Diffusion-Policy/requirements.txt at final-submission · thedannyliu/Diffusion-Policy · GitHub

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# ============================================
# DPFM: Diffusion Policy with Flow Matching
# Requirements for the project
# ============================================

# Core Deep Learning
torch>=1.12.1
torchvision>=0.13.1
einops>=0.4.1

# Diffusion / Flow Matching
diffusers>=0.11.1

# Visualization and Logging
matplotlib>=3.6.0
wandb>=0.13.0
tensorboard>=2.10.0
tensorboardx>=2.5.0

# Data Handling
numpy>=1.23.0
scipy>=1.9.0
h5py>=3.7.0
zarr>=2.12.0
numcodecs>=0.10.0

# Configuration
hydra-core>=1.2.0
omegaconf>=2.2.0

# Image Processing
opencv-python>=4.6.0
scikit-image>=0.19.0
imageio>=2.22.0
imageio-ffmpeg>=0.4.7

# Simulation Environments
gym==0.21.0
robomimic==0.2.0
robosuite @ git+https://github.com/cheng-chi/robosuite.git@277ab9588ad7a4f4b55cf75508b44aa67ec171f0
mujoco-py>=2.1.0

# Utilities
tqdm>=4.64.0
dill>=0.3.5
click>=8.0.4
termcolor>=2.0.0
psutil>=5.9.0

# Video Processing
scikit-video>=1.1.11
av>=10.0.0

# For Push-T environment
pymunk>=6.2.1
pygame>=2.1.2
shapely>=1.8.4

# Testing
pytest>=7.0.0

# Flow Matching (additional dependencies)
# For implementing flow matching loss
# torchdiffeq>=0.2.3  # Optional: for ODE solvers if needed