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python: 'cv2.' -> 'cv.' via 'import cv2 as cv'

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This commit is contained in:
Alexander Alekhin
2017-12-11 12:55:03 +03:00
parent 9665dde678
commit 5560db73bf
162 changed files with 2083 additions and 2084 deletions
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samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py
+13 -13
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@@ -1,4 +1,4 @@
import cv2
import cv2 as cv
import numpy as np
input_image = np.array((
@@ -16,23 +16,23 @@ kernel = np.array((
[1, -1, 1],
[0, 1, 0]), dtype="int")
output_image = cv2.morphologyEx(input_image, cv2.MORPH_HITMISS, kernel)
output_image = cv.morphologyEx(input_image, cv.MORPH_HITMISS, kernel)
rate = 50
kernel = (kernel + 1) * 127
kernel = np.uint8(kernel)
kernel = cv2.resize(kernel, None, fx = rate, fy = rate, interpolation = cv2.INTER_NEAREST)
cv2.imshow("kernel", kernel)
cv2.moveWindow("kernel", 0, 0)
kernel = cv.resize(kernel, None, fx = rate, fy = rate, interpolation = cv.INTER_NEAREST)
cv.imshow("kernel", kernel)
cv.moveWindow("kernel", 0, 0)
input_image = cv2.resize(input_image, None, fx = rate, fy = rate, interpolation = cv2.INTER_NEAREST)
cv2.imshow("Original", input_image)
cv2.moveWindow("Original", 0, 200)
input_image = cv.resize(input_image, None, fx = rate, fy = rate, interpolation = cv.INTER_NEAREST)
cv.imshow("Original", input_image)
cv.moveWindow("Original", 0, 200)
output_image = cv2.resize(output_image, None , fx = rate, fy = rate, interpolation = cv2.INTER_NEAREST)
cv2.imshow("Hit or Miss", output_image)
cv2.moveWindow("Hit or Miss", 500, 200)
output_image = cv.resize(output_image, None , fx = rate, fy = rate, interpolation = cv.INTER_NEAREST)
cv.imshow("Hit or Miss", output_image)
cv.moveWindow("Hit or Miss", 500, 200)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv.waitKey(0)
cv.destroyAllWindows()
samples/python/tutorial_code/imgProc/Pyramids/pyramids.py
+7 -7
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@@ -1,5 +1,5 @@
import sys
import cv2
import cv2 as cv
def main(argv):
@@ -14,7 +14,7 @@ def main(argv):
filename = argv[0] if len(argv) > 0 else "../data/chicky_512.png"
# Load the image
src = cv2.imread(filename)
src = cv.imread(filename)
# Check if image is loaded fine
if src is None:
@@ -26,25 +26,25 @@ def main(argv):
while 1:
rows, cols, _channels = map(int, src.shape)
## [show_image]
cv2.imshow('Pyramids Demo', src)
cv.imshow('Pyramids Demo', src)
## [show_image]
k = cv2.waitKey(0)
k = cv.waitKey(0)
if k == 27:
break
## [pyrup]
elif chr(k) == 'i':
src = cv2.pyrUp(src, dstsize=(2 * cols, 2 * rows))
src = cv.pyrUp(src, dstsize=(2 * cols, 2 * rows))
print ('** Zoom In: Image x 2')
## [pyrup]
## [pyrdown]
elif chr(k) == 'o':
src = cv2.pyrDown(src, dstsize=(cols // 2, rows // 2))
src = cv.pyrDown(src, dstsize=(cols // 2, rows // 2))
print ('** Zoom Out: Image / 2')
## [pyrdown]
## [loop]
cv2.destroyAllWindows()
cv.destroyAllWindows()
return 0
if __name__ == "__main__":
samples/python/tutorial_code/imgProc/Smoothing/smoothing.py
+11 -11
View File
@@ -1,5 +1,5 @@
import sys
import cv2
import cv2 as cv
import numpy as np
# Global Variables
@@ -14,13 +14,13 @@ window_name = 'Smoothing Demo'
def main(argv):
