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Sefik Ilkin Serengil 2024-08-17 08:10:49 +01:00
parent 39a6d24163
commit 52d6873253
1 changed files with 8 additions and 9 deletions
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17
deepface/modules/verification.py
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@ -115,22 +115,21 @@ def verify(
}
def extract_embeddings_and_facial_areas(
img_path: Union[str, np.ndarray, List[float]],
index: int
) -> Tuple[List[List[float]], List[dict]]:
img_path: Union[str, np.ndarray, List[float]], index: int
) -> Tuple[List[List[float]], List[dict]]:
"""
Extracts facial embeddings and corresponding facial areas from an
image or returns pre-calculated embeddings.
Depending on the type of img_path, the function either extracts
facial embeddings from the provided image
facial embeddings from the provided image
(via a path or NumPy array) or verifies that the input is a list of
pre-calculated embeddings and validates them.
Args:
img_path (Union[str, np.ndarray, List[float]]):
- A string representing the file path to an image,
- A NumPy array containing the image data,
img_path (Union[str, np.ndarray, List[float]]):
- A string representing the file path to an image,
- A NumPy array containing the image data,
- Or a list of pre-calculated embedding values (of type `float`).
index (int): An index value used in error messages and logging
to identify the number of the image.
@ -150,7 +149,7 @@ def verify(
if silent is False:
logger.warn(
"You passed 1st image as pre-calculated embeddings."
f"You passed {index}-th image as pre-calculated embeddings."
"Please ensure that embeddings have been calculated"
f" for the {model_name} model."
)
@ -158,7 +157,7 @@ def verify(
if len(img_path) != dims:
raise ValueError(
f"embeddings of {model_name} should have {dims} dimensions,"
f" but it has {len(img_path)} dimensions input"
f" but {index}-th image has {len(img_path)} dimensions input"
)
img_embeddings = [img_path]