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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/mosse.py
+30 -30
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@@ -30,7 +30,7 @@ if PY3:
xrange = range
import numpy as np
import cv2
import cv2 as cv
from common import draw_str, RectSelector
import video
@@ -44,7 +44,7 @@ def rnd_warp(a):
T[:2, :2] += (np.random.rand(2, 2) - 0.5)*coef
c = (w/2, h/2)
T[:,2] = c - np.dot(T[:2, :2], c)
return cv2.warpAffine(a, T, (w, h), borderMode = cv2.BORDER_REFLECT)
return cv.warpAffine(a, T, (w, h), borderMode = cv.BORDER_REFLECT)
def divSpec(A, B):
Ar, Ai = A[...,0], A[...,1]
@@ -58,32 +58,32 @@ eps = 1e-5
class MOSSE:
def __init__(self, frame, rect):
x1, y1, x2, y2 = rect
w, h = map(cv2.getOptimalDFTSize, [x2-x1, y2-y1])
w, h = map(cv.getOptimalDFTSize, [x2-x1, y2-y1])
x1, y1 = (x1+x2-w)//2, (y1+y2-h)//2
self.pos = x, y = x1+0.5*(w-1), y1+0.5*(h-1)
self.size = w, h
img = cv2.getRectSubPix(frame, (w, h), (x, y))
img = cv.getRectSubPix(frame, (w, h), (x, y))
self.win = cv2.createHanningWindow((w, h), cv2.CV_32F)
self.win = cv.createHanningWindow((w, h), cv.CV_32F)
g = np.zeros((h, w), np.float32)
g[h//2, w//2] = 1
g = cv2.GaussianBlur(g, (-1, -1), 2.0)
g = cv.GaussianBlur(g, (-1, -1), 2.0)
g /= g.max()
self.G = cv2.dft(g, flags=cv2.DFT_COMPLEX_OUTPUT)
self.G = cv.dft(g, flags=cv.DFT_COMPLEX_OUTPUT)
self.H1 = np.zeros_like(self.G)
self.H2 = np.zeros_like(self.G)
for _i in xrange(128):
a = self.preprocess(rnd_warp(img))
A = cv2.dft(a, flags=cv2.DFT_COMPLEX_OUTPUT)
self.H1 += cv2.mulSpectrums(self.G, A, 0, conjB=True)
self.H2 += cv2.mulSpectrums( A, A, 0, conjB=True)
A = cv.dft(a, flags=cv.DFT_COMPLEX_OUTPUT)
self.H1 += cv.mulSpectrums(self.G, A, 0, conjB=True)
self.H2 += cv.mulSpectrums( A, A, 0, conjB=True)
self.update_kernel()
self.update(frame)
def update(self, frame, rate = 0.125):
(x, y), (w, h) = self.pos, self.size
self.last_img = img = cv2.getRectSubPix(frame, (w, h), (x, y))
self.last_img = img = cv.getRectSubPix(frame, (w, h), (x, y))
img = self.preprocess(img)
self.last_resp, (dx, dy), self.psr = self.correlate(img)
self.good = self.psr > 8.0
@@ -91,19 +91,19 @@ class MOSSE:
return
self.pos = x+dx, y+dy
self.last_img = img = cv2.getRectSubPix(frame, (w, h), self.pos)
self.last_img = img = cv.getRectSubPix(frame, (w, h), self.pos)
img = self.preprocess(img)
A = cv2.dft(img, flags=cv2.DFT_COMPLEX_OUTPUT)
H1 = cv2.mulSpectrums(self.G, A, 0, conjB=True)
H2 = cv2.mulSpectrums( A, A, 0, conjB=True)
A = cv.dft(img, flags=cv.DFT_COMPLEX_OUTPUT)
H1 = cv.mulSpectrums(self.G, A, 0, conjB=True)
H2 = cv.mulSpectrums( A, A, 0, conjB=True)
self.H1 = self.H1 * (1.0-rate) + H1 * rate
self.H2 = self.H2 * (1.0-rate) + H2 * rate
self.update_kernel()
@property
def state_vis(self):
