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dylanebert
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initial commit
Browse files- app.py +41 -0
- requirements.txt +34 -0
app.py
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import shlex
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import subprocess
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import gradio as gr
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import numpy as np
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import torch
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from diffusers import DiffusionPipeline
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subprocess.run(
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shlex.split(
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"pip install https://huggingface.co/spaces/dylanebert/LGM-mini/resolve/main/wheel/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl"
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)
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)
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pipeline = DiffusionPipeline.from_pretrained(
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"dylanebert/LGM-full",
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custom_pipeline="dylanebert/LGM-full",
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torch_dtype=torch.float16,
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trust_remote_code=True,
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).to("cuda")
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def run(image):
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input_image = np.array(image, dtype=np.float32) / 255.0
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splat = pipeline(
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"", input_image, guidance_scale=5, num_inference_steps=30, elevation=0
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)
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splat_file = "/tmp/output.ply"
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pipeline.save_ply(splat, splat_file)
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return splat_file
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demo = gr.Interface(
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fn=run,
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inputs="image",
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outputs=gr.Model3D(),
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examples=[
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"https://huggingface.co/datasets/dylanebert/iso3d/resolve/main/jpg@512/a_cat_statue.jpg"
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],
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)
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demo.queue().launch()
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requirements.txt
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wheel
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numpy
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tyro
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diffusers
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dearpygui
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einops
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accelerate
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gradio
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imageio
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imageio-ffmpeg
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lpips
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matplotlib
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packaging
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Pillow
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pygltflib
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rembg[gpu,cli]
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rich
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safetensors
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scikit-image
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scikit-learn
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scipy
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spaces
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tqdm
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transformers
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trimesh
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kiui >= 0.2.3
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xatlas
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roma
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plyfile
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torch == 2.2.0
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torchvision == 0.17.0
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torchaudio == 2.2.0
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xformers
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ushlex
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