def test_inference_mono_3d_detector():
# FCOS3D only has GPU implementations
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
img = 'tests/data/nuscenes/samples/CAM_BACK_LEFT/' \
'n015-2018-07-18-11-07-57+0800__CAM_BACK_LEFT__1531883530447423.jpg'
ann_file = 'tests/data/nuscenes/nus_infos_mono3d.coco.json'
detector_cfg = 'configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_' \
'2x8_1x_nus-mono3d.py'
detector = init_model(detector_cfg, device='cuda:0')
results = inference_mono_3d_detector(detector, img, ann_file)
bboxes_3d = results[0][0]['img_bbox']['boxes_3d']
scores_3d = results[0][0]['img_bbox']['scores_3d']
labels_3d = results[0][0]['img_bbox']['labels_3d']
assert bboxes_3d.tensor.shape[0] >= 0
assert bboxes_3d.tensor.shape[1] == 9
assert scores_3d.shape[0] >= 0
assert labels_3d.shape[0] >= 0
def main():
parser = ArgumentParser()
parser.add_argument('image', help='image file')
parser.add_argument('ann', help='ann file')
parser.add_argument('config', help='Config file')
parser.add_argument('checkpoint', help='Checkpoint file')
parser.add_argument('--device',
default='cuda:0',
help='Device used for inference')
parser.add_argument('--score-thr',
type=float,
default=0.15,
help='bbox score threshold')
parser.add_argument('--out-dir',
type=str,
default='demo',
help='dir to save results')
parser.add_argument('--show',
action='store_true',
help='show online visualization results')
parser.add_argument('--snapshot',
action='store_true',
help='whether to save online visualization results')
args = parser.parse_args()
# build the model from a config file and a checkpoint file
model = init_model(args.config, args.checkpoint, device=args.device)
# test a single image
result, data = inference_mono_3d_detector(model, args.image, args.ann)
# show the results
show_result_meshlab(data,
result,
args.out_dir,
args.score_thr,
show=args.show,
snapshot=args.snapshot,
task='mono-det')