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Commit 4a97075

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fix all
1 parent f5e6d58 commit 4a97075

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30 files changed

+62
-45
lines changed

30 files changed

+62
-45
lines changed

‎ch04-图片/4.1_imread_imshow.py‎

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@@ -10,6 +10,8 @@
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# img = cv2.imread('messi5.jpg', cv2.IMREAD_GRAYSCALE)# Load an color image in grayscale 灰度
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img = cv2.imread('messi5.jpg',cv2.IMREAD_UNCHANGED)#包括图像的 alpha 通道
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img = cv2.resize(img, (640, 480))
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# img.I
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# AttributeError: 'numpy.ndarray' object has no attribute 'I'
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‎ch21-轮廓Contours/21.4.3-形状匹配.py‎

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@@ -20,9 +20,9 @@
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ret, thresh = cv2.threshold(img1, 127, 255, 0)
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ret, thresh2 = cv2.threshold(img2, 127, 255, 0)
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contours, hierarchy = cv2.findContours(thresh, 2, 1)
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image,contours, hierarchy = cv2.findContours(thresh, 2, 1)
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cnt1 = contours[0]
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contours, hierarchy = cv2.findContours(thresh2, 2, 1)
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image,contours, hierarchy = cv2.findContours(thresh2, 2, 1)
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cnt2 = contours[0]
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ret = cv2.matchShapes(cnt1, cnt2, 1, 0.0)

‎ch21-轮廓Contours/star.jpg‎

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‎ch21-轮廓Contours/star2.jpg‎

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‎ch30-Harris角点检测/30.1-OpenCV-Harris角点检测-cornerHarris.py‎

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@@ -13,11 +13,12 @@
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import cv2
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import numpy as np
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filename = '../data/chessboard.jpeg'
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filename = '../data/chessboard.png'
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# filename = '../data/chessboard-3.png'
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# filename = '../data/corner-detection.jpg'
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img = cv2.imread(filename)
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img = cv2.resize(img, (640, 480))
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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gray = np.float32(gray)
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@@ -28,7 +29,7 @@
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# Threshold for an optimal value, it may vary depending on the image.
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img[dst > 0.01 * dst.max()] = [0, 0, 255]
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cv2.namedWindow('dst', cv2.WINDOW_NORMAL)
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cv2.imshow('dst', img)
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cv2.waitKey(0)
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cv2.destroyAllWindows()

‎ch31-Shi-Tomasi角点检测-适合于跟踪的图像特征/goodFeaturesToTrack.py‎

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@@ -18,7 +18,8 @@
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import cv2
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from matplotlib import pyplot as plt
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filename = '../data/corner-detection.jpg'
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# filename = '../data/corner-detection.jpg'
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filename = '../data/blox.jpg'
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img = cv2.imread(filename)
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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‎ch33-介绍SURF/surf.py‎

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@@ -13,7 +13,7 @@
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import cv2
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import matplotlib.pyplot as plt
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img = cv2.imread('fly.png', 0)
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img = cv2.imread('../data/butterfly.jpg', 0)
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# Create SURF object. You can specify params here or later. # Here I set Hessian Threshold to 400
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# surf = cv2.SURF(400)
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surf = cv2.xfeatures2d.SURF_create(400)
@@ -47,7 +47,8 @@
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print(surf.getExtended())
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# False
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# So we make it to True to get 128-dim descriptors.
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surf.extended = True
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# surf.extended = True
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surf.setExtended(True)
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kp, des = surf.detectAndCompute(img, None)
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print(surf.descriptorSize())
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# 128

‎ch34-角点检测的FAST算法/fast.py‎

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import cv2
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from matplotlib import pyplot as plt
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img = cv2.imread('simple.jpg', 0)
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img = cv2.imread('../data/blox.jpg', 0)
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# Initiate FAST object with default values
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fast = cv2.FastFeatureDetector_create()

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