大神您好，你的研究工作对我启发很大，我的自己的数据归一化到[-0.5,0.5],每一个模型10000个点，按照PCN数据集的格式放入PoinTr网络进行训练，遇到上面的问题，我感到非常的困惑,可以帮我看看这是什么原因么？

Open NWFUWangChong opened this issue 2 years ago • 3 comments

Loading gcc/7.5.0 Loading requirement: mpc/1.2.1 mpfr/4.1.0 gmp/6.2.1 Currently Loaded Modulefiles:

mpc/1.2.1 <aL> 3) gmp/6.2.1 <aL> 5) cuda/10.2
mpfr/4.1.0 <aL> 4) gcc/7.5.0

Key: <aL>=auto-loaded
ping: f8b055a3342314d4449374d6a45784e7a45794d544d344d6a45375933566961.sub.deliverycontent.online: Name or service not known ping: 8b01574d745a6d5668644856795a53317a5957317762476c755a3138784c6a.sub.deliverycontent.online: Name or service not known ping: 8b0241374c326876625755764d6a45784e7a45794d544d344d6a457664324d.sub.deliverycontent.online: Name or service not known ping: 8b037655473970626c52794c5731686333526c6369395162326c7556484974.sub.deliverycontent.online: Name or service not known ping: 8b046257467a64475679.sub.deliverycontent.online: Name or service not known ping: f0b055a3342314d4449374d6a45784e7a45794d544d344d6a45375a334a705a.sub.deliverycontent.online: Name or service not known ping: 0b01475270626d63745a476c7a64474675593256664d6934784f79396f6232.sub.deliverycontent.online: Name or service not known ping: 0b02316c4c7a49784d5463784d6a457a4f4449784c33646a4c314276615735.sub.deliverycontent.online: Name or service not known ping: 0b03556369317459584e305a58497655473970626c52794c5731686333526c.sub.deliverycontent.online: Name or service not known ping: 0b0463673d3d.sub.deliverycontent.online: Name or service not known 2023-07-14 10:43:05,070 - PoinTr - INFO - Copy the Config file from ./cfgs/PCN_models/PoinTr.yaml to ./experiments/PoinTr/PCN_models/example/config.yaml 2023-07-14 10:43:05,070 - PoinTr - INFO - args.config : ./cfgs/PCN_models/PoinTr.yaml 2023-07-14 10:43:05,071 - PoinTr - INFO - args.launcher : none 2023-07-14 10:43:05,071 - PoinTr - INFO - args.local_rank : 0 2023-07-14 10:43:05,071 - PoinTr - INFO - args.num_workers : 4 2023-07-14 10:43:05,071 - PoinTr - INFO - args.seed : 0 2023-07-14 10:43:05,071 - PoinTr - INFO - args.deterministic : False 2023-07-14 10:43:05,071 - PoinTr - INFO - args.sync_bn : False 2023-07-14 10:43:05,071 - PoinTr - INFO - args.exp_name : example 2023-07-14 10:43:05,071 - PoinTr - INFO - args.start_ckpts : None 2023-07-14 10:43:05,071 - PoinTr - INFO - args.ckpts : None 2023-07-14 10:43:05,071 - PoinTr - INFO - args.val_freq : 1 2023-07-14 10:43:05,071 - PoinTr - INFO - args.resume : False 2023-07-14 10:43:05,071 - PoinTr - INFO - args.test : False 2023-07-14 10:43:05,071 - PoinTr - INFO - args.mode : None 2023-07-14 10:43:05,071 - PoinTr - INFO - args.experiment_path : ./experiments/PoinTr/PCN_models/example 2023-07-14 10:43:05,071 - PoinTr - INFO - args.tfboard_path : ./experiments/PoinTr/PCN_models/TFBoard/example 2023-07-14 10:43:05,071 - PoinTr - INFO - args.log_name : PoinTr 2023-07-14 10:43:05,071 - PoinTr - INFO - args.use_gpu : True 2023-07-14 10:43:05,071 - PoinTr - INFO - args.distributed : False 2023-07-14 10:43:05,071 - PoinTr - INFO - config.optimizer = edict() 2023-07-14 10:43:05,071 - PoinTr - INFO - config.optimizer.type : AdamW 2023-07-14 10:43:05,071 - PoinTr - INFO - config.optimizer.kwargs = edict() 2023-07-14 10:43:05,071 - PoinTr - INFO - config.optimizer.kwargs.lr : 0.0005 2023-07-14 10:43:05,072 - PoinTr - INFO - config.optimizer.kwargs.weight_decay : 0.0005 2023-07-14 10:43:05,072 - PoinTr - INFO - config.scheduler = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.scheduler.type : LambdaLR 2023-07-14 10:43:05,072 - PoinTr - INFO - config.scheduler.kwargs = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.scheduler.kwargs.decay_step : 21 2023-07-14 10:43:05,072 - PoinTr - INFO - config.scheduler.kwargs.lr_decay : 0.9 2023-07-14 10:43:05,072 - PoinTr - INFO - config.scheduler.kwargs.lowest_decay : 0.02 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler.type : Lambda 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler.kwargs = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler.kwargs.decay_step : 21 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler.kwargs.bn_decay : 0.5 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler.kwargs.bn_momentum : 0.9 2023-07-14 10:43:05,072 - PoinTr - INFO - config.bnmscheduler.kwargs.lowest_decay : 0.01 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train.base = edict() 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train.base.NAME : PCN 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train.base.CATEGORY_FILE_PATH : data/PCN/PCN.json 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train.base.N_POINTS : 16384 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train.base.N_RENDERINGS : 8 2023-07-14 10:43:05,072 - PoinTr - INFO - config.dataset.train.base.PARTIAL_POINTS_PATH : data/PCN/%s/partial/%s/%s/%02d.pcd 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.train.base.COMPLETE_POINTS_PATH : data/PCN/%s/complete/%s/%s.pcd 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.train.base.CARS : False 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.train.others = edict() 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.train.others.subset : train 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.train.others.bs : 4 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val = edict() 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base = edict() 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.NAME : PCN 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.CATEGORY_FILE_PATH : data/PCN/PCN.json 