UMass-Foundation-Model / 3D-LLM

Code for 3D-LLM: Injecting the 3D World into Large Language Models
MIT License
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Some questions #27

Open xbq1994 opened 1 year ago

xbq1994 commented 1 year ago

Hi, when I run the code

python -m torch.distributed.run --nproc_per_node=8 train.py --cfg-path lavis/projects/blip2/train/3dvqa_ft.yaml

there are some questions:

  1. I downloaded the weights locally from "https://huggingface.co/facebook/opt-2.7b" and replaced 'opt_model' in the code with the local weight file, but it shows that the weight and model sizes don't match.

  2. What directory should I place the downloaded dataset in?

  3. I found that the three annotations files in 3dvqa_ft.yaml do not exist. How can I obtain them?

train:
  storage: ./examples/all_refer_questions_train.json
test:
  storage: ./examples/all_refer_questions_val.json
val:
  storage: ./examples/all_refer_questions_val.json
evelinehong commented 1 year ago
  1. The codes in this repo use flant5. The weights should be automatically downloaded with the scripts.
  2. self.feature dir should be "features", and self.voxel dir should be "points" from the scene data
  3. replace the files with the json file in the google drive

We will push another version to fix these path mismatch

jiuyouyun9 commented 1 year ago
  1. The codes in this repo use flant5. The weights should be automatically downloaded with the scripts.
  2. self.feature dir should be "features", and self.voxel dir should be "points" from the scene data
  3. replace the files with the json file in the google drive

We will push another version to fix these path mismatch

For "3. replace the files with the json file in the google drive", json files in the google drive are 'data_part1_all_objaverse.json' and 'data_part2_scene.json'. In 3dvqa_ft.yaml, there are train, val, and test. Do I need to split the 'data_part1_all_objaverse.json' and 'data_part2_scene.json' into train/val/test sets in proportion of (8:1:1)?

xbq1994 commented 1 year ago
  1. The codes in this repo use flant5. The weights should be automatically downloaded with the scripts.
  2. self.feature dir should be "features", and self.voxel dir should be "points" from the scene data
  3. replace the files with the json file in the google drive

We will push another version to fix these path mismatch

Thanks! Do I need to split the 'data_part1_all_objaverse.json' and 'data_part2_scene.json' into train/val/test sets in proportion of (8:1:1)? I found you have uploaded files "voxelized_features_sam_nonzero_preprocess.zip" and "voxelized_voxels_sam_nonzero_preprocess.zip", what's that for?

cazhang commented 7 months ago
  1. The codes in this repo use flant5. The weights should be automatically downloaded with the scripts.
  2. self.feature dir should be "features", and self.voxel dir should be "points" from the scene data
  3. replace the files with the json file in the google drive

We will push another version to fix these path mismatch

Thanks! Do I need to split the 'data_part1_all_objaverse.json' and 'data_part2_scene.json' into train/val/test sets in proportion of (8:1:1)? I found you have uploaded files "voxelized_features_sam_nonzero_preprocess.zip" and "voxelized_voxels_sam_nonzero_preprocess.zip", what's that for?

Are you using the voxel point cloud as input? I thought the paper was using continuous representation. For voxel, how the discretization is done?