mapanything/models/__init__.py

"""
Model Factory for MapAnything
"""

import importlib.util
import logging
import warnings

import numpy as np
from omegaconf import DictConfig, OmegaConf

# Core models that are always available
from mapanything.models.any4d.models.model import Any4D

# Suppress DINOv2 warnings
logging.getLogger("dinov2").setLevel(logging.WARNING)
warnings.filterwarnings("ignore", message="xFormers is available", category=UserWarning)
warnings.filterwarnings(
    "ignore", message="xFormers is not available", category=UserWarning
)


def resolve_special_float(value):
    if value == "inf":
        return np.inf
    elif value == "-inf":
        return -np.inf
    else:
        raise ValueError(f"Unknown special float value: {value}")


def init_model(
    model_str: str, model_config: DictConfig, torch_hub_force_reload: bool = False
):
    """
    Initialize a model using OmegaConf configuration.

    Args:
        model_str (str): Name of the model class to create.
        model_config (DictConfig): OmegaConf model configuration.
        torch_hub_force_reload (bool): Whether to force reload relevant parts of the model from torch hub.
    """
    if not OmegaConf.has_resolver("special_float"):
        OmegaConf.register_new_resolver("special_float", resolve_special_float)
    model_dict = OmegaConf.to_container(model_config, resolve=True)
    model = model_factory(
        model_str, torch_hub_force_reload=torch_hub_force_reload, **model_dict
    )

    return model


# Define model configurations with import paths
MODEL_CONFIGS = {
    "any4d": {
        "class": Any4D,
    },
}


def check_module_exists(module_path):
    """
    Check if a module can be imported without actually importing it.

    Args:
        module_path (str): The path to the module to check.

    Returns:
        bool: True if the module can be imported, False otherwise.
    """
    return importlib.util.find_spec(module_path) is not None


def model_factory(model_str: str, **kwargs):
    """
    Model factory for MapAnything.

    Args:
        model_str (str): Name of the model to create.
        **kwargs: Additional keyword arguments to pass to the model constructor.

    Returns:
       nn.Module: An instance of the specified model.
    """
    if model_str not in MODEL_CONFIGS:
        raise ValueError(
            f"Unknown model: {model_str}. Valid options are: {', '.join(MODEL_CONFIGS.keys())}"
        )

    model_config = MODEL_CONFIGS[model_str]

    # Handle core models directly
    if "class" in model_config:
        model_class = model_config["class"]
    # Handle external models with dynamic imports
    elif "module" in model_config:
        module_path = model_config["module"]
        class_name = model_config["class_name"]

        # Check if the module can be imported
        if not check_module_exists(module_path):
            raise ImportError(
                f"Model '{model_str}' requires module '{module_path}' which is not installed. "
                f"Please install the corresponding submodule or package."
            )

        # Dynamically import the module and get the class
        try:
            module = importlib.import_module(module_path)
            model_class = getattr(module, class_name)
        except (ImportError, AttributeError) as e:
            raise ImportError(
                f"Failed to import {class_name} from {module_path}: {str(e)}"
            )
    else:
        raise ValueError(f"Invalid model configuration for {model_str}")

    print(f"Initializing {model_class} with kwargs: {kwargs}")
    if model_str != "org_dust3r":
        return model_class(**kwargs)
    else:
        eval_str = kwargs.get("model_eval_str", None)
        return eval(eval_str)


def get_available_models() -> list:
    """
    Get a list of available models in MapAnything.

    Returns:
        list: A list of available model names.
    """
    return list(MODEL_CONFIGS.keys())


__all__ = ["model_factory", "get_available_models"]