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OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

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openpcdet使用pillarnet. yaml训练后eval报错finalpred_dict=batch_dict['finalboxdicts']KeyError:'finalbox_dicts'我也有这个问题,请问有解决办法吗

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``` Traceback (most recent call last): | 0/1630 [00:00

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ImportError: cannot import name 'iou3d_nms_cuda' from 'pcdet.ops.iou3d_nms' (unknown location)

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I've successfully trained and evaluated several models using "kitti_infos_train.pkl" and "kitti_infos_val.pkl" without any problems. However, when I attempted to test using "kitti_infos_test.pkl," all the returned recall values are showing as...

Hi!@sshaoshuai Thank you for your wonderful work. Do you have any plans to do model prune, weights quantization,distilling knowledge or use tensorRT acceleration tool to accelerate OpenPCDet?

Hello author, can you provide a 20% segmentation strategy for the waymo data set. I hope you can reply to me, I will be very grateful

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How to get the results of distances for the Kitti dataset? Thank you!

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**Bug** The .pth file does not contain the key "model_state" key, meaning it cannot be loaded by pcdet/models/detectors/detector3d_template.py In [Line 368](https://github.com/open-mmlab/OpenPCDet/blob/8cacccec11db6f59bf6934600c9a175dae254806/pcdet/models/detectors/detector3d_template.py#L368) [Line 371](https://github.com/open-mmlab/OpenPCDet/blob/8cacccec11db6f59bf6934600c9a175dae254806/pcdet/models/detectors/detector3d_template.py#L371) [Line 396](https://github.com/open-mmlab/OpenPCDet/blob/8cacccec11db6f59bf6934600c9a175dae254806/pcdet/models/detectors/detector3d_template.py#L396) Modifying the file by wrapping...

Hi, I'm new to 3D object detection and I discovered OpenPCDet a few days ago, it really caught my attention. I tried to use it with other LiDAR point clouds...

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In data_processor.py ``` def mask_points_and_boxes_outside_range(self, data_dict=None, config=None): if data_dict is None: return partial(self.mask_points_and_boxes_outside_range, config=config) if data_dict.get('points', None) is not None: mask = common_utils.mask_points_by_range(data_dict['points'], self.point_cloud_range) data_dict['points'] = data_dict['points'][mask] if data_dict.get('gt_boxes', None)...