logger.debug('processing {0} frame'.format(frame_id))
len_frame = len(frames)
frames = [frame] + frames[:min(2, len(frames))]
if len(frames) == 3:
diff = frame_diff(frames[0], frames[1], frame)
val = numpy.mean(diff)
data = numpy.hstack(([val], data[:min(args.n_samples, data.shape[0])]))
data_avg = numpy.mean(data)
data_std = numpy.std(data)
data_var = numpy.abs(val-data_avg)/data_std
logger.debug('data_avg: {0}, data_std: {1}, data_var: {2}, value: {3}'.format(data_avg, data_std, data_var, val))
critical = (data_var > args.offset) and (frame_id > args.n_min)
if args.display:
msg0 = "avg: {0}, std: {0}, var: {1}".format(data_avg, data_std, data_var)
msg1 = "critical image: {0}".format(critical)
cv2.imshow('input frame', Scripts.display_message(frame, msg0, msg1))
cv2.imshow('frame_diff', Scripts.display_message(diff, msg0, msg1))
if critical and not triggered:
triggered = True
logger.info('Significant Motion Detected on Frame {0}!'.format(frame_id))
if args.dump_images:
img_path = '{0}_inputFrame.png'.format(frame_id)
dif_path = '{0}_diffFrame.png'.format(frame_id)
if args.dump_path:
img_path = os.path.join(args.dump_path, img_path)
dif_path = os.path.join(args.dump_path, dif_path)
logger.debug('saving inputFrame to {0}'.format(img_path))
logger.debug('saving diffFrame to {0}'.format(dif_path))
cv2.imwrite(img_path, frame)
assert os.path.exists(img_path), 'inputFrame did not save correctly'
cv2.imwrite(dif_path, diff)