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)
cv.namedWindow(window_name, cv.WINDOW_AUTOSIZE)
# Load the source image
imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
global src
src = cv2.imread(imageName, 1)
src = cv.imread(imageName, 1)
if src is None:
print ('Error opening image')
print ('Usage: smoothing.py [image_name -- default ../data/lena.jpg] \n')
@@ -40,7 +40,7 @@ def main(argv):
## [blur]
for i in range(1, MAX_KERNEL_LENGTH, 2):
dst = cv2.blur(src, (i, i))
dst = cv.blur(src, (i, i))
if display_dst(DELAY_BLUR) != 0:
return 0
## [blur]
@@ -51,7 +51,7 @@ def main(argv):
## [gaussianblur]
for i in range(1, MAX_KERNEL_LENGTH, 2):
dst = cv2.GaussianBlur(src, (i, i), 0)
dst = cv.GaussianBlur(src, (i, i), 0)
if display_dst(DELAY_BLUR) != 0:
return 0
## [gaussianblur]
@@ -62,7 +62,7 @@ def main(argv):
## [medianblur]
for i in range(1, MAX_KERNEL_LENGTH, 2):
dst = cv2.medianBlur(src, i)
dst = cv.medianBlur(src, i)
if display_dst(DELAY_BLUR) != 0:
return 0
## [medianblur]
@@ -74,7 +74,7 @@ def main(argv):
## [bilateralfilter]
# Remember, bilateral is a bit slow, so as value go higher, it takes long time
for i in range(1, MAX_KERNEL_LENGTH, 2):
dst = cv2.bilateralFilter(src, i, i * 2, i / 2)
dst = cv.bilateralFilter(src, i, i * 2, i / 2)
if display_dst(DELAY_BLUR) != 0:
return 0
## [bilateralfilter]
@@ -89,16 +89,16 @@ def display_caption(caption):
global dst
dst = np.zeros(src.shape, src.dtype)
rows, cols, ch = src.shape
cv2.putText(dst, caption,
cv.putText(dst, caption,
(int(cols / 4), int(rows / 2)),
cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255))
cv.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255))
return display_dst(DELAY_CAPTION)
def display_dst(delay):
cv2.imshow(window_name, dst)
c = cv2.waitKey(delay)
cv.imshow(window_name, dst)
c = cv.waitKey(delay)
if c >= 0 : return -1
return 0
samples/python/tutorial_code/imgProc/hough_line_transform/hough_line_transform.py
+7 -7
View File
@@ -1,11 +1,11 @@
import cv2
import cv2 as cv
import numpy as np
img = cv2.imread('../data/sudoku.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
img = cv.imread('../data/sudoku.png')
gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
edges = cv.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLines(edges,1,np.pi/180,200)
lines = cv.HoughLines(edges,1,np.pi/180,200)
for line in lines:
rho,theta = line[0]
a = np.cos(theta)
@@ -17,6 +17,6 @@ for line in lines:
x2 = int(x0 - 1000*(-b))
y2 = int(y0 - 1000*(a))
cv2.line(img,(x1,y1),(x2,y2),(0,0,255),2)
cv.line(img,(x1,y1),(x2,y2),(0,0,255),2)
cv2.imwrite('houghlines3.jpg',img)
cv.imwrite('houghlines3.jpg',img)
samples/python/tutorial_code/imgProc/hough_line_transform/probabilistic_hough_line_transform.py
+7 -7
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@@ -1,12 +1,12 @@
import cv2
import cv2 as cv
import numpy as np
img = cv2.imread('../data/sudoku.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)
img = cv.imread('../data/sudoku.png')
gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
edges = cv.Canny(gray,50,150,apertureSize = 3)
lines = cv.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)
for line in lines:
x1,y1,x2,y2 = line[0]
cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2)
cv.line(img,(x1,y1),(x2,y2),(0,255,0),2)
