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use cv2 function
added color_histogram.py sample work on VideoSynth (chessboard)
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@ -3,7 +3,7 @@ browse.py shows how to implement a simple hi resolution image navigation
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'''
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import numpy as np
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import cv2, cv
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import cv2
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import sys
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print 'This sample shows how to implement a simple hi resolution image navigation.'
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@ -20,7 +20,7 @@ else:
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img = np.zeros((sz, sz), np.uint8)
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track = np.cumsum(np.random.rand(500000, 2)-0.5, axis=0)
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track = np.int32(track*10 + (sz/2, sz/2))
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cv2.polylines(img, [track], 0, 255, 1, cv.CV_AA)
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cv2.polylines(img, [track], 0, 255, 1, cv2.CV_AA)
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small = img
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for i in xrange(3):
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@ -34,5 +34,5 @@ def onmouse(event, x, y, flags, param):
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cv2.imshow('zoom', zoom)
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cv2.imshow('preview', small)
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cv.SetMouseCallback('preview', onmouse, None)
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cv2.setMouseCallback('preview', onmouse, None)
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cv2.waitKey()
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@ -1,20 +1,12 @@
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import numpy as np
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import cv2, cv
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import os
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from common import splitfn
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USAGE = '''
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USAGE: calib.py [--save <filename>] [--debug <output path>] [<image mask>]
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'''
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class Bunch:
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def __init__(self, **kwds):
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self.__dict__.update(kwds)
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def splitfn(fn):
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path, fn = os.path.split(fn)
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name, ext = os.path.splitext(fn)
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return path, name, ext
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if __name__ == '__main__':
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@ -42,7 +34,7 @@ if __name__ == '__main__':
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found, corners = cv2.findChessboardCorners(img, pattern_size)
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if found:
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term = ( cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1 )
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cv2.cornerSubPix(img, corners, (11, 11), (-1, -1), term)
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cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
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if debug_dir:
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vis = cv2.cvtColor(img, cv.CV_GRAY2BGR)
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cv2.drawChessboardCorners(vis, pattern_size, corners, found)
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@ -7,7 +7,7 @@
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'''
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import numpy as np
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import cv, cv2
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import cv2, cv
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def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
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@ -55,9 +55,9 @@ if __name__ == '__main__':
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cv2.imshow('dst', dst)
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cv2.namedWindow('control', 0)
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cv.CreateTrackbar('sigma', 'control', 9, 15, nothing)
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cv.CreateTrackbar('blend', 'control', 7, 10, nothing)
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cv.CreateTrackbar('str_sigma', 'control', 9, 15, nothing)
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cv2.createTrackbar('sigma', 'control', 9, 15, nothing)
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cv2.createTrackbar('blend', 'control', 7, 10, nothing)
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cv2.createTrackbar('str_sigma', 'control', 9, 15, nothing)
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print 'Press SPACE to update the image\n'
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51
samples/python2/color_histogram.py
Normal file
51
samples/python2/color_histogram.py
Normal file
@ -0,0 +1,51 @@
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import numpy as np
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import cv2, cv
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from time import clock
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import sys
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import video
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hsv_map = np.zeros((180, 256, 3), np.uint8)
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h, s = np.indices(hsv_map.shape[:2])
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hsv_map[:,:,0] = h
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hsv_map[:,:,1] = s
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hsv_map[:,:,2] = 255
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hsv_map = cv2.cvtColor(hsv_map, cv.CV_HSV2BGR)
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cv2.imshow('hsv_map', hsv_map)
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cv2.namedWindow('hist', 0)
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hist_scale = 10
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def set_scale(val):
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global hist_scale
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hist_scale = val
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cv.CreateTrackbar('scale', 'hist', hist_scale, 32, set_scale)
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try: fn = sys.argv[1]
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except: fn = 'synth:bg=../cpp/baboon.jpg:class=chess:noise=0.05'
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cam = video.create_capture(fn)
