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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/find_obj.py
+36 -36
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@@ -18,7 +18,7 @@ USAGE
from __future__ import print_function
import numpy as np
import cv2
import cv2 as cv
from common import anorm, getsize
FLANN_INDEX_KDTREE = 1 # bug: flann enums are missing
@@ -28,33 +28,33 @@ FLANN_INDEX_LSH = 6
def init_feature(name):
chunks = name.split('-')
if chunks[0] == 'sift':
detector = cv2.xfeatures2d.SIFT_create()
norm = cv2.NORM_L2
detector = cv.xfeatures2d.SIFT_create()
norm = cv.NORM_L2
elif chunks[0] == 'surf':
detector = cv2.xfeatures2d.SURF_create(800)
norm = cv2.NORM_L2
detector = cv.xfeatures2d.SURF_create(800)
norm = cv.NORM_L2
elif chunks[0] == 'orb':
detector = cv2.ORB_create(400)
norm = cv2.NORM_HAMMING
detector = cv.ORB_create(400)
norm = cv.NORM_HAMMING
elif chunks[0] == 'akaze':
detector = cv2.AKAZE_create()
norm = cv2.NORM_HAMMING
detector = cv.AKAZE_create()
norm = cv.NORM_HAMMING
elif chunks[0] == 'brisk':
detector = cv2.BRISK_create()
norm = cv2.NORM_HAMMING
detector = cv.BRISK_create()
norm = cv.NORM_HAMMING
else:
return None, None
if 'flann' in chunks:
if norm == cv2.NORM_L2:
if norm == cv.NORM_L2:
flann_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
else:
flann_params= dict(algorithm = FLANN_INDEX_LSH,
table_number = 6, # 12
key_size = 12, # 20
multi_probe_level = 1) #2
matcher = cv2.FlannBasedMatcher(flann_params, {}) # bug : need to pass empty dict (#1329)
matcher = cv.FlannBasedMatcher(flann_params, {}) # bug : need to pass empty dict (#1329)
else:
matcher = cv2.BFMatcher(norm)
matcher = cv.BFMatcher(norm)
return detector, matcher
@@ -76,12 +76,12 @@ def explore_match(win, img1, img2, kp_pairs, status = None, H = None):
vis = np.zeros((max(h1, h2), w1+w2), np.uint8)
vis[:h1, :w1] = img1
vis[:h2, w1:w1+w2] = img2
vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR)
vis = cv.cvtColor(vis, cv.COLOR_GRAY2BGR)
if H is not None:
corners = np.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]])
corners = np.int32( cv2.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0) )
cv2.polylines(vis, [corners], True, (255, 255, 255))
corners = np.int32( cv.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0) )
cv.polylines(vis, [corners], True, (255, 255, 255))
if status is None:
status = np.ones(len(kp_pairs), np.bool_)
@@ -96,26 +96,26 @@ def explore_match(win, img1, img2, kp_pairs, status = None, H = None):
for (x1, y1), (x2, y2), inlier in zip(p1, p2, status):
if inlier:
col = green
cv2.circle(vis, (x1, y1), 2, col, -1)
cv2.circle(vis, (x2, y2), 2, col, -1)
cv.circle(vis, (x1, y1), 2, col, -1)
cv.circle(vis, (x2, y2), 2, col, -1)
else:
col = red
r = 2
thickness = 3
cv2.line(vis, (x1-r, y1-r), (x1+r, y1+r), col, thickness)
cv2.line(vis, (x1-r, y1+r), (x1+r, y1-r), col, thickness)
cv2.line(vis, (x2-r, y2-r), (x2+r, y2+r), col, thickness)
cv2.line(vis, (x2-r, y2+r), (x2+r, y2-r), col, thickness)
cv.line(vis, (x1-r, y1-r), (x1+r, y1+r), col, thickness)
cv.line(vis, (x1-r, y1+r), (x1+r, y1-r), col, thickness)
cv.line(vis, (x2-r, y2-r), (x2+r, y2+r), col, thickness)
cv.line(vis, (x2-r, y2+r), (x2+r, y2-r), col, thickness)
vis0 = vis.copy()
for (x1, y1), (x2, y2), inlier in zip(p1, p2, status):
if inlier:
cv2.line(vis, (x1, y1), (x2, y2), green)
cv.line(vis, (x1, y1), (x2, y2), green)
cv2.imshow(win, vis)
cv.imshow(win, vis)
def onmouse(event, x, y, flags, param):
cur_vis = vis
if flags & cv2.EVENT_FLAG_LBUTTON:
if flags & cv.EVENT_FLAG_LBUTTON:
cur_vis = vis0.copy()
r = 8
m = (anorm(np.array(p1) - (x, y)) < r) | (anorm(np.array(p2) - (x, y)) < r)
@@ -124,15 +124,15 @@ def explore_match(win, img1, img2, kp_pairs, status = None, H = None):
for i in idxs:
(x1, y1), (x2, y2) = p1[i], p2[i]
col = (red, green)[status[i]]
cv2.line(cur_vis, (x1, y1), (x2, y2), col)
cv.line(cur_vis, (x1, y1), (x2, y2), col)
kp1, kp2 = kp_pairs[i]
kp1s.append(kp1)
kp2s.append(kp2)
cur_vis = cv2.drawKeypoints(cur_vis, kp1s, None, flags=4, color=kp_color)
cur_vis[:,w1:] = cv2.drawKeypoints(cur_vis[:,w1:], kp2s, None, flags=4, color=kp_color)
cur_vis = cv.drawKeypoints(cur_vis, kp1s, None, flags=4, color=kp_color)
cur_vis[:,w1:] = cv.drawKeypoints(cur_vis[:,w1:], kp2s, None, flags=4, color=kp_color)
cv2.imshow(win, cur_vis)
cv2.setMouseCallback(win, onmouse)
cv.imshow(win, cur_vis)
cv.setMouseCallback(win, onmouse)
return vis
@@ -149,8 +149,8 @@ if __name__ == '__main__':
fn1 = '../data/box.png'
fn2 = '../data/box_in_scene.png'
img1 = cv2.imread(fn1, 0)
img2 = cv2.imread(fn2, 0)
img1 = cv.imread(fn1, 0)
img2 = cv.imread(fn2, 0)
detector, matcher = init_feature(feature_name)
if img1 is None:
@@ -176,7 +176,7 @@ if __name__ == '__main__':
raw_matches = matcher.knnMatch(desc1, trainDescriptors = desc2, k = 2) #2
p1, p2, kp_pairs = filter_matches(kp1, kp2, raw_matches)
if len(p1) >= 4:
H, status = cv2.findHomography(p1, p2, cv2.RANSAC, 5.0)
H, status = cv.findHomography(p1, p2, cv.RANSAC, 5.0)
print('%d / %d inliers/matched' % (np.sum(status), len(status)))
else:
H, status = None, None
@@ -185,5 +185,5 @@ if __name__ == '__main__':
_vis = explore_match(win, img1, img2, kp_pairs, status, H)
match_and_draw('find_obj')
cv2.waitKey()
cv2.destroyAllWindows()
cv.waitKey()
cv.destroyAllWindows()