Closed Hxinyue closed 11 months ago
Hi, you can put your .ply files under data/demo/synthetic_room_dataset, and then run
python generate_optim_scene.py configs/pointcloud/demo_syn_room.yaml
Thank you very much for your reply! Do I need to change my ply format data to the same style as "syntactic_room_dataset"?
You need to normalize the point clouds to [-1, 1].
@tangjiapeng 您好,请问我在自己的数据集(室内场景)上没有取得很好地效果,可以修改那些参数来增强效果。
You need to normalize the point clouds to [-1, 1]. Hello, I am trying to run "python generate_optim_scene.py configs/pointcloud/demo_syn_room.yaml" and an error message is reported as follows. May I know where the problem is with me?
非常希望和您讨论学习,我的问题请详见附件
------------------ 原始邮件 ------------------ 发件人: "tangjiapeng/SA-ConvONet" @.>; 发送时间: 2023年4月13日(星期四) 中午1:42 @.>; @.**@.>; 主题: Re: [tangjiapeng/SA-ConvONet] on my own data (Issue #11)
You need to normalize the point clouds to [-1, 1]. Hello, I am trying to run "python generate_optim_scene.py configs/pointcloud/demo_syn_room.yaml" and an error message is reported as follows. May I know where the problem is with me
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@tangjiapeng Hello, I understand that the loss nature of UCE adds a layer of RulU to the output. What is the relationship between this design and normal line? And whether the "we force the observed surface P to align with the 0.5 level set of occupancy field, and the signed occupancy values of non-surface points to be either 0 or 1"in the article will lose information?
The reason why we don't use common BCE is that we don't know the inside/outside information due to the lack of normals. Based on the pre-trained geometric priors, we can still optimize the occupancy fields, by enforcing the occupancy values of non-surface points as either 0 or 1. The prior initialization can provide some constraints that the points outside the surface would not be pulled to the inside during the optimization of UCE.
The reason why we don't use common BCE is that we don't know the inside/outside information due to the lack of normals. Based on the pre-trained geometric priors, we can still optimize the occupancy fields, by enforcing the occupancy values of non-surface points as either 0 or 1. The prior initialization can provide some constraints that the points outside the surface would not be pulled to the inside during the optimization of UCE.
Hello, may I ask if this zero setting operation will cause loss of output information?
您好,非常感谢您的工作,请问我只有一个.ply文件,我想用模型将.ply直接生成mesh并输出,应该怎么做
you can generate the npz file from ply file by "python scripts/dataset_matterport/make_cropscene_dataset2.py --in_folder data/demo/Matterport3D_processed --out_folder data/demo/Matterport3D_processed_normalize --do_norm".
您可以通过“python scripts/dataset_matterport/make_cropscene_dataset2.py--in_folder data/demo/Materport3D_processed--out_folder-data/demo/Materport 3D_pprocessed_normalize--do_norm”从ply文件生成npz文件。
Thank you very much for your reply. I have successfully run it according to your guidance!
Thank you very much for your work, there is no problem at present, it will be closed
Thanks for your work! I only have points in .ply format, how can I retrain or generate them directly?