def od_sample_detection_bboxes():
return [
DetectionBbox.from_array(
[109.0, 190.0, 205.0, 408.0],
label_idx=3,
label_name="carton",
score=0.9985,
),
DetectionBbox.from_array(
[340.0, 326.0, 465.0, 549.0],
label_idx=2,
label_name="milk_bottle",
score=0.9979,
),
DetectionBbox.from_array(
[214.0, 181.0, 315.0, 460.0],
label_idx=1,
label_name="can",
score=0.9945,
),
DetectionBbox.from_array(
[215.0, 193.0, 316.0, 471.0],
label_idx=2,
label_name="milk_bottle",
score=0.1470,
),
DetectionBbox.from_array(
[109.0, 209.0, 209.0, 420.0],
label_idx=1,
label_name="can",
score=0.0903,
),
]
def det_bbox() -> "DetectionBbox":
return DetectionBbox(left=0,
top=10,
right=100,
bottom=1000,
label_idx=0,
score=0.5)
def od_cup_det_bboxes(tmp_session, od_cup_path) -> List[DetectionBbox]:
return [
DetectionBbox(
left=61,
top=59,
right=273,
bottom=244,
label_name="cup",
label_idx=0,
im_path=od_cup_path,
score=0.99,
)
]
def test_detection_bbox_from_array(det_bbox):
bbox_from_array = DetectionBbox.from_array([0, 10, 100, 1000],
label_idx=0,
score=0)
validate_bbox(det_bbox)
assert type(bbox_from_array) == DetectionBbox