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Open Source Computer Vision Library
https://opencv.org/
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61 lines
1.7 KiB
61 lines
1.7 KiB
import numpy as np |
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import cv2 |
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class VideoSynth(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(bg, self.frame_size) |
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self.noise = float(noise) |
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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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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 create_capture(source): |
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''' |
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source: <int> or '<int>' or '<filename>' or 'synth:<params>' |
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''' |
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try: source = int(source) |
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except ValueError: pass |
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else: |
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return cv2.VideoCapture(source) |
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source = str(source).strip() |
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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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return cv2.VideoCapture(source) |
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if __name__ == '__main__': |
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import sys |
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try: fn = sys.argv[1] |
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except: fn = 'synth:bg=../cpp/lena.jpg:noise=0.1' |
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cap = create_capture(fn) |
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while True: |
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ret, img = cap.read() |
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cv2.imshow('img', img) |
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ch = cv2.waitKey(1) |
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if ch == 27: |
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break
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