import numpy as np
import cv2

class VideoSynth(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:
            w, h = map(int, size.split('x'))
            self.frame_size = (w, h)
            self.bg = cv2.resize(bg, self.frame_size)

        self.noise = float(noise)

    def read(self, dst=None):
        w, h = self.frame_size

        buf = np.zeros((h, w, 3), np.uint8)
        if self.bg is not None:
            buf[:] = self.bg
        if self.noise > 0.0:
            noise = np.random.normal(scale = 255*self.noise, size=(h, w, 3))
            buf = cv2.add(buf, noise, dtype=cv2.CV_8UC3)
        return True, buf


def create_capture(source):
    '''
      source: <int> or '<int>' or '<filename>' or 'synth:<params>'
    '''
    try: source = int(source)
    except ValueError: pass
    else:
        return cv2.VideoCapture(source)
    source = str(source).strip()
    if source.startswith('synth'):
        ss = filter(None, source.split(':'))
        params = dict( s.split('=') for s in ss[1:] )
        return VideoSynth(**params)
    return cv2.VideoCapture(source)


if __name__ == '__main__':
    import sys
    try: fn = sys.argv[1]
    except: fn = 'synth:bg=../cpp/lena.jpg:noise=0.1'

    cap = create_capture(fn)
    while True:
        ret, img = cap.read()
        cv2.imshow('img', img)
        ch = cv2.waitKey(1)
        if ch == 27:
            break