def od_sample_detection(od_sample_raw_preds, od_detection_mask_dataset):
labels = ["one", "two", "three", "four"]
detections = _extract_od_results(
_apply_threshold(od_sample_raw_preds[0], threshold=0.001),
labels,
od_detection_mask_dataset.im_paths[0],
)
detections["idx"] = 0
del detections["keypoints"]
return detections
def test__extract_od_results(od_sample_raw_preds, od_data_path_labels):
""" test that `_extract_od_results` can convert raw preds. """
pred = {
k: v.detach().cpu().numpy()
for k, v in od_sample_raw_preds[0].items()
}
out = _extract_od_results(pred, labels=od_data_path_labels, im_path=None)
bboxes = out["det_bboxes"]
assert type(bboxes[0]) == DetectionBbox
assert len(bboxes) == 5
assert out["masks"].shape == (5, 666, 499)
assert out["keypoints"].shape == (5, 13, 3)