def test_clip_to_window(self):
boxlist = np_box_list.BoxList(
np.array([[0.25, 0.25, 0.75, 0.75], [0.0, 0.0, 0.5, 0.75],
[-0.2, -0.3, 0.7, 1.5]],
dtype=np.float32))
boxlist_clipped = np_box_list_ops.clip_to_window(
boxlist, [0.0, 0.0, 1.0, 1.0])
expected_boxlist_clipped = np_box_list.BoxList(
np.array([[0.25, 0.25, 0.75, 0.75], [0.0, 0.0, 0.5, 0.75],
[0.0, 0.0, 0.7, 1.0]],
dtype=np.float32))
self.assertAllClose(expected_boxlist_clipped.get(),
boxlist_clipped.get())
def test_clip_to_window(self):
boxlist = np_box_list.BoxList(
np.array(
[[0.25, 0.25, 0.75, 0.75], [0.0, 0.0, 0.5, 0.75],
[-0.2, -0.3, 0.7, 1.5]],
dtype=np.float32))
boxlist_clipped = np_box_list_ops.clip_to_window(boxlist,
[0.0, 0.0, 1.0, 1.0])
expected_boxlist_clipped = np_box_list.BoxList(
np.array(
[[0.25, 0.25, 0.75, 0.75], [0.0, 0.0, 0.5, 0.75],
[0.0, 0.0, 0.7, 1.0]],
dtype=np.float32))
self.assertAllClose(expected_boxlist_clipped.get(), boxlist_clipped.get())
def get_rect_area_total(obj_list, window):
if not obj_list:
return 0.0
area_total = 0
box_list = get_box_list(obj_list)
box_list_clip = np_box_list_ops.clip_to_window(box_list, window)
box_list_norm = np_box_list_ops.change_coordinate_frame(
box_list_clip, window)
n_boxes = box_list_norm.num_boxes()
index = [str(i) for i in range(n_boxes)]
box_list_norm.add_field('index', np.asarray(index))
box_list_norm_org = copy.deepcopy(box_list_norm)
sign = 1
while box_list_norm:
area = np.sum(np_box_list_ops.area(box_list_norm))
area_total += area * sign
sign *= -1
box_list_norm = np_box_list_ops.intersection_boxes(
box_list_norm_org, box_list_norm)
return area_total
def get_overlapping(labels, window, ioa_thresh=0.000001, clip=False):
"""Return subset of labels that overlap with window.
Args:
labels: ObjectDetectionLabels
window: Box
ioa_thresh: the minimum IOA for a box to be considered as
overlapping
clip: if True, clip label boxes to the window
"""
# Lazily load TF Object Detection
from object_detection.utils.np_box_list import BoxList
from object_detection.utils.np_box_list_ops import (
prune_non_overlapping_boxes, clip_to_window)
window_npbox = window.npbox_format()
window_boxlist = BoxList(np.expand_dims(window_npbox, axis=0))
boxlist = prune_non_overlapping_boxes(labels.boxlist,
window_boxlist,
minoverlap=ioa_thresh)
if clip:
boxlist = clip_to_window(boxlist, window_npbox)
return ObjectDetectionLabels.from_boxlist(boxlist)