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t = clock()
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while True:
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flag, frame = cam.read()
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cv2.imshow('camera', frame)
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small = cv2.pyrDown(frame)
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hsv = cv2.cvtColor(small, cv.CV_BGR2HSV)
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dark = hsv[...,2] < 32
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hsv[dark] = 0
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h = cv2.calcHist( [hsv], [0, 1], None, [180, 256], [0, 180, 0, 256] )
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h = np.clip(h*0.005*hist_scale, 0, 1)
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vis = hsv_map*h[:,:,np.newaxis] / 255.0
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cv2.imshow('hist', vis)
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t1 = clock()
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#print (t1-t)*1000
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t = t1
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ch = cv2.waitKey(1)
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if ch == 27:
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break
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@ -1,8 +1,11 @@
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import numpy as np
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import cv2
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import os
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def to_list(a):
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return [tuple(p) for p in a]
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def splitfn(fn):
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path, fn = os.path.split(fn)
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name, ext = os.path.splitext(fn)
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return path, name, ext
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def anorm2(a):
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return (a*a).sum(-1)
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@ -37,36 +40,15 @@ def lookat(eye, target, up = (0, 0, 1)):
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right = np.cross(fwd, up)
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right /= anorm(right)
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down = np.cross(fwd, right)
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Rt = np.zeros((3, 4))
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Rt[:,:3] = [right, down, fwd]
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Rt[:,3] = -np.dot(Rt[:,:3], eye)
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return Rt
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R = np.float64([right, down, fwd])
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tvec = -np.dot(R, eye)
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return R, tvec
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def mtx2rvec(R):
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pass
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if __name__ == '__main__':
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import cv2
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from time import clock
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'''
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w, h = 640, 480
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while True:
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img = np.zeros((h, w, 3), np.uint8)
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t = clock()
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eye = [5*cos(t), 5*sin(t), 3]
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Rt = lookat(eye, [0, 0, 0])
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'''
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eye = [1, -4, 3]
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target = [0, 0, 0]
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Rt = lookat(eye, [0, 0, 0])
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print Rt
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p = [0, 0, 0]
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print cv2.transform(np.float64([[p]]), Rt)
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print cv2.SVDecomp(Rt[:,:3])
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w, u, vt = cv2.SVDecomp(R - np.eye(3))
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p = vt[0] + u[:,0]*w[0] # same as np.dot(R, vt[0])
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c = np.dot(vt[0], p)
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s = np.dot(vt[1], p)
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axis = np.cross(vt[0], vt[1])
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return axis * np.arctan2(s, c)
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@ -3,14 +3,14 @@ import video
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import sys
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try: fn = sys.argv[1]
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except: fn = video.presets['lena']
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except: fn = video.presets['chess']
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def nothing(*arg):
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pass
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cv2.namedWindow('edge')
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cv.CreateTrackbar('thrs1', 'edge', 2000, 5000, nothing)
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cv.CreateTrackbar('thrs2', 'edge', 4000, 5000, nothing)
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cv2.createTrackbar('thrs1', 'edge', 2000, 5000, nothing)
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cv2.createTrackbar('thrs2', 'edge', 4000, 5000, nothing)
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cap = video.create_capture(fn)
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while True:
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@ -1,11 +1,10 @@
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import numpy as np
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import cv2
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from time import clock
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from numpy import pi, sin, cos
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import common
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def lookat(cam_pos, target_pos, up = ()):
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dp = cam_pos - target_pos
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class VideoSynth(object):
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class VideoSynthBase(object):
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def __init__(self, size=None, noise=0.0, bg = None, **params):
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self.bg = None
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self.frame_size = (640, 480)
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@ -17,19 +16,13 @@ class VideoSynth(object):
