def apply(self, cur_image):
"""
apply the algorithm for running average in color
:param cur_image: numpy array; a color image (RGB)
:return new_objects_box: array consists of new object squares
:return new_fg: binary image consists of image (black and white)
"""
cur_image_gray = cv2.cvtColor(cur_image, cv2.COLOR_BGR2GRAY)
if self.prev_image is not None:
threshold_array = np.multiply(np.ones_like(cur_image_gray, 'uint8'), self.threshold)
diff = np.absolute(np.subtract(cur_image_gray, self.prev_frame))
fg_raw = np.multiply(
np.ones_like(cur_image_gray, 'uint8'),
np.where(
np.less(diff, threshold_array),
0,
255
)
)
raw_boxes, new_fg = PostProcessing.foreground_process(fg_raw)
new_objects_box = PostProcessing.bounding_box_mask(raw_boxes, new_fg)
else:
new_fg = np.zeros_like(cur_image_gray)
new_objects_box = []
self.prev_image = np.copy(cur_image_gray)
return new_objects_box, new_fg
def apply(self, cur_image, cur_objects):
"""
apply the algorithm for running average in color
:param cur_image: numpy array; a color image (RGB)
:param cur_objects: array consists of object squares
:return new_objects_box: array consists of new object squares
:return new_fg: binary image consists of image (black and white)
"""
cols, rows, depth = cur_image.shape
if self.bg is None:
self.bg = np.copy(cur_image)
if self.prev_frame is None:
self.prev_frame = np.copy(cur_image)
self.prev_prev_frame = np.copy(cur_image)
# get neighbor pixels
neighbor_pixels = map(
lambda x: cv2.warpAffine(cur_image, x, (cols, rows)),
self.WARP_MATRIX
)
# update background
new_bg = np.add(((1 - self.alpha) * self.bg), (self.alpha * cur_image))
# compare neighbor pixel with current background
# neighbor_pixels_diff = map(
# lambda x: np.absolute(np.subtract(new_bg, x)),
# neighbor_pixels
# )
# get difference at this pixel
diff = np.absolute(np.subtract(new_bg, cur_image))
fg_raw = cv2.inRange(cv2.cvtColor(diff.astype('uint8'), cv2.COLOR_BGR2GRAY), 25, 255)
raw_boxes, new_fg = PostProcessing.foreground_process(fg_raw)
new_objects_box = PostProcessing.bounding_box_mask(raw_boxes, new_fg)
cv2.imshow('Background', new_bg.astype('uint8'))
self.bg = np.copy(new_bg)
self.prev_prev_frame = np.copy(self.prev_frame)
self.prev_frame = np.copy(cur_image)
return new_objects_box, new_fg
