From 86fa2dfa83b25f0dcec943ffa70b3959f4818751 Mon Sep 17 00:00:00 2001 From: "Samuel J. Woodward" Date: Fri, 10 Jan 2025 11:46:28 -0500 Subject: [PATCH] updating docstrings to appease linter --- deepface/DeepFace.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py index b42c40d..58547fa 100644 --- a/deepface/DeepFace.py +++ b/deepface/DeepFace.py @@ -176,9 +176,9 @@ def analyze( """ Analyze facial attributes such as age, gender, emotion, and race in the provided image. Args: - img_path (str or np.ndarray or IO[bytes]): The exact path to the image, a numpy array in BGR format, - or a base64 encoded image. If the source image contains multiple faces, the result will - include information for each detected face. + img_path (str or np.ndarray or IO[bytes]): The exact path to the image, a numpy array + in BGR format, or a base64 encoded image. If the source image contains multiple faces, + the result will include information for each detected face. actions (tuple): Attributes to analyze. The default is ('age', 'gender', 'emotion', 'race'). You can exclude some of these attributes from the analysis if needed. @@ -281,9 +281,9 @@ def find( """ Identify individuals in a database Args: - img_path (str or np.ndarray or IO[bytes]): The exact path to the image, a numpy array in BGR format, - or a base64 encoded image. If the source image contains multiple faces, the result will - include information for each detected face. + img_path (str or np.ndarray or IO[bytes]): The exact path to the image, a numpy array + in BGR format, or a base64 encoded image. If the source image contains multiple + faces, the result will include information for each detected face. db_path (string): Path to the folder containing image files. All detected faces in the database will be considered in the decision-making process. @@ -383,9 +383,9 @@ def represent( Represent facial images as multi-dimensional vector embeddings. Args: - img_path (str or np.ndarray or IO[bytes]): The exact path to the image, a numpy array in BGR format, - or a base64 encoded image. If the source image contains multiple faces, the result will - include information for each detected face. + img_path (str or np.ndarray or IO[bytes]): The exact path to the image, a numpy array + in BGR format, or a base64 encoded image. If the source image contains multiple faces, + the result will include information for each detected face. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet