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232 lines
6.9 KiB
Python
Executable File
232 lines
6.9 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Video capture sample.
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Sample shows how VideoCapture class can be used to acquire video
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frames from a camera of a movie file. Also the sample provides
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an example of procedural video generation by an object, mimicking
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the VideoCapture interface (see Chess class).
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'create_capture' is a convenience function for capture creation,
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falling back to procedural video in case of error.
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Usage:
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video.py [--shotdir <shot path>] [source0] [source1] ...'
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sourceN is an
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- integer number for camera capture
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- name of video file
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- synth:<params> for procedural video
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Synth examples:
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synth:bg=lena.jpg:noise=0.1
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synth:class=chess:bg=lena.jpg:noise=0.1:size=640x480
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Keys:
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ESC - exit
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SPACE - save current frame to <shot path> directory
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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import re
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from numpy import pi, sin, cos
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# built-in modules
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from time import clock
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# local modules
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from tst_scene_render import TestSceneRender
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import common
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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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if bg is not None:
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self.bg = cv.imread(cv.samples.findFile(bg))
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h, w = self.bg.shape[:2]
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self.frame_size = (w, h)
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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 = cv.resize(self.bg, self.frame_size)
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self.noise = float(noise)
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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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if self.bg is None:
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buf = np.zeros((h, w, 3), np.uint8)
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else:
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buf = self.bg.copy()
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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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cv.randn(noise, np.zeros(3), np.ones(3)*255*self.noise)
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buf = cv.add(buf, noise, dtype=cv.CV_8UC3)
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return True, buf
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def isOpened(self):
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return True
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class Book(VideoSynthBase):
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def __init__(self, **kw):
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super(Book, self).__init__(**kw)
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backGr = cv.imread(cv.samples.findFile('graf1.png'))
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fgr = cv.imread(cv.samples.findFile('box.png'))
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self.render = TestSceneRender(backGr, fgr, speed = 1)
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def read(self, dst=None):
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noise = np.zeros(self.render.sceneBg.shape, np.int8)
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cv.randn(noise, np.zeros(3), np.ones(3)*255*self.noise)
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return True, cv.add(self.render.getNextFrame(), noise, dtype=cv.CV_8UC3)
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class Cube(VideoSynthBase):
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def __init__(self, **kw):
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super(Cube, self).__init__(**kw)
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self.render = TestSceneRender(cv.imread(cv.samples.findFile('pca_test1.jpg')), deformation = True, speed = 1)
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def read(self, dst=None):
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noise = np.zeros(self.render.sceneBg.shape, np.int8)
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cv.randn(noise, np.zeros(3), np.ones(3)*255*self.noise)
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return True, cv.add(self.render.getNextFrame(), noise, dtype=cv.CV_8UC3)
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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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self.t = 0
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def draw_quads(self, img, quads, color = (0, 255, 0)):
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img_quads = cv.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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cv.fillConvexPoly(img, np.int32(q*4), color, cv.LINE_AA, shift=2)
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def render(self, dst):
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t = self.t
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self.t += 1.0/30.0
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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, book=Book, cube=Cube)
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presets = dict(
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empty = 'synth:',
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lena = 'synth:bg=lena.jpg:noise=0.1',
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chess = 'synth:class=chess:bg=lena.jpg:noise=0.1:size=640x480',
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book = 'synth:class=book:bg=graf1.png:noise=0.1:size=640x480',
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cube = 'synth:class=cube:bg=pca_test1.jpg:noise=0.0:size=640x480'
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)
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def create_capture(source = 0, fallback = presets['chess']):
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'''source: <int> or '<int>|<filename>|synth [:<param_name>=<value> [:...]]'
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'''
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source = str(source).strip()
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# Win32: handle drive letter ('c:', ...)
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source = re.sub(r'(^|=)([a-zA-Z]):([/\\a-zA-Z0-9])', r'\1?disk\2?\3', source)
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chunks = source.split(':')
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chunks = [re.sub(r'\?disk([a-zA-Z])\?', r'\1:', s) for s in chunks]
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source = chunks[0]
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try: source = int(source)
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except ValueError: pass
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params = dict( s.split('=') for s in chunks[1:] )
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cap = None
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if source == 'synth':
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Class = classes.get(params.get('class', None), VideoSynthBase)
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try: cap = Class(**params)
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except: pass
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else:
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cap = cv.VideoCapture(source)
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if 'size' in params:
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w, h = map(int, params['size'].split('x'))
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cap.set(cv.CAP_PROP_FRAME_WIDTH, w)
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cap.set(cv.CAP_PROP_FRAME_HEIGHT, h)
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if cap is None or not cap.isOpened():
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print('Warning: unable to open video source: ', source)
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if fallback is not None:
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return create_capture(fallback, None)
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return cap
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if __name__ == '__main__':
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import sys
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import getopt
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print(__doc__)
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args, sources = getopt.getopt(sys.argv[1:], '', 'shotdir=')
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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 = [ 0 ]
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caps = list(map(create_capture, sources))
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shot_idx = 0
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while True:
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imgs = []
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for i, cap in enumerate(caps):
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ret, img = cap.read()
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imgs.append(img)
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cv.imshow('capture %d' % i, img)
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ch = cv.waitKey(1)
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if ch == 27:
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break
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if ch == ord(' '):
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for i, img in enumerate(imgs):
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fn = '%s/shot_%d_%03d.bmp' % (shotdir, i, shot_idx)
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cv.imwrite(fn, img)
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print(fn, 'saved')
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shot_idx += 1
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cv.destroyAllWindows()
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