UMass-Foundation-Model / 3D-LLM

Code for 3D-LLM: Injecting the 3D World into Large Language Models

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Some questions about the code

xbq1994 opened this issue · comments

Hi, I have some questions:

  1. As there are no descriptions about "task_type" in the annotations, how to split the 'data_part1_all_objaverse.json' and 'data_part2_scene.json' into train/val/test sets in proportion of (8:1:1)?
  2. I found you have uploaded files "voxelized_features_sam_nonzero_preprocess.zip" and "voxelized_voxels_sam_nonzero_preprocess.zip", what's that for?
  3. During the evaluation, the code needs the "coco_fmt_qust_file" annotations for computing accuracy. However there are no descriptions about "coco_fmt_qust_file" in the annotations, so how to calculate the test accuracy?
            if hasattr(dataset[split], "coco_fmt_qust_file") and dataset[split].coco_fmt_qust_file is not None:
                self.ques_files[split] = dataset[split].coco_fmt_qust_file
                self.anno_files[split] = dataset[split].coco_fmt_anno_file
  1. evaluation set: https://drive.google.com/drive/folders/1tdvEW5iB-ZEPo1tCqEAqKKhgHiDd4Dx0?usp=drive_link
  2. scannet features and point clouds
  3. we do not need that in the evaluation. We have uploaded our own evaluation scripts