deepface/DeepFace.py

# common dependencies
import os
import warnings
import logging
from typing import Any, Dict, List, Tuple, Union, Optional

# this has to be set before importing tensorflow
os.environ["TF_USE_LEGACY_KERAS"] = "1"

# pylint: disable=wrong-import-position

# 3rd party dependencies
import numpy as np
import pandas as pd
import tensorflow as tf

# package dependencies
from deepface.commons import package_utils, folder_utils
from deepface.modules import (
    recognition,
    demography,
)

# users should install tf_keras package if they are using tf 2.16 or later versions
package_utils.validate_for_keras3()


# create required folders if necessary to store model weights
folder_utils.initialize_folder()


def analyze(
    img_path: Union[str, np.ndarray],
    actions: Union[tuple, list] = ("emotion", "age", "gender", "race"),
    enforce_detection: bool = True,
    detector_backend: str = "opencv",
    align: bool = True,
    expand_percentage: int = 0,
    silent: bool = False,
) -> List[Dict[str, Any]]:
    return demography.analyze(
        img_path=img_path,
        actions=actions,
        enforce_detection=enforce_detection,
        detector_backend=detector_backend,
        align=align,
        expand_percentage=expand_percentage,
        silent=silent,
    )


def find(
    img_path: Union[str, np.ndarray],
    db_path: str,
    model_name: str = "VGG-Face",
    distance_metric: str = "cosine",
    enforce_detection: bool = True,
    detector_backend: str = "opencv",
    align: bool = True,
    expand_percentage: int = 0,
    threshold: Optional[float] = None,
    normalization: str = "base",
    silent: bool = False,
) -> List[pd.DataFrame]:
    
    return recognition.find(
        img_path=img_path,
        db_path=db_path,
        model_name=model_name,
        distance_metric=distance_metric,
        enforce_detection=enforce_detection,
        detector_backend=detector_backend,
        align=align,
        expand_percentage=expand_percentage,
        threshold=threshold,
        normalization=normalization,
        silent=silent,
    )