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if size is not None:
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w, h = map(int, size.split('x'))
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self.frame_size = (w, h)
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self.bg = cv2.resize(bg, self.frame_size)
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self.bg = cv2.resize(self.bg, self.frame_size)
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self.noise = float(noise)
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w, h = self.frame_size
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self.K = np.float64([[1.0/w, 0.0, 0.5*(w-1)],
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[ 0.0, 1.0/w, 0.5*(h-1)],
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[ 0.0, 0.0, 1.0]])
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def draw_layers(self, dst):
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def render(self, dst):
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pass
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def read(self, dst=None):
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w, h = self.frame_size
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@ -38,7 +31,7 @@ class VideoSynth(object):
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else:
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buf = self.bg.copy()
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self.draw_layers(buf)
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self.render(buf)
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if self.noise > 0.0:
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noise = np.zeros((h, w, 3), np.int8)
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@ -46,6 +39,54 @@ class VideoSynth(object):
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buf = cv2.add(buf, noise, dtype=cv2.CV_8UC3)
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return True, buf
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class Chess(VideoSynthBase):
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def __init__(self, **kw):
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super(Chess, self).__init__(**kw)
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w, h = self.frame_size
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self.grid_size = sx, sy = 10, 7
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white_quads = []
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black_quads = []
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for i, j in np.ndindex(sy, sx):
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q = [[j, i, 0], [j+1, i, 0], [j+1, i+1, 0], [j, i+1, 0]]
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[white_quads, black_quads][(i + j) % 2].append(q)
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self.white_quads = np.float32(white_quads)
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self.black_quads = np.float32(black_quads)
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fx = 0.9
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self.K = np.float64([[fx*w, 0, 0.5*(w-1)],
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[0, fx*w, 0.5*(h-1)],
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[0.0,0.0, 1.0]])
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self.dist_coef = np.float64([-0.2, 0.1, 0, 0])
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def draw_quads(self, img, quads, color = (0, 255, 0)):
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img_quads = cv2.projectPoints(quads.reshape(-1, 3), self.rvec, self.tvec, self.K, self.dist_coef) [0]
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img_quads.shape = quads.shape[:2] + (2,)
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for q in img_quads:
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cv2.fillConvexPoly(img, np.int32(q*4), color, cv2.CV_AA, shift=2)
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def render(self, dst):
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t = clock()
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sx, sy = self.grid_size
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center = np.array([0.5*sx, 0.5*sy, 0.0])
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phi = pi/3 + sin(t*3)*pi/8
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c, s = cos(phi), sin(phi)
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ofs = np.array([sin(1.2*t), cos(1.8*t), 0]) * sx * 0.2
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eye_pos = center + np.array([cos(t)*c, sin(t)*c, s]) * 15.0 + ofs
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target_pos = center + ofs
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R, self.tvec = common.lookat(eye_pos, target_pos)
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self.rvec = common.mtx2rvec(R)
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self.draw_quads(dst, self.white_quads, (245, 245, 245))
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self.draw_quads(dst, self.black_quads, (10, 10, 10))
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classes = dict(chess=Chess)
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def create_capture(source):
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'''
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@ -59,13 +100,17 @@ def create_capture(source):
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if source.startswith('synth'):
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ss = filter(None, source.split(':'))
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params = dict( s.split('=') for s in ss[1:] )
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return VideoSynth(**params)
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try: Class = classes[params['class']]
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except: Class = VideoSynthBase
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return Class(**params)
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return cv2.VideoCapture(source)
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presets = dict(
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empty = 'synth:',
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lena = 'synth:bg=../cpp/lena.jpg:noise=0.1'
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lena = 'synth:bg=../cpp/lena.jpg:noise=0.1',
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chess = 'synth:class=chess:bg=../cpp/lena.jpg:noise=0.1:size=640x480'
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)
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if __name__ == '__main__':
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@ -80,7 +125,7 @@ if __name__ == '__main__':
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args = dict(args)
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shotdir = args.get('--shotdir', '.')
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if len(sources) == 0:
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sources = [ presets['lena'] ]
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sources = [ presets['chess'] ]
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print 'Press SPACE to save current frame'
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