dst_pts = dst_pts.reshape((-1, 1, 2))
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
result = combine.combine_images(frame, result, M)
if args.display and not args.quiet:
scripts.display('result', result)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
else:
logger.warning('too few correspondence points')
else:
result = frame
result_gry = cv2.cvtColor(result, cv2.COLOR_RGB2GRAY)
else:
break
logger.debug('{0} is completed'.format(path))
cam.release()
cv2.destroyAllWindows()
if args.save:
scripts.save_image(path, result)
except Exception as error:
logger.warning('Failed to process {0}'.format(path))
logger.debug('Error msg: {0}'.format(error))
return result
if __name__ == '__main__':
args = scripts.get_args()
logger = scripts.get_logger(quiet=args.quiet, debug=args.debug)
result = main(args)
scripts.display('final result', result)
cv2.waitKey(0)
def blur_detector(img_col, thresh=10, mask=False):
assert isinstance(img_col, numpy.ndarray), 'img_col must be a numpy array'
assert img_col.ndim == 3, 'img_col must be a color image ({0} dimensions currently)'.format(
img_col.ndim)
args = scripts.gen_args()
args.thresh = thresh
if mask:
return FocusMask.blur_mask(img)
else:
return evaluate(img_col=img_col, args=args)
if __name__ == '__main__':
args = scripts.get_args()
logger = scripts.get_logger(quite=args.quite, debug=args.debug)
x_okay, y_okay = [], []
x_blur, y_blur = [], []
for path in args.image_paths:
for img_path in scripts.find_images(path):
logger.debug('evaluating {0}'.format(img_path))
img = cv2.imread(img_path)
if isinstance(img, numpy.ndarray):
if args.testing:
scripts.display('dialog (blurry: Y?)', img)
blurry = False
if cv2.waitKey(0) in map(lambda i: ord(i), ['Y', 'y']):
blurry = True
x_axis = [1, 3, 5, 7, 9]
for x in x_axis:
img_mod = cv2.GaussianBlur(img, (x, x), 0)
def blur_detector(img_col, thresh=10, mask=False):
assert isinstance(img_col, numpy.ndarray), 'img_col must be a numpy array'
assert img_col.ndim == 3, 'img_col must be a color image ({0} dimensions currently)'.format(img_col.ndim)
args = scripts.gen_args()
args.thresh = thresh
if mask:
return FocusMask.blur_mask(img)
else:
return evaluate(img_col=img_col, args=args)
if __name__ == '__main__':
args = scripts.get_args()
logger = scripts.get_logger(quite=args.quite, debug=args.debug)
x_okay, y_okay = [], []
x_blur, y_blur = [], []
for path in args.image_paths:
for img_path in scripts.find_images(path):
logger.debug('evaluating {0}'.format(img_path))
img = cv2.imread(img_path)
if isinstance(img, numpy.ndarray):
if args.testing:
scripts.display('dialog (blurry: Y?)', img)
blurry = False
if cv2.waitKey(0) in map(lambda i: ord(i), ['Y', 'y']):
blurry = True
x_axis = [1, 3, 5, 7, 9]
for x in x_axis:
img_mod = cv2.GaussianBlur(img, (x, x), 0)