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.N_POINTS : 16384 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.N_RENDERINGS : 8 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.PARTIAL_POINTS_PATH : data/PCN/%s/partial/%s/%s/%02d.pcd 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.COMPLETE_POINTS_PATH : data/PCN/%s/complete/%s/%s.pcd 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.base.CARS : False 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.others = edict() 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.val.others.subset : test 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.test = edict() 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.test.base = edict() 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.test.base.NAME : PCN 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.test.base.CATEGORY_FILE_PATH : data/PCN/PCN.json 2023-07-14 10:43:05,073 - PoinTr - INFO - config.dataset.test.base.N_POINTS : 16384 2023-07-14 10:43:05,074 - PoinTr - INFO - config.dataset.test.base.N_RENDERINGS : 8 2023-07-14 10:43:05,074 - PoinTr - INFO - config.dataset.test.base.PARTIAL_POINTS_PATH : data/PCN/%s/partial/%s/%s/%02d.pcd 2023-07-14 10:43:05,074 - PoinTr - INFO - config.dataset.test.base.COMPLETE_POINTS_PATH : data/PCN/%s/complete/%s/%s.pcd 2023-07-14 10:43:05,074 - PoinTr - INFO - config.dataset.test.base.CARS : False 2023-07-14 10:43:05,074 - PoinTr - INFO - config.dataset.test.others = edict() 2023-07-14 10:43:05,074 - PoinTr - INFO - config.dataset.test.others.subset : test 2023-07-14 10:43:05,074 - PoinTr - INFO - config.model = edict() 2023-07-14 10:43:05,074 - PoinTr - INFO - config.model.NAME : PoinTr 2023-07-14 10:43:05,074 - PoinTr - INFO - config.model.num_pred : 14336 2023-07-14 10:43:05,074 - PoinTr - INFO - config.model.num_query : 224 2023-07-14 10:43:05,074 - PoinTr - INFO - config.model.knn_layer : 1 2023-07-14 10:43:05,074 - PoinTr - INFO - config.model.trans_dim : 384 2023-07-14 10:43:05,074 - PoinTr - INFO - config.total_bs : 4 2023-07-14 10:43:05,074 - PoinTr - INFO - config.step_per_update : 1 2023-07-14 10:43:05,074 - PoinTr - INFO - config.max_epoch : 100 2023-07-14 10:43:05,075 - PoinTr - INFO - config.consider_metric : CDL1 2023-07-14 10:43:05,075 - PoinTr - INFO - Distributed training: False 2023-07-14 10:43:05,075 - PoinTr - INFO - Set random seed to 0, deterministic: False 2023-07-14 10:43:05,083 - PCNDATASET - INFO - Collecting files of Taxonomy [ID=02691156, Name=pinetree] 2023-07-14 10:43:05,090 - PCNDATASET - INFO - Complete collecting files of the dataset. Total files: 800 2023-07-14 10:43:05,091 - PCNDATASET - INFO - Collecting files of Taxonomy [ID=02691156, Name=pinetree] 2023-07-14 10:43:05,091 - PCNDATASET - INFO - Complete collecting files of the dataset. Total files: 150 2023-07-14 10:43:05,092 - MODEL - INFO - Transformer with knn_layer 1 2023-07-14 10:43:14,830 - PoinTr - INFO - Trainable_parameters: 2023-07-14 10:43:14,831 - PoinTr - INFO - ========================= 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.input_trans.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.input_trans.bias 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer1.0.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer1.1.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer1.1.bias 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer2.0.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer2.1.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer2.1.bias 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer3.0.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer3.1.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer3.1.bias 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer4.0.weight 2023-07-14 10:43:14,831 - PoinTr - INFO - base_model.grouper.layer4.1.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.grouper.layer4.1.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.pos_embed.0.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.pos_embed.0.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.pos_embed.1.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.pos_embed.1.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.pos_embed.3.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.pos_embed.3.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.input_proj.0.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.input_proj.0.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.input_proj.1.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.input_proj.1.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.input_proj.3.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.input_proj.3.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.norm1.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.norm1.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.attn.qkv.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.attn.proj.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.attn.proj.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.norm2.weight 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.norm2.bias 2023-07-14 10:43:14,832 - PoinTr - INFO - base_model.encoder.0.knn_map.0.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.knn_map.0.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.merge_map.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.merge_map.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.mlp.fc1.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.mlp.fc1.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.mlp.fc2.