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conda create -n dreamvla python=3.10
conda activate dreamvlagit clone https://github.com/Zhangwenyao1/DreamVLAUse .reshape(...) instead., just change it../co-tracker/checkpoints1mv ./data_process/cotrack_extractor.py ./co-tracker/
2cd co-tracker
3python cotrack_extractor.pycp dist_utils.py ./segment-anything/
mv ./data_info/ep_start_end_ids.npy <your_data_path>
mv ./data_process/sam_extractor.py ./segment-anything/
cd segment-anything
python sam_extractor.pycp dist_utils.py ./dinov2/
mv ./data_process/dino_extractor.py ./dinov2/
cd dinov2
python dino_extractor.pypython dino_extractor.py is must to run.python ./data_process/merge_sam_dino.py # merge sam and dino feature into new dataset
python ./data_process/merge_track.py # merge optical flow into new dataset./scripts/CALVIN_ABC_D/DreamVLA/. Moreover, if you use less than 8 gpus, plase change the node_num in *.sh.bash ./scripts/CALVIN_ABC_D/DreamVLA/pretrain.shbash ./scripts/CALVIN_ABC_D/DreamVLA/finetune.shcheckpoints/. Then put it into the file.bash ./scripts/CALVIN_ABC_D/DreamVLA/eval.sharticle{dreamvla25,
author = {Wenyao Zhang and
Hongsi Liu and
Zekun Qi and
Yunan Wang and
Xinqiang Yu and
Jiazhao Zhang and
Runpei Dong and
Jiawei He and
He Wang and
Zhizheng Zhang and
Li Yi and
Wenjun Zeng and
Xin Jin},
title = {DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge},
journal = {CoRR},
volume = {abs/2507.04447},
year = {2025},
url = {https://doi.org/10.48550/arXiv.2507.04447},
doi = {10.48550/ARXIV.2507.04447},
eprinttype = {arXiv},
eprint = {2507.04447}
}