imwrite(r"1\imwrite.png", lenna, (cv2.IMWRITE_PNG_COMPRESSION, 5))
+lenna = cv.imread(r"img\iris.jpg")
+print(type(lenna))
+cv.namedWindow("Lena", cv.WINDOW_AUTOSIZE)
+cv.imshow("Lena", lenna)
+cv.waitKey(0)
+cv.destroyWindow("Lena")
+cv.imwrite(r"1\imwrite.png", lenna, (cv.IMWRITE_PNG_COMPRESSION, 5))

1/6.py

@@ -1,10 +1,9 @@
-import cv2
+import cv2 as cv
 import matplotlib.pyplot as plt
 
-if __name__ == "__main__":
-    plt.rcParams["font.family"] = ["SimHei"]
-    plt.rcParams["axes.unicode_minus"] = False
-    img_BGR = cv2.imread(r"src.jpg")
-    img_RGB = cv2.cvtColor(img_BGR, cv2.COLOR_BGR2RGB)
-    plt.imshow(img_RGB)
-    plt.show()
+plt.rcParams["font.family"] = ["SimHei"]
+plt.rcParams["axes.unicode_minus"] = False
+img_BGR = cv.imread(r"img\iris.jpg")
+img_RGB = cv.cvtColor(img_BGR, cv.COLOR_BGR2RGB)
+plt.imshow(img_RGB)
+plt.show()

1/7.py

@@ -1,6 +1,5 @@
-import cv2
+import cv2 as cv
 import matplotlib.pyplot as plt
-import math
 import numpy as np
 
 
@@ -8,7 +7,7 @@ def createBox():
     box = np.zeros((100, 100), np.uint8) + 255
     print(type(box))
     shape = box.shape
-    box = cv2.circle(box, (30, 50), 25, 0, -1)
+    box = cv.circle(box, (30, 50), 25, 0, -1)  # type: ignore
     for i in range(shape[0]):
         for j in range(shape[1]):
             if j in range(45, 95) and i in range(25, 75):
@@ -29,7 +28,7 @@ if __name__ == "__main__":
     image0 = createBox()
     plt.figure()
     plt.subplot(1, 2, 1)
-    plt.imshow(image0, vmin=0, vmax=255, cmap=plt.cm.gray)
+    plt.imshow(image0, vmin=0, vmax=255, cmap=plt.cm.gray)  # type: ignore
     plt.title("idel image")
     image_hist0 = histogram(image0)
     plt.subplot(1, 2, 2)

2/1.py

@@ -20,7 +20,7 @@ def histogram_equalization(im):
 
 
 if __name__ == "__main__":
-    im = cv.imread(r"src.jpg", cv.IMREAD_GRAYSCALE)
+    im = cv.imread(r"img\iris.jpg", cv.IMREAD_GRAYSCALE)
     im1 = global_linear_transmation(im, 0, 150)
     im2 = global_linear_transmation(im, 100)
     im3 = global_linear_transmation(im, 50, 150)
@@ -39,11 +39,11 @@ if __name__ == "__main__":
     plt.imshow(im4, cmap="gray")
     plt.title("equalized")
     plt.subplot(245)
-    plt.hist(im1.flatten(), 256, [0, 256])
+    plt.hist(im1.flatten(), 256, [0, 256])  # type: ignore
     plt.subplot(246)
-    plt.hist(im2.flatten(), 256, [0, 256])
+    plt.hist(im2.flatten(), 256, [0, 256])  # type: ignore
     plt.subplot(247)
-    plt.hist(im3.flatten(), 256, [0, 256])
+    plt.hist(im3.flatten(), 256, [0, 256])  # type: ignore
     plt.subplot(248)
-    plt.hist(im4.flatten(), 256, [0, 256])
+    plt.hist(im4.flatten(), 256, [0, 256])  # type: ignore
     plt.show()

2/2.py

@@ -10,7 +10,7 @@ def gamma_trans(img, gamma=1.0):
 
 
 if __name__ == "__main__":
-    im = cv.imread(r"src.jpg", cv.IMREAD_GRAYSCALE)
+    im = cv.imread(r"img\iris.jpg", cv.IMREAD_GRAYSCALE)
     im1 = gamma_trans(im, 0.5)
     im2 = gamma_trans(im, 1.5)
     plt.figure()

2/3.py

@@ -1,9 +1,9 @@
 import cv2 as cv
-from matplotlib import pyplot as plt
+import matplotlib.pyplot as plt
 import numpy as np
 
 if __name__ == "__main__":
-    img = cv.imread(r"src.jpg", 0)
+    img = cv.imread(r"img\iris.jpg", 0)
     fil1 = 1 / 16 * np.array([[1, 2, 1], [2, 4, 2], [1, 2, 1]])
     fil2 = 1 / 9 * np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]])
     fil3 = 1 / 10 * np.array([[1, 1, 1], [1, 2, 1], [1, 1, 1]])
@@ -12,7 +12,6 @@ if __name__ == "__main__":
     ImgSmoothed2 = cv.filter2D(img, -1, fil2, borderType=cv.BORDER_DEFAULT)
     ImgSmoothed3 = cv.filter2D(img, -1, fil3, borderType=cv.BORDER_DEFAULT)
     ImgSharp = cv.filter2D(img, -1, fil4, borderType=cv.BORDER_DEFAULT)
-
     plt.figure()
     plt.subplot(221)
     plt.imshow(ImgSmoothed1, cmap="gray")

2/4.py

@@ -33,15 +33,15 @@ def addGaussianNoise(src, means, sigma):
 
 
 if __name__ == "__main__":
-    im = cv.imread(r"src.jpg", cv.IMREAD_GRAYSCALE)
+    im = cv.imread(r"img\iris.jpg", cv.IMREAD_GRAYSCALE)
     im1 = addSaltAndPepper(im, 0.1)
     im11 = cv.blur(im1, (3, 3))
     im12 = cv.medianBlur(im1, 3)
     im13 = cv.GaussianBlur(im1, (3, 3), 1)
     im2 = addGaussianNoise(im, 0, 0.1)
-    im21 = cv.blur(im2, (3, 3))
-    im22 = cv.medianBlur(im2, 3)
-    im23 = cv.GaussianBlur(im2, (3, 3), 1)
+    im21 = cv.blur(im2, (3, 3))  # type: ignore
+    im22 = cv.medianBlur(im2, 3)  # type: ignore
+    im23 = cv.GaussianBlur(im2, (3, 3), 1)  # type: ignore
     plt.figure()
     plt.subplot(241)
     plt.imshow(im1, cmap="gray")

2/5.py

@@ -3,12 +3,11 @@ from matplotlib import pyplot as plt
 import numpy as np
 
 if __name__ == "__main__":
-    img = cv.imread(r"src.jpg", 0)
+    img = cv.imread(r"img\iris.jpg", 0)
     lplc = np.array([[0, -1, 0], [-1, 4, -1], [0, -1, 0]])
     lplcEnhance = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
     ImgLplc = cv.filter2D(img, -1, lplc, borderType=cv.BORDER_DEFAULT)
     ImgLplcEnhance = cv.filter2D(img, -1, lplcEnhance, borderType=cv.BORDER_DEFAULT)
-
     plt.figure()
     plt.subplot(131)
     plt.imshow(img, cmap="gray")