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video.py
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video.py
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#!/usr/bin/env python
'''
Video capture sample.
Sample shows how VideoCapture class can be used to acquire video
frames from a camera of a movie file. Also the sample provides
an example of procedural video generation by an object, mimicking
the VideoCapture interface (see Chess class).
'create_capture' is a convinience function for capture creation,
falling back to procedural video in case of error.
Usage:
video.py [--shotdir <shot path>] [source0] [source1] ...'
sourceN is an
- integer number for camera capture
- name of video file
- synth:<params> for procedural video
Synth examples:
synth:bg=../data/lena.jpg:noise=0.1
synth:class=chess:bg=../data/lena.jpg:noise=0.1:size=640x480
Keys:
ESC - exit
SPACE - save current frame to <shot path> directory
'''
import numpy as np
from numpy import pi, sin, cos
import cv2
# built-in modules
from time import clock
# local modules
import common
class VideoSynthBase(object):
def __init__(self, size=None, noise=0.0, bg = None, **params):
self.bg = None
self.frame_size = (640, 480)
if bg is not None:
self.bg = cv2.imread(bg, 1)
h, w = self.bg.shape[:2]
self.frame_size = (w, h)
if size is not None:
self.frame_size = tuple(size);
if self.bg is not None:
self.bg = cv2.resize(self.bg, self.frame_size)
self.noise = float(noise)
def render(self, dst):
pass
def read(self, dst=None):
w, h = self.frame_size
if self.bg is None:
buf = np.zeros((h, w, 3), np.uint8)
else:
buf = self.bg.copy()
self.render(buf)
if self.noise > 0.0:
noise = np.zeros((h, w, 3), np.int8)
cv2.randn(noise, np.zeros(3), np.ones(3)*255*self.noise)
buf = cv2.add(buf, noise, dtype=cv2.CV_8UC3)
return True, buf
def isOpened(self):
return True
class Chess(VideoSynthBase):
def __init__(self, **kw):
super(Chess, self).__init__(**kw)
w, h = self.frame_size
self.grid_size = sx, sy = 10, 7
white_quads = []
black_quads = []
for i, j in np.ndindex(sy, sx):
q = [[j, i, 0], [j+1, i, 0], [j+1, i+1, 0], [j, i+1, 0]]
[white_quads, black_quads][(i + j) % 2].append(q)
self.white_quads = np.float32(white_quads)
self.black_quads = np.float32(black_quads)
fx = 0.9
self.K = np.float64([[fx*w, 0, 0.5*(w-1)],
[0, fx*w, 0.5*(h-1)],
[0.0,0.0, 1.0]])
self.dist_coef = np.float64([-0.2, 0.1, 0, 0])
self.t = 0
def draw_quads(self, img, quads, color = (0, 255, 0)):
img_quads = cv2.projectPoints(quads.reshape(-1, 3), self.rvec, self.tvec, self.K, self.dist_coef) [0]
img_quads.shape = quads.shape[:2] + (2,)
for q in img_quads:
cv2.fillConvexPoly(img, np.int32(q*4), color, cv2.LINE_AA, shift=2)
def render(self, dst):
t = self.t
self.t += 1.0/30.0
sx, sy = self.grid_size
center = np.array([0.5*sx, 0.5*sy, 0.0])
phi = pi/3 + sin(t*3)*pi/8
c, s = cos(phi), sin(phi)
ofs = np.array([sin(1.2*t), cos(1.8*t), 0]) * sx * 0.2
eye_pos = center + np.array([cos(t)*c, sin(t)*c, s]) * 15.0 + ofs
target_pos = center + ofs
R, self.tvec = common.lookat(eye_pos, target_pos)
self.rvec = common.mtx2rvec(R)
self.draw_quads(dst, self.white_quads, (245, 245, 245))
self.draw_quads(dst, self.black_quads, (10, 10, 10))
class ImageSequence(VideoSynthBase):
def __init__(self, **kw):
super(ImageSequence, self).__init__(size=(kw["imgs"].shape[1], kw["imgs"].shape[0]), **kw)
w, h = self.frame_size
self.imgs = kw["imgs"];
self.index = 0;
self.num_imgs = self.imgs.shape[3]
def render(self, dst):
if self.index >= self.num_imgs:
self.index = 0;
dst[:] = self.imgs[:,:,:,self.index];
self.index += 1;
classes = dict(chess=Chess, imgseq=ImageSequence)
presets = dict(
empty = 'synth:',
lena = 'synth:bg=../data/lena.jpg:noise=0.1',
chess = 'synth:class=chess:bg=../data/lena.jpg:noise=0.1:size=640x480'
)
def create_capture(source=0, size=None):
source = int(source);
cap = cv2.VideoCapture(source)
if size is not None:
w, h = size;
cap.set(cv2.CAP_PROP_FRAME_WIDTH, w)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, h)
return cap;
def create_synth_capture(classname, **kwargs):
Class = classes.get(classname, VideoSynthBase);
return Class(**kwargs)
if __name__ == '__main__':
import sys
import getopt
print __doc__