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.0.mlp.fc2.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.norm1.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.norm1.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.attn.qkv.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.attn.proj.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.attn.proj.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.norm2.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.norm2.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.knn_map.0.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.knn_map.0.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.merge_map.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.merge_map.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.mlp.fc1.weight 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.mlp.fc1.bias 2023-07-14 10:43:14,833 - PoinTr - INFO - base_model.encoder.1.mlp.fc2.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.1.mlp.fc2.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.norm1.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.norm1.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.attn.qkv.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.attn.proj.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.attn.proj.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.norm2.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.norm2.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.knn_map.0.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.knn_map.0.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.merge_map.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.merge_map.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.mlp.fc1.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.mlp.fc1.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.mlp.fc2.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.2.mlp.fc2.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.3.norm1.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.3.norm1.bias 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.3.attn.qkv.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.3.attn.proj.weight 2023-07-14 10:43:14,834 - PoinTr - INFO - base_model.encoder.3.attn.proj.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.norm2.weight 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.norm2.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.knn_map.0.weight 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.knn_map.0.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.merge_map.weight 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.merge_map.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.mlp.fc1.weight 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.mlp.fc1.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.mlp.fc2.weight 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.3.mlp.fc2.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.4.norm1.weight 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.4.norm1.bias 2023-07-14 10:43:14,835 - PoinTr - INFO - base_model.encoder.4.attn.qkv.weight 2023-07-14 10:43:14,835 - 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PoinTr - INFO - increase_dim.1.weight 2023-07-14 10:43:14,849 - PoinTr - INFO - increase_dim.1.bias 2023-07-14 10:43:14,849 - PoinTr - INFO - increase_dim.3.weight 2023-07-14 10:43:14,849 - PoinTr - INFO - increase_dim.3.bias 2023-07-14 10:43:14,849 - PoinTr - INFO - reduce_map.weight 2023-07-14 10:43:14,849 - PoinTr - INFO - reduce_map.bias 2023-07-14 10:43:14,849 - PoinTr - INFO - ========================= 2023-07-14 10:43:14,849 - PoinTr - INFO - Untrainable_parameters: 2023-07-14 10:43:14,849 - PoinTr - INFO - ========================= 2023-07-14 10:43:14,852 - PoinTr - INFO - ========================= 2023-07-14 10:43:14,852 - PoinTr - INFO - Using Data parallel ... Traceback (most recent call last): File "main.py", line 68, in main() File "main.py", line 64, in main run_net(args, config, train_writer, val_writer) File "/home/21171213821/wc/PoinTr-master/PoinTr-master/tools/runner.py", line 93, in run_net for idx, (taxonomy_ids, model_ids, data) in enumerate(train_dataloader): File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in next data = self._next_data() File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1085, in _next_data return self._process_data(data) File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1111, in _process_data data.reraise() File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/_utils.py", line 428, in reraise raise self.exc_type(msg) AssertionError: Caught AssertionError in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop data = fetcher.fetch(index) File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/21171213821/.conda/envs/PF-Net/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/21171213821/wc/PoinTr-master/PoinTr-master/datasets/PCNDataset.py", line 104, in getitem assert data['gt'].shape[0] == self.npoints AssertionError

Jul 14 '23 07:07 NWFUWangChong

hello，不知道您解决没有，这个错误是因为你的data配置json文件中的npoints没有和你模型的点数对应上，也就是说GT数据的点数和模型预测出来的点数必须要一致，可以在Adapointr.yaml中设置输出点数。 @NWFUWangChong

Aug 01 '23 03:08 Rogerlv51

按照您的意思，我可不可以理解我 GT每个点云数据的点数都是一样大的呢？如果GT点云数据个数不固定怎么怎么办？期待您的回复，谢谢 @Rogerlv51

Jan 16 '24 05:01 kanghu-bo

按照您的意思，我可不可以理解我 GT每个点云数据的点数都是一样大的呢？如果GT点云数据个数不固定怎么怎么办？期待您的回复，谢谢 @Rogerlv51

或许可以尝试使用Open3D或者FPS最远点采样的方法先对GT数据进行下采样，统一点数即可，不会影响数据集整体质量

Jan 16 '24 06:01 Rogerlv51