cv2.imwrite('houghlines5.jpg',img)
cv.imwrite('houghlines5.jpg',img)
samples/python/tutorial_code/imgProc/match_template/match_template.py
+18 -18
View File
@@ -1,5 +1,5 @@
import sys
import cv2
import cv2 as cv
## [global_variables]
use_mask = False
@@ -23,14 +23,14 @@ def main(argv):
## [load_image]
global img
global templ
img = cv2.imread(sys.argv[1], cv2.IMREAD_COLOR)
templ = cv2.imread(sys.argv[2], cv2.IMREAD_COLOR)
img = cv.imread(sys.argv[1], cv.IMREAD_COLOR)
templ = cv.imread(sys.argv[2], cv.IMREAD_COLOR)
if (len(sys.argv) > 3):
global use_mask
use_mask = True
global mask
mask = cv2.imread( sys.argv[3], cv2.IMREAD_COLOR )
mask = cv.imread( sys.argv[3], cv.IMREAD_COLOR )
if ((img is None) or (templ is None) or (use_mask and (mask is None))):
print 'Can\'t read one of the images'
@@ -38,19 +38,19 @@ def main(argv):
## [load_image]
## [create_windows]
cv2.namedWindow( image_window, cv2.WINDOW_AUTOSIZE )
cv2.namedWindow( result_window, cv2.WINDOW_AUTOSIZE )
cv.namedWindow( image_window, cv.WINDOW_AUTOSIZE )
cv.namedWindow( result_window, cv.WINDOW_AUTOSIZE )
## [create_windows]
## [create_trackbar]
trackbar_label = 'Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED'
cv2.createTrackbar( trackbar_label, image_window, match_method, max_Trackbar, MatchingMethod )
cv.createTrackbar( trackbar_label, image_window, match_method, max_Trackbar, MatchingMethod )
## [create_trackbar]
MatchingMethod(match_method)
## [wait_key]
cv2.waitKey(0)
cv.waitKey(0)
return 0
## [wait_key]
@@ -63,32 +63,32 @@ def MatchingMethod(param):
img_display = img.copy()
## [copy_source]
## [match_template]
method_accepts_mask = (cv2.TM_SQDIFF == match_method or match_method == cv2.TM_CCORR_NORMED)
method_accepts_mask = (cv.TM_SQDIFF == match_method or match_method == cv.TM_CCORR_NORMED)
if (use_mask and method_accepts_mask):
result = cv2.matchTemplate(img, templ, match_method, None, mask)
result = cv.matchTemplate(img, templ, match_method, None, mask)
else:
result = cv2.matchTemplate(img, templ, match_method)
result = cv.matchTemplate(img, templ, match_method)
## [match_template]
## [normalize]
cv2.normalize( result, result, 0, 1, cv2.NORM_MINMAX, -1 )
cv.normalize( result, result, 0, 1, cv.NORM_MINMAX, -1 )
## [normalize]
## [best_match]
_minVal, _maxVal, minLoc, maxLoc = cv2.minMaxLoc(result, None)
_minVal, _maxVal, minLoc, maxLoc = cv.minMaxLoc(result, None)
## [best_match]
## [match_loc]
if (match_method == cv2.TM_SQDIFF or match_method == cv2.TM_SQDIFF_NORMED):
if (match_method == cv.TM_SQDIFF or match_method == cv.TM_SQDIFF_NORMED):
matchLoc = minLoc
else:
matchLoc = maxLoc
## [match_loc]
## [imshow]
cv2.rectangle(img_display, matchLoc, (matchLoc[0] + templ.shape[0], matchLoc[1] + templ.shape[1]), (0,0,0), 2, 8, 0 )
cv2.rectangle(result, matchLoc, (matchLoc[0] + templ.shape[0], matchLoc[1] + templ.shape[1]), (0,0,0), 2, 8, 0 )
cv2.imshow(image_window, img_display)
cv2.imshow(result_window, result)
cv.rectangle(img_display, matchLoc, (matchLoc[0] + templ.shape[0], matchLoc[1] + templ.shape[1]), (0,0,0), 2, 8, 0 )
cv.rectangle(result, matchLoc, (matchLoc[0] + templ.shape[0], matchLoc[1] + templ.shape[1]), (0,0,0), 2, 8, 0 )
cv.imshow(image_window, img_display)
cv.imshow(result_window, result)
## [imshow]
pass
samples/python/tutorial_code/imgProc/morph_lines_detection/morph_lines_detection.py
