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Agent-Grounder: Zero-Shot 3D Visual Pointcloud Grounding

Table of Content

0. Environment Setup

We recommend using our docker image for environment setup

make build
make up
make into
make stop

Install our package inside docker:

pip install -e .

1. Download Model Weights

cd AgentGrounder/weights
git clone https://huggingface.co/IDEA-Research/Rex-Omni         # Rex-Omni
git clone https://huggingface.co/IDEA-Research/Rex-Omni-AWQ     # Quantized Rex-Omni
git clone https://huggingface.co/facebook/sam3                  # SAM3

2. Download Datasets

2.1. ScanRefer

Download ScanRefer dataset from official repo, and place it in the following directory:

data/ScanRefer/ScanRefer_filtered_val.json

2.2. Nr3D

Download the Nr3D dataset from the official repo, and place it in the following directory:

data/Nr3D/Nr3D.json

2.3. Vil3dref Preprocessed Data

Download the preprocessed Vil3dref data from vil3dref.

The expected structure should look like this:

referit3d/
.
├── annotations
|   ├── meta_data
|   │   ├── cat2glove42b.json
|   │   ├── scannetv2-labels.combined.tsv
|   │   └── scannetv2_raw_categories.json
│   └── ...
├── ...
└── scan_data
    ├── ...
    ├── instance_id_to_name
    └── pcd_with_global_alignment

3. Data Processing

Download mask3d pred first.

  • ScanRefer
python -m prepare_data.object_lookup_table_scanrefer
  • Nr3D
python -m prepare_data.process_feat_3d

python -m prepare_data.object_lookup_table_nr3d

4. Inference

4.1. Deploying VLM Service

We use ollama to deploy the VLM. Please install ollama server on your server.

4.2. Generating Anchors & Targets

  • ScanRefer
python -m parse_query.generate_query_data_scanrefer
  • Nr3D
python -m parse_query.generate_query_data_nr3d

4.3. Predictions

python -m inference.inference --config_path <nr3d_or_scanrefer_config_path>

4.4. Evaluations

  • ScanRefer
python -m eval.eval_nr3d
  • Nr3D
python -m eval.eval_scanrefer

5. License

This work is released under the CC BY 4.0 license.

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