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--- |
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license: apache-2.0 |
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library_name: generic |
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tags: |
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- motion-generation |
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- diffusion |
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- 3d |
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- humanml3d |
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- babel |
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--- |
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# FloodDiffusion Downloads |
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This repository contains the datasets, dependencies, and pretrained models for **FloodDiffusion: Tailored Diffusion Forcing for Streaming Motion Generation**. |
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Code repository: [GitHub](https://github.com/ShandaAI/FloodDiffusion) |
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## Repository Structure |
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The files in this repository are organized to match the directory structure required by FloodDiffusion. |
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### 1. Model Checkpoints |
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The `outputs.zip` and `outputs_tiny.zip` archives contains the pretrained model weights. |
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* **Target**: Unzip into your project root. It should create an `outputs/` folder. |
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``` |
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outputs/ |
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βββ vae_1d_z4_step=300000.ckpt # VAE model (1D, z_dim=4) |
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βββ 20251106_063218_ldf/ |
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β βββ step_step=50000.ckpt # LDF model checkpoint (HumanML3D) |
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βββ 20251107_021814_ldf_stream/ |
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β βββ step_step=240000.ckpt # LDF streaming model checkpoint (BABEL) |
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βββ 20251217_023720_ldf_tiny/ |
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β βββ step_step=60000.ckpt # LDF tiny model checkpoint |
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βββ 20251219_01492_ldf_tiny_stream/ |
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βββ step_step=200000.ckpt # LDF tiny streaming model checkpoint |
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``` |
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### 2. Datasets |
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Due to the large number of files, datasets are provided as ZIP archives. |
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* **`HumanML3D.zip`**: Contains the HumanML3D dataset (extracted features and texts). |
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* **Target**: Unzip into `raw_data/`. It should create `raw_data/HumanML3D/` containing `new_joint_vecs`, `texts`, etc. |
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* **`BABEL_streamed.zip`**: Contains the BABEL dataset processed for streaming generation. |
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* **Target**: Unzip into `raw_data/`. It should create `raw_data/BABEL_streamed/`. |
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### 3. Dependencies (`deps.zip`) |
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* **`deps.zip`**: Contains necessary dependencies like the T5 text encoder, evaluation models (T2M), and GloVe embeddings. |
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* **Target**: Unzip into your project root. It should create a `deps/` folder. |
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``` |
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deps/ |
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βββ t2m/ # Text-to-Motion evaluation models |
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βββ glove/ # GloVe word embeddings |
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βββ t5_umt5-xxl-enc-bf16/ # T5 text encoder |
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``` |
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## How to Download & Setup |
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We recommend using the python script below to automatically download and place files in the correct structure. |
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### Python Script (Recommended) |
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Save this as `download_assets.py` in your `FloodDiffusion` project root: |
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```python |
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from huggingface_hub import hf_hub_download |
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import zipfile |
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import os |
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REPO_ID = "ShandaAI/FloodDiffusionDownloads" |
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def download_extract_zip(filename, target_dir="."): |
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print(f"Downloading {filename}...") |
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path = hf_hub_download(repo_id=REPO_ID, filename=filename, repo_type="model") |
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print(f"Extracting {filename} to {target_dir}...") |
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with zipfile.ZipFile(path, 'r') as zip_ref: |
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zip_ref.extractall(target_dir) |
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# 1. Download and extract Dependencies (creates ./deps/) |
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download_extract_zip("deps.zip", ".") |
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# 2. Download and extract Datasets (creates ./raw_data/HumanML3D and ./raw_data/BABEL_streamed) |
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os.makedirs("raw_data", exist_ok=True) |
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download_extract_zip("HumanML3D.zip", "raw_data") |
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download_extract_zip("BABEL_streamed.zip", "raw_data") |
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# 3. Download Models (creates ./outputs/) |
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download_extract_zip("outputs.zip", ".") |
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download_extract_zip("outputs_tiny.zip", ".") |
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print("Done! Your project is ready.") |
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``` |
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## Data License & Acknowledgements |
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This repository provides pre-processed motion features (263-dim) to facilitate the reproduction of FloodDiffusion. |
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- **HumanML3D**: The motion features are derived from the [HumanML3D](https://github.com/EricGuo5513/HumanML3D) pipeline, originally built upon [AMASS](https://amass.is.tue.mpg.de/) and [HumanAct12](https://github.com/EricGuo5513/Action2Motion). |
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- **BABEL**: The streaming motion features are derived from the [BABEL](https://babel.is.tue.mpg.de/) dataset, which also builds upon AMASS. |
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**Important Note**: |
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We only distribute the **extracted motion features and text annotations**, which is standard practice in the research community. We do **not** distribute the raw AMASS data (SMPL parameters/meshes). If you require the raw motion data or plan to use it for commercial purposes, you must register and agree to the licenses on the [AMASS website](https://amass.is.tue.mpg.de/). |
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