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Merge pull request #1223 from GobinathAL/threshold

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Sefik Ilkin Serengil 2024-04-30 19:20:50 +01:00 committed by GitHub
commit 04baf3e179
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2 changed files with 15 additions and 2 deletions
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7
deepface/DeepFace.py
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@ -72,6 +72,7 @@ def verify(
expand_percentage: int = 0,
normalization: str = "base",
silent: bool = False,
threshold: Optional[float] = None,
) -> Dict[str, Any]:
"""
Verify if an image pair represents the same person or different persons.
@ -107,6 +108,11 @@ def verify(
silent (boolean): Suppress or allow some log messages for a quieter analysis process
(default is False).
threshold (float): Specify a threshold to determine whether a pair represents the same
person or different individuals. This threshold is used for comparing distances.
If left unset, default pre-tuned threshold values will be applied based on the specified
model name and distance metric (default is None).
Returns:
result (dict): A dictionary containing verification results with following keys.
@ -143,6 +149,7 @@ def verify(
expand_percentage=expand_percentage,
normalization=normalization,
silent=silent,
threshold=threshold,
)

10
deepface/modules/verification.py
View File

@ -1,6 +1,6 @@
# built-in dependencies
import time
from typing import Any, Dict, Union, List, Tuple
from typing import Any, Dict, Optional, Union, List, Tuple
# 3rd party dependencies
import numpy as np
@ -24,6 +24,7 @@ def verify(
expand_percentage: int = 0,
normalization: str = "base",
silent: bool = False,
threshold: Optional[float] = None,
) -> Dict[str, Any]:
"""
Verify if an image pair represents the same person or different persons.
@ -63,6 +64,11 @@ def verify(
silent (boolean): Suppress or allow some log messages for a quieter analysis process
(default is False).
threshold (float): Specify a threshold to determine whether a pair represents the same
person or different individuals. This threshold is used for comparing distances.
If left unset, default pre-tuned threshold values will be applied based on the specified
model name and distance metric (default is None).
Returns:
result (dict): A dictionary containing verification results.
@ -186,7 +192,7 @@ def verify(
)
# find the face pair with minimum distance
threshold = find_threshold(model_name, distance_metric)
threshold = threshold or find_threshold(model_name, distance_metric)
distance = float(min(distances)) # best distance
facial_areas = facial_areas[np.argmin(distances)]