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deepFace batch detection; typing

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galthran-wq 2025-02-12 10:04:20 +00:00
parent f4d18a70c0
commit 0ad7c57abf
2 changed files with 8 additions and 8 deletions
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12
deepface/DeepFace.py
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@ -2,7 +2,7 @@
import os
import warnings
import logging
from typing import Any, Dict, IO, List, Union, Optional
from typing import Any, Dict, IO, List, Union, Optional, Sequence
# this has to be set before importing tensorflow
os.environ["TF_USE_LEGACY_KERAS"] = "1"
@ -510,7 +510,7 @@ def stream(
def extract_faces(
img_path: Union[str, np.ndarray, IO[bytes]],
img_path: Union[str, np.ndarray, IO[bytes], Sequence[Union[str, np.ndarray, IO[bytes]]]],
detector_backend: str = "opencv",
enforce_detection: bool = True,
align: bool = True,
@ -521,12 +521,12 @@ def extract_faces(
anti_spoofing: bool = False,
) -> List[Dict[str, Any]]:
"""
Extract faces from a given image
Extract faces from a given image or sequence of images.
Args:
img_path (str or np.ndarray or IO[bytes]): Path to the first image. Accepts exact image path
as a string, numpy array (BGR), a file object that supports at least `.read` and is
opened in binary mode, or base64 encoded images.
img_path (Union[str, np.ndarray, IO[bytes], Sequence[Union[str, np.ndarray, IO[bytes]]]]):
Path(s) to the image(s). Accepts a string path, a numpy array (BGR), a file object
that supports at least `.read` and is opened in binary mode, or base64 encoded images.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',

4
deepface/modules/detection.py
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@ -1,5 +1,5 @@
# built-in dependencies
from typing import Any, Dict, IO, List, Tuple, Union, Optional
from typing import Any, Dict, IO, List, Tuple, Union, Optional, Sequence
# 3rd part dependencies
from heapq import nlargest
@ -19,7 +19,7 @@ logger = Logger()
def extract_faces(
img_path: Union[List[Union[str, np.ndarray, IO[bytes]]], str, np.ndarray, IO[bytes]],
img_path: Union[Sequence[Union[str, np.ndarray, IO[bytes]]], str, np.ndarray, IO[bytes]],
detector_backend: str = "opencv",
enforce_detection: bool = True,
align: bool = True,