copa
Official implementation of CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models
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Download Latest Version (.zip)- banner.gif
- banner.mp4
- hardware_setup.jpg
- method-overview.gif
- __init__.py
- constraint.py
- elements.py
- parser.py
- solver.py
- transform.py
- action_parser.py
- draw_arrow.py
- main_infer_trans.py
- bullet_dataset.py
- command_generate_tolerance_label.sh
- generate_tolerance_label.py
- graspnet_dataset.py
- color.png
- demo_result.png
- depth.png
- meta.mat
- workspace_mask.png
- teaser.png
- knn_cpu.cpp
- vision.h
- knn.cu
- vision.h
- knn.h
- vision.cpp
- knn_modules.py
- setup.py
- backbone.py
- graspnet.py
- loss.py
- modules.py
- ball_query.h
- cuda_utils.h
- cylinder_query.h
- group_points.h
- interpolate.h
- sampling.h
- utils.h
- ball_query.cpp
- ball_query_gpu.cu
- bindings.cpp
- cylinder_query.cpp
- cylinder_query_gpu.cu
- group_points.cpp
- group_points_gpu.cu
- interpolate.cpp
- interpolate_gpu.cu
- sampling.cpp
- sampling_gpu.cu
- pointnet2_modules.py
- pointnet2_utils.py
- pytorch_utils.py
- setup.py
- collision_detector.py
- data_utils.py
- grasp_projection.py
- label_generation.py
- loss_utils.py
- motion_planner.py
- ros_adapter.py
- .gitignore
- command_demo.sh
- command_test.sh
- command_train.sh
- demo.py
- demo_filter_grasp.py
- main_to_ros.py
- requirements.txt
- test.py
- train.py
- visualize.py
- behavior.py
- functional_grasp.py
- generate_point_cloud.launch
- generate_point_cloud.py
- visualize.py
- CMakeLists.txt
- get_point_cloud.launch
- get_point_cloud.py
- CMakeLists.txt
- point_cloud_snapshot.py
- robot_homing.launch
- robot_homing.py
- CMakeLists.txt
- robot_states_monitor.launch
- robot_states_monitor.py
- CMakeLists.txt
- trajectory_recorder.launch
- trajectory_recorder.py
- CMakeLists.txt
- trajectory_recorder.py
- CMakeLists.txt
- package.xml
- README.md
- method2_xyz.png
- som_bench_bottom.jpg
- som_bench_upper.jpg
- som_gpt4v_demo.mp4
- som_logo.png
- som_toolbox_interface.jpg
- teaser.png
- README.md
- seem_focall_unicl_lang_v1.yaml
- semantic_sam_only_sa-1b_swinL.yaml
- gpt-4v-som-example.jpg
- ironing_man.jpg
- ironing_man_som.png
- som_logo.png
- prompt1.png
- prompt1.txt
- prompt2.png
- prompt2.txt
- prompt3.png
- prompt3.txt
- prompt4.txt
- __init__.py
- ms_deform_attn_func.py
- __init__.py
- ms_deform_attn.py
- ms_deform_attn_cpu.cpp
- ms_deform_attn_cpu.h
- ms_deform_attn_cuda.cu
- ms_deform_attn_cuda.h
- ms_deform_im2col_cuda.cuh
- ms_deform_attn.h
- vision.cpp
- make.sh
- setup.py
- test.py
- prompt1.png
- prompt1.txt
- prompt2.png
- prompt2.txt
- prompt3.png
- prompt3.txt
- prompt4.txt
- __Init__.py
- inference_sam_m2m_auto.py
- inference_sam_m2m_interactive.py
- __init__.py
- __init__.py
- automatic_mask_generator.py
- inference_seem_interactive.py
- inference_seem_pano.py
- interactive_seem_m2m_auto.py
- __init__.py
- __init__.py
- automatic_mask_generator.py
- inference_semsam_m2m_auto.py
- interactive_idino_1o1_box.py
- interactive_idino_m2m.py
- interactive_predictor.py
- lfq_visualizer.py
- visualizer.py
- visualizer_method_2.py
- visualizer_method_2_1.py
- visualizer_method_2_2.py
- visualizer_method_first_seg.py
- .gitignore
- camera_extrinsic2.npy
- CODE_OF_CONDUCT.md
- dataset_tasks.py
- demo_functional_grasp.py
- demo_gpt4v_som.py
- demo_som.py
- download_ckpt.sh
- draw_arrow.py
- gpt4v.py
- gpt4v_azure.py
- LICENSE
- main_behavior.py
- main_constraint.py
- main_grasp.py
- mask_filters.py
- README.md
- SECURITY.md
- SUPPORT.md
- .gitignore
- demo.py
- README.md
# Installation Guide
1. Get the code
git clone https://github.com/HaoxuHuang/copa
Downloads the entire project code from GitHub to your computer.
cd copa
Moves into the project folder you just downloaded.
2. CMake
Medium RecommendedPrerequisites
cd real_world
This project's files live in a subfolder, so move into it first.
mkdir build && cd build
Creates a folder to hold the build output and moves into it.
cmake ..
Analyzes the source code and generates build configuration files (must be run inside the build folder).
make
Compiles the code based on the generated build configuration to produce an executable.
Check that an executable was created inside the build folder, then run it directly (e.g. ./build/app_name).
3. Python
EasyPrerequisites
pip install -r graspnet/requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
python <μ€νν νμΌλͺ
>.py # READMEμμ μ νν μ€ν νμΌλͺ
μ νμΈνμΈμ
Runs the Python script (or module).
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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