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202 lines
5.8 KiB
202 lines
5.8 KiB
#!/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 convinience 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=../data/lena.jpg:noise=0.1 |
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synth:class=chess:bg=../data/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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from numpy import pi, sin, cos |
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import cv2 |
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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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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 = cv2.imread(bg, 1) |
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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 = cv2.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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cv2.randn(noise, np.zeros(3), np.ones(3)*255*self.noise) |
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buf = cv2.add(buf, noise, dtype=cv2.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 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 = 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.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) |
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presets = dict( |
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empty = 'synth:', |
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lena = 'synth:bg=../data/lena.jpg:noise=0.1', |
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chess = 'synth:class=chess:bg=../data/lena.jpg:noise=0.1: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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chunks = source.split(':') |
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# handle drive letter ('c:', ...) |
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if len(chunks) > 1 and len(chunks[0]) == 1 and chunks[0].isalpha(): |
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chunks[1] = chunks[0] + ':' + chunks[1] |
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del chunks[0] |
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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 = cv2.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(cv2.CAP_PROP_FRAME_WIDTH, w) |
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cap.set(cv2.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 = 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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cv2.imshow('capture %d' % i, img) |
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ch = 0xFF & cv2.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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cv2.imwrite(fn, img) |
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print(fn, 'saved') |
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shot_idx += 1 |
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cv2.destroyAllWindows()
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