+22 -22
View File
@@ -4,14 +4,14 @@
"""
import numpy as np
import sys
import cv2
import cv2 as cv
def show_wait_destroy(winname, img):
cv2.imshow(winname, img)
cv2.moveWindow(winname, 500, 0)
cv2.waitKey(0)
cv2.destroyWindow(winname)
cv.imshow(winname, img)
cv.moveWindow(winname, 500, 0)
cv.waitKey(0)
cv.destroyWindow(winname)
def main(argv):
@@ -23,7 +23,7 @@ def main(argv):
return -1
# Load the image
src = cv2.imread(argv[0], cv2.IMREAD_COLOR)
src = cv.imread(argv[0], cv.IMREAD_COLOR)
# Check if image is loaded fine
if src is None:
@@ -31,13 +31,13 @@ def main(argv):
return -1
# Show source image
cv2.imshow("src", src)
cv.imshow("src", src)
# [load_image]
# [gray]
# Transform source image to gray if it is not already
if len(src.shape) != 2:
gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
else:
gray = src
@@ -47,9 +47,9 @@ def main(argv):
# [bin]
# Apply adaptiveThreshold at the bitwise_not of gray, notice the ~ symbol
gray = cv2.bitwise_not(gray)
bw = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, \
cv2.THRESH_BINARY, 15, -2)
gray = cv.bitwise_not(gray)
bw = cv.adaptiveThreshold(gray, 255, cv.ADAPTIVE_THRESH_MEAN_C, \
cv.THRESH_BINARY, 15, -2)
# Show binary image
show_wait_destroy("binary", bw)
# [bin]
@@ -66,11 +66,11 @@ def main(argv):
horizontal_size = cols / 30
# Create structure element for extracting horizontal lines through morphology operations
horizontalStructure = cv2.getStructuringElement(cv2.MORPH_RECT, (horizontal_size, 1))
horizontalStructure = cv.getStructuringElement(cv.MORPH_RECT, (horizontal_size, 1))
# Apply morphology operations
horizontal = cv2.erode(horizontal, horizontalStructure)
horizontal = cv2.dilate(horizontal, horizontalStructure)
horizontal = cv.erode(horizontal, horizontalStructure)
horizontal = cv.dilate(horizontal, horizontalStructure)
# Show extracted horizontal lines
show_wait_destroy("horizontal", horizontal)
@@ -82,11 +82,11 @@ def main(argv):
verticalsize = rows / 30
# Create structure element for extracting vertical lines through morphology operations
verticalStructure = cv2.getStructuringElement(cv2.MORPH_RECT, (1, verticalsize))
verticalStructure = cv.getStructuringElement(cv.MORPH_RECT, (1, verticalsize))
# Apply morphology operations
vertical = cv2.erode(vertical, verticalStructure)
vertical = cv2.dilate(vertical, verticalStructure)
vertical = cv.erode(vertical, verticalStructure)
vertical = cv.dilate(vertical, verticalStructure)
# Show extracted vertical lines
show_wait_destroy("vertical", vertical)
@@ -94,7 +94,7 @@ def main(argv):
# [smooth]
# Inverse vertical image
vertical = cv2.bitwise_not(vertical)
vertical = cv.bitwise_not(vertical)
show_wait_destroy("vertical_bit", vertical)
'''
@@ -107,20 +107,20 @@ def main(argv):
'''
# Step 1
edges = cv2.adaptiveThreshold(vertical, 255, cv2.ADAPTIVE_THRESH_MEAN_C, \
cv2.THRESH_BINARY, 3, -2)
edges = cv.adaptiveThreshold(vertical, 255, cv.ADAPTIVE_THRESH_MEAN_C, \
cv.THRESH_BINARY, 3, -2)
show_wait_destroy("edges", edges)
# Step 2
kernel = np.ones((2, 2), np.uint8)
edges = cv2.dilate(edges, kernel)
edges = cv.dilate(edges, kernel)
show_wait_destroy("dilate", edges)
# Step 3
smooth = np.copy(vertical)
# Step 4
smooth = cv2.blur(smooth, (2, 2))
smooth = cv.blur(smooth, (2, 2))
# Step 5
(rows, cols) = np.where(edges != 0)