mirror of
https://github.com/storytold/storyteller-ml.git
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moonshinkiro
74 lines
3.3 KiB
Markdown
74 lines
3.3 KiB
Markdown
## Introduction
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This is an image-to-3d render commandline inference point based on the official TripoSR repo at https://github.com/VAST-AI-Research/TripoSR
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### Installation
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- Python >= 3.8
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- Install CUDA if available
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- Create environment with `conda create -n triposr python=3.11`
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- Install PyTorch with `pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121` OTHERWISE do so according to your platform: [https://pytorch.org/get-started/locally/](https://pytorch.org/get-started/locally/) **[Please make sure that the locally-installed CUDA major version matches the PyTorch-shipped CUDA major version. For example if you have CUDA 11.x installed, make sure to install PyTorch compiled with CUDA 11.x.]**
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- Update setuptools by `pip install --upgrade setuptools`
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- Install other dependencies by `pip install -r requirements.txt`
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### Commandline Inference
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```sh
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python run.py examples/chair.png --output-dir output/ --bake-texture
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```
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This will save the reconstructed 3D model to `output/`. You can also specify more than one image path separated by spaces. The default options takes about **6GB VRAM** for a single image input.
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For detailed usage of this script, use `python run.py --help`.
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### Commandline Arguments
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`python run.py` commandline options:
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`-h, --help` show this help message and exit
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`--device` DEVICE
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Device to use. If no CUDA-compatible device is found, will fallback to 'cpu'. Default: 'cuda:0'
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`--pretrained-model-name-or-path` PRETRAINED_MODEL_NAME_OR_PATH
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Path to the pretrained model. Could be either a huggingface model id is or a local path. Default: 'stabilityai/TripoSR'
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`--chunk-size` CHUNK_SIZE
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Evaluation chunk size for surface extraction and rendering. Smaller chunk size reduces VRAM usage but
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increases computation time. 0 for no chunking. Default: 8192
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`--mc-resolution` MC_RESOLUTION
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Marching cubes grid resolution. Default: 256
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If specified, the background will NOT be automatically removed from the input image, and the input image should be an RGB image with gray background and properly-sized foreground. Default: false
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`--foreground-ratio` FOREGROUND_RATIO
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Ratio of the foreground size to the image size. Only used when --no-remove-bg is not specified.
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Default: 0.85
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`--output-dir` OUTPUT_DIR
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Output directory to save the results. Default: 'output/'
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`--model-save-format` {obj,glb}
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Format to save the extracted mesh. Default: 'obj'
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`--bake-texture`
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Bake a texture atlas for the extracted mesh, instead of vertex colors
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`--texture-resolution` TEXTURE_RESOLUTION
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Texture atlas resolution, only useful with --bake-texture. Default: 2048
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`--render`
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If specified, save a NeRF-rendered video. Default: false
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## Troubleshooting
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> AttributeError: module 'torchmcubes_module' has no attribute 'mcubes_cuda'
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or
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> torchmcubes was not compiled with CUDA support, use CPU version instead.
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This is because `torchmcubes` is compiled without CUDA support. Please make sure that
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- The locally-installed CUDA major version matches the PyTorch-shipped CUDA major version. For example if you have CUDA 11.x installed, make sure to install PyTorch compiled with CUDA 11.x.
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- `setuptools>=49.6.0`. If not, upgrade by `pip install --upgrade setuptools`.
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Then re-install `torchmcubes` by:
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```sh
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pip uninstall torchmcubes
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pip install git+https://github.com/tatsy/torchmcubes.git
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```
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