update 11-13

Author: makelove

.idea/workspace.xml

@@ -9,11 +9,16 @@
     # 换到 HSV
     hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
     # 定蓝色的 值
-    lower_blue = np.array([110, 50, 50])
-    upper_blue = np.array([130, 255, 255])
+    # lower_blue = np.array([110, 50, 50])
+    # upper_blue = np.array([130, 255, 255])
+
+    #黑色
+    lower_black = np.array([0, 0, 0])
+    upper_black = np.array([180, 255, 30])
 
     # 根据 值构建掩模
-    mask = cv2.inRange(hsv, lower_blue, upper_blue)
+    # mask = cv2.inRange(hsv, lower_blue, upper_blue)
+    mask = cv2.inRange(hsv, lower_black, upper_black)
     # 对原图像和掩模位 算
     res = cv2.bitwise_and(frame, frame, mask=mask)
     # 显示图像
@@ -23,5 +28,5 @@
     k = cv2.waitKey(5) & 0xFF
     if k == 27:
         break
-# 关 窗口
+# 关闭窗口
 cv2.destroyAllWindows()

ch13/13.VideoCapture_blue_object.py …13-颜色空间转换/13.VideoCapture_blue_object.pych13/13.VideoCapture_blue_object.py renamed to ch13-颜色空间转换/13.VideoCapture_blue_object.py ch13/13.VideoCapture_blue_object.py renamed to ch13-颜色空间转换/13.VideoCapture_blue_object.py

@@ -19,4 +19,9 @@
 green=np.uint8([[[0,255,0]]])
 hsv_green=cv2.cvtColor(green,cv2.COLOR_BGR2HSV)
 print hsv_green
-#[[[60 255 255]]]
+#[[[60 255 255]]]
+
+black=np.uint8([[[0,0,0]]])
+hsv_black=cv2.cvtColor(black,cv2.COLOR_BGR2HSV)
+print hsv_black
+#[[[0 0 0]]]

ch13/13.cvtColor_flag.py ch13-颜色空间转换/13.cvtColor_flag.pych13/13.cvtColor_flag.py renamed to ch13-颜色空间转换/13.cvtColor_flag.py

@@ -4,15 +4,16 @@
 import cv2
 
 # im = cv2.imread('test.jpg')#
-im = cv2.imread('../data/star.png')#contour.jpg
+# im = cv2.imread('../data/black-white-rect.png')#contour.jpg #
+im = cv2.imread('../data/chessboard.jpeg')
 imgray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
 
-ret,thresh = cv2.threshold(imgray,50,255,0)
+ret,thresh = cv2.threshold(imgray,0,25,0)
 image, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
 print "contours size: ", len(contours)
 #img = cv2.drawContour(img, contours, -1, (0,255,0), 3)
 
-img = cv2.drawContours(image, contours, 3, (0,0,255), 3)
+img = cv2.drawContours(image, contours, 3, (255,0,0), 3)
 
 cv2.namedWindow("contour.jpg",0)
 cv2.imshow("contour.jpg",img)

ch13/13.find_object_hsv.py ch13-颜色空间转换/13.find_object_hsv.pych13/13.find_object_hsv.py renamed to ch13-颜色空间转换/13.find_object_hsv.py

@@ -6,10 +6,11 @@
 
 import cv2
 import numpy as np
-img = cv2.imread('../data/star.jpg',0)
+img = cv2.imread('../data/star.png',0)
 ret,thresh = cv2.threshold(img,127,255,0)
 # ret, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
-contours,hierarchy = cv2.findContours(thresh, 1, 2)
+# contours,hierarchy = cv2.findContours(thresh, 1, 2)
+image, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
 # contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
 cnt = contours[0]
 M = cv2.moments(cnt)

ch21-Contours/21-findContour.py

@@ -0,0 +1,17 @@
+#-*-coding:utf8-*-#
+__author__ = 'play4fun'
+"""
+create time:15-11-8 下午4:44
+"""
+
+
+
+import cv2
+import numpy as np
+from matplotlib import pyplot as plt
+img = cv2.imread('../data/home.jpg')
+cv2.imshow("src",img)
+hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
+hist = cv2.calcHist( [hsv], [0, 1], None, [180, 256], [0, 180, 0, 256] )
+plt.imshow(hist,interpolation = 'nearest')
+plt.show()

ch21-Contours/21-moments.py

@@ -0,0 +1,25 @@
+#-*-coding:utf8-*-#
+__author__ = 'play4fun'
+"""
+create time:15-10-28 下午7:27
+"""
+
+import cv2
+import numpy as np
+# filename = '../data/chessboard-3.png'
+filename = '../data/corner-detection.jpg'
+
+img = cv2.imread(filename)
+gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+gray = np.float32(gray)
+
+#输入图像必 是 float32 最后一个参数在 0.04 到 0.05 之间
+dst = cv2.cornerHarris(gray,2,3,0.04)
+#result is dilated for marking the corners, not important
+dst = cv2.dilate(dst,None)
+# Threshold for an optimal value, it may vary depending on the image.
+img[dst>0.01*dst.max()]=[0,0,255]
+
+cv2.imshow('dst',img)
+if cv2.waitKey(0) & 0xff == 27:
+    cv2.destroyAllWindows()

ch22/22.3.4.hsv_hist.py

@@ -0,0 +1,43 @@
+# -*-coding:utf8-*-#
+__author__ = 'play4fun'
+"""
+create time:15-10-29 上午7:47
+"""
+
+import cv2
+import numpy as np
+
+filename = '../data/chessboard-2.png'
+img = cv2.imread(filename)
+
+gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+# find Harris corners
+gray = np.float32(gray)
+dst = cv2.cornerHarris(gray, 2, 3, 0.04)
+dst = cv2.dilate(dst, None)
+ret, dst = cv2.threshold(dst, 0.01 * dst.max(), 255, 0)
+dst = np.uint8(dst)
+
+# find centroids
+# connectedComponentsWithStats(InputArray image, OutputArray labels, OutputArray stats,
+# OutputArray centroids, int connectivity=8, int ltype=CV_32S)
+ret, labels, stats, centroids = cv2.connectedComponentsWithStats(dst)
+# define the criteria to stop and refine the corners
+criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.001)
+# Python: cv2.cornerSubPix(image, corners, winSize, zeroZone, criteria)
+# zeroZone – Half of the size of the dead region in the middle of the search zone
+# over which the summation in the formula below is not done. It is used sometimes
+# to avoid possible singularities of the autocorrelation matrix. The value of (-1,-1)
+# indicates that there is no such a size.
+# 返回值由 点坐标组成的一个数组 而 图像
+corners = cv2.cornerSubPix(gray, np.float32(centroids), (5, 5), (-1, -1), criteria)
+# Now draw them
+res = np.hstack((centroids, corners))
+# np.int0 可以用来省略小数点后 的数字，非四舍五入
+res = np.int0(res)
+img[res[:, 1], res[:, 0]] = [0, 0, 255]
+img[res[:, 3], res[:, 2]] = [0, 255, 0]
+
+# cv2.imwrite('subpixel5.png',img)
+cv2.imshow('subpixel5.png', img)
+cv2.waitKey(0)