def _filterOtherRectangles(self):
filtered_rectangle_centres = []
contains_map = {}
# The ratio between the hole length + the horizontal space and the hole length
model_hole_space_ratio = (self._model.hole_length + self._model.hole_h_space) / self._model.hole_length
model_length_width_ratio = (self._model.hole_length / self._model.hole_width)
for centre in self._filtered_rectangle_centres:
if not contains_map.get(centre, False):
box = self._boxes[self._centres_to_indices[centre]]
((box_vector, box_length), (_, box_width)) = geom.get_box_info(box)
max_distance = 0.5 * box_length
# If the rectangle is not too small and the length/width ratio is the ratio expected by the _model
if box_length > 30 and geom.are_ratio_similar(box_length / box_width, model_length_width_ratio, 1.75):
for other_centre in self._filtered_rectangle_centres:
if other_centre is not centre:
other_box = self._boxes[self._centres_to_indices[other_centre]]
((other_box_vector, other_box_length),(_, other_box_width)) = geom.get_box_info(other_box)
centres_vector = geom.vectorize(centre, other_centre)
# If the other rectangle is not too small and the length/width ratio
# is the ratio expected by the _model
# and : the two rectangle have the same length
# and : the distance between the _rectangles is the distance expected by the _model
# and : the vector of the long_side of the rectangle and the vector that binds the
# two centres is approximately parallel
if other_box_length > 30 \
and geom.are_ratio_similar(other_box_length / other_box_width,
model_length_width_ratio, 1.75) \
and geom.are_vectors_similar(box_vector, other_box_vector, max_distance,
signed=False) \
and geom.are_ratio_similar(np.linalg.norm(centres_vector) / box_length,
model_hole_space_ratio, 0.25) \
and geom.are_vectors_parallel(box_vector, centres_vector, 0.4):
if not contains_map.get(centre, False):
filtered_rectangle_centres.append(centre)
contains_map[centre] = True
if not contains_map.get(other_centre, False):
filtered_rectangle_centres.append(other_centre)
contains_map[other_centre] = True
return filtered_rectangle_centres
def _findHamcodesRectangles(self):
hamcodes_id_to_rect_centres = {}
for hamcode in self._hamcodes:
hamcode.contours = geom.sort_rectangle_corners(hamcode.contours)
ham_long_vector = geom.vectorize(hamcode.contours[0], hamcode.contours[1])
for rect_centre in self._filtered_rectangle_centres:
((long_vector, long_norm), (_, _)) = geom.get_box_info(self._boxes[self._centres_to_indices[rect_centre]])
if geom.are_vectors_parallel(long_vector, ham_long_vector, 0.25):
hamcode_vector = geom.vectorize(hamcode.contours[0], hamcode.contours[1])
centers_vector = geom.vectorize(hamcode.center, rect_centre)
model_ratio = (self._model.hamcode_v_margin + (self._model.hamcode_side / 2.)
- self._model.hole_v_margin - (self._model.hole_width / 2.)) / self._model.hamcode_side
image_ratio = np.linalg.norm(centers_vector) / np.linalg.norm(hamcode_vector)
if geom.are_ratio_similar(image_ratio, model_ratio, 1.3):
hamcodes_id_to_rect_centres[hamcode.id] = rect_centre
return hamcodes_id_to_rect_centres
