Re3Sim
[ICRA 2026] Re3Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation
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최종 버전 다운로드 (.zip)- 1_gpu.yaml
- 2_gpu.yaml
- 4_gpu.yaml
- 8_gpu.yaml
- act_new_abs.yaml
- act_new_rela.yaml
- act_old.yaml
- act_old_jpg.yaml
- act_old_jpg_continuous.yaml
- act_old_lmdb.yaml
- act_old_lmdb_expand_last_step.yaml
- act_old_mp4.yaml
- act_realrobot_data.yaml
- act_realrobot_data_lmdb.yaml
- base.yaml
- sim_random_position_1010_1_large.yaml
- sim_random_position_105_1_large.yaml
- sim_random_position_105_1_mid.yaml
- config.yaml
- hydra.launcher
- pick_one_into_basket.yaml
- __init__.py
- datasets_utils.py
- episodic_dataset.py
- episodic_dataset_jpg.py
- episodic_dataset_jpg_continue.py
- episodic_dataset_lmdb.py
- episodic_dataset_lmdb_expand_last_step.py
- jpg_manager.py
- mix_dataset.py
- real_robot_dataset.py
- real_world_episodic_dataset.py
- real_world_episodic_dataset_lmdb.py
- __init__.py
- backbone.py
- detr_vae.py
- latent_model.py
- position_encoding.py
- transformer.py
- __init__.py
- box_ops.py
- misc.py
- plot_utils.py
- LICENSE
- main.py
- README.md
- setup.py
- __init__.py
- util.py
- __init__.py
- real_task.py
- __init__.py
- distributed.py
- lr_scheduler.py
- misc.py
- training_stats.py
- .gitignore
- __init__.py
- conda_env.yaml
- configclass.py
- constants.example.py
- constants.py
- dynamixel_client.py
- ee_sim_env.py
- imitate_episodes.py
- imitate_episodes_cosine.py
- LICENSE
- policy.py
- postprocess_episodes.py
- process_data.py
- record_sim_episodes.py
- replay_episodes.py
- requirements.txt
- scripted_policy.py
- setup.py
- sim_env.py
- train_actuator_network.py
- train_latent_model.py
- truncate_data.py
- utils.py
- vinn_cache_feature.py
- vinn_eval.py
- vinn_select_k.py
- visualize_episodes.py
- __init__.py
- Materials.usd
- panda_hand.usd
- panda_leftfinger.usd
- panda_link0.usd
- panda_link1.usd
- panda_link2.usd
- panda_link3.usd
- panda_link4.usd
- panda_link5.usd
- panda_link6.usd
- panda_link7.usd
- panda_rightfinger.usd
- franka.usd
- collect_data_render_1_1_eggplant_low_res_continuous_four_item.yaml
- .collect_data_render_1_16_one_item.yaml.swp
- collect_data_render_1_16_one_item.yaml
- eval_one_item_12_19.yaml
- __init__.py
- multi_item_controller.py
- pick_and_place_mplib.py
- __init__.py
- config.py
- env.py
- runner.py
- scene.py
- __init__.py
- __init__.py
- network_gui.py
- lpips.py
- networks.py
- utils.py
- __init__.py
- __init__.py
- cameras.py
- colmap_loader.py
- dataset_readers.py
- gaussian_model.py
- .gitignore
- convert.py
- index.html
- LICENSE
- main.js
- output.splat
- README.md
- auxiliary.h
- backward.cu
- backward.h
- config.h
- forward.cu
- forward.h
- rasterizer.h
- rasterizer_impl.cu
- rasterizer_impl.h
- __init__.py
- cmake_uninstall.cmake.in
- all_0.html
- all_0.js
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- transformations.py
- .gitignore
- README.md
# 설치 가이드
git clone https://github.com/InternRobotics/Re3Sim
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd Re3Sim
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. 공식 설치 스크립트
쉬움 추천- Python 3 pip 명령어를 쓰려면 Python이 필요합니다.
pip install src/gaussian_splatting/submodules/diff-gaussian-rasterization/
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
pip install src/gaussian_splatting/submodules/simple-knn/
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
3. Docker
쉬움- Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
- Docker Desktop 컨테이너를 빌드하고 실행하려면 필요합니다. 설치 후 실행해서 백그라운드에 켜두세요.
docker build -t re3sim:1.0.0 .
Dockerfile을 기반으로 실행 가능한 이미지를 빌드합니다.
docker run --name re3sim --entrypoint bash -itd --runtime=nvidia --gpus='"device=0"' -e "ACCEPT_EULA=Y" --rm --network=bridge --shm-size="32g" -e "PRIVACY_CONSENT=Y" \
빌드된 이미지를 실제 컨테이너로 실행합니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
4. CMake
보통cd re3sim/gaussian_splatting/submodules/diff-gaussian-rasterization
이 프로젝트의 관련 파일이 하위 폴더 안에 있어서, 먼저 그 폴더로 이동합니다.
mkdir build && cd build
빌드 결과물을 담을 폴더를 만들고 그 안으로 이동합니다.
cmake ..
소스코드를 분석해 빌드 설정 파일을 생성합니다 (build 폴더 안에서 실행해야 함).
make
생성된 빌드 설정을 바탕으로 실제 컴파일을 진행해 실행 파일을 만듭니다.
5. Python
쉬움pip install src/gaussian_splatting/submodules/diff-gaussian-rasterization/
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
pip install src/gaussian_splatting/submodules/simple-knn/
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
pip install -e .
requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
