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deepfracture

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fracture
vq-vae
physical-simulation
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deepfracture
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{
  "model_name": "pre-trained-v2",
  "version": "2.0.0",
  "description": "Physics-based 3D object deformation models",
  "architecture": "encoder-decoder",
  "framework": "pytorch",
  "available_models": [
    {
      "name": "base",
      "description": "Base object deformation model",
      "training_samples": 277,
      "file_size_mb": 360,
      "files": [
        "base.obj",
        "base-encoder.pt",
        "base-decoder.pt",
        "base-1000-encoder.pt",
        "base-1000-decoder.pt"
      ]
    },
    {
      "name": "pot",
      "description": "Pot object deformation model",
      "training_samples": 433,
      "file_size_mb": 367,
      "files": [
        "pot.obj",
        "pot-encoder.pt",
        "pot-decoder.pt",
        "pot-1000-encoder.pt",
        "pot-1000-decoder.pt"
      ]
    },
    {
      "name": "squirrel",
      "description": "Squirrel object deformation model",
      "training_samples": 0,
      "file_size_mb": 0,
      "files": [
        "squirrel.obj",
        "squirrel-encoder.pt",
        "squirrel-decoder.pt",
        "squirrel-1000-encoder.pt",
        "squirrel-1000-decoder.pt"
      ]
    },
    {
      "name": "bunny",
      "description": "Bunny object deformation model",
      "training_samples": 0,
      "file_size_mb": 0,
      "files": [
        "bunny.obj",
        "bunny-encoder.pt",
        "bunny-decoder.pt",
        "bunny-1000-encoder.pt",
        "bunny-1000-decoder.pt"
      ]
    },
    {
      "name": "lion",
      "description": "Lion object deformation model",
      "training_samples": 0,
      "file_size_mb": 0,
      "files": [
        "lion.obj",
        "lion-encoder.pt",
        "lion-decoder.pt",
        "lion-1000-encoder.pt",
        "lion-1000-decoder.pt"
      ]
    }
  ],
  "model_config": {
    "encoder": {
      "type": "mlp_with_attention",
      "input_dim": 9,
      "hidden_dims": [512, 256, 128],
      "output_dim": 64
    },
    "decoder": {
      "type": "geometric_reconstruction",
      "input_dim": 64,
      "hidden_dims": [128, 256, 512],
      "output_dim": 3
    },
    "training": {
      "optimizer": "adam",
      "learning_rate": 1e-4,
      "batch_size": 32,
      "epochs": 1000,
      "loss_function": "combined_geometric_physics"
    }
  },
  "requirements": {
    "python": ">=3.8",
    "pytorch": ">=1.9.0",
    "numpy": ">=1.21.0",
    "trimesh": ">=3.9.0"
  },
  "license": "Apache-2.0",
  "authors": ["Your Name"],
  "contact": "your.email@example.com"
}