f = cv2.idft(self.H, flags=cv2.DFT_SCALE | cv2.DFT_REAL_OUTPUT )
f = cv.idft(self.H, flags=cv.DFT_SCALE | cv.DFT_REAL_OUTPUT )
h, w = f.shape
f = np.roll(f, -h//2, 0)
f = np.roll(f, -w//2, 1)
@@ -116,12 +116,12 @@ class MOSSE:
def draw_state(self, vis):
(x, y), (w, h) = self.pos, self.size
x1, y1, x2, y2 = int(x-0.5*w), int(y-0.5*h), int(x+0.5*w), int(y+0.5*h)
cv2.rectangle(vis, (x1, y1), (x2, y2), (0, 0, 255))
cv.rectangle(vis, (x1, y1), (x2, y2), (0, 0, 255))
if self.good:
cv2.circle(vis, (int(x), int(y)), 2, (0, 0, 255), -1)
cv.circle(vis, (int(x), int(y)), 2, (0, 0, 255), -1)
else:
cv2.line(vis, (x1, y1), (x2, y2), (0, 0, 255))
cv2.line(vis, (x2, y1), (x1, y2), (0, 0, 255))
cv.line(vis, (x1, y1), (x2, y2), (0, 0, 255))
cv.line(vis, (x2, y1), (x1, y2), (0, 0, 255))
draw_str(vis, (x1, y2+16), 'PSR: %.2f' % self.psr)
def preprocess(self, img):
@@ -130,12 +130,12 @@ class MOSSE:
return img*self.win
def correlate(self, img):
C = cv2.mulSpectrums(cv2.dft(img, flags=cv2.DFT_COMPLEX_OUTPUT), self.H, 0, conjB=True)
resp = cv2.idft(C, flags=cv2.DFT_SCALE | cv2.DFT_REAL_OUTPUT)
C = cv.mulSpectrums(cv.dft(img, flags=cv.DFT_COMPLEX_OUTPUT), self.H, 0, conjB=True)
resp = cv.idft(C, flags=cv.DFT_SCALE | cv.DFT_REAL_OUTPUT)
h, w = resp.shape
_, mval, _, (mx, my) = cv2.minMaxLoc(resp)
_, mval, _, (mx, my) = cv.minMaxLoc(resp)
side_resp = resp.copy()
cv2.rectangle(side_resp, (mx-5, my-5), (mx+5, my+5), 0, -1)
cv.rectangle(side_resp, (mx-5, my-5), (mx+5, my+5), 0, -1)
smean, sstd = side_resp.mean(), side_resp.std()
psr = (mval-smean) / (sstd+eps)
return resp, (mx-w//2, my-h//2), psr
@@ -148,13 +148,13 @@ class App:
def __init__(self, video_src, paused = False):
self.cap = video.create_capture(video_src)
_, self.frame = self.cap.read()
cv2.imshow('frame', self.frame)
cv.imshow('frame', self.frame)
self.rect_sel = RectSelector('frame', self.onrect)
self.trackers = []
self.paused = paused
def onrect(self, rect):
frame_gray = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
frame_gray = cv.cvtColor(self.frame, cv.COLOR_BGR2GRAY)
tracker = MOSSE(frame_gray, rect)
self.trackers.append(tracker)
@@ -164,7 +164,7 @@ class App:
ret, self.frame = self.cap.read()
if not ret:
break
frame_gray = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
frame_gray = cv.cvtColor(self.frame, cv.COLOR_BGR2GRAY)
for tracker in self.trackers:
tracker.update(frame_gray)
@@ -172,11 +172,11 @@ class App:
for tracker in self.trackers:
tracker.draw_state(vis)
if len(self.trackers) > 0:
cv2.imshow('tracker state', self.trackers[-1].state_vis)
cv.imshow('tracker state', self.trackers[-1].state_vis)
self.rect_sel.draw(vis)
cv2.imshow('frame', vis)
ch = cv2.waitKey(10)
cv.imshow('frame', vis)
ch = cv.waitKey(10)
if ch == 27:
break
if ch == ord(' '):