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fix linter issues

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This commit is contained in:
Stefan Charsley 2025-03-02 23:50:03 +00:00
parent da41050308
commit 1372180567
1 changed files with 52 additions and 13 deletions
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65
deepface/api/src/modules/core/routes.py
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@ -85,12 +85,24 @@ def represent():
img_path=img, img_path=img,
model_name=input_args.get("model_name", "VGG-Face"), model_name=input_args.get("model_name", "VGG-Face"),
detector_backend=input_args.get("detector_backend", "opencv"), detector_backend=input_args.get("detector_backend", "opencv"),
enforce_detection=input_args.get("enforce_detection", True) if type(input_args.get("enforce_detection", True)) is bool else input_args.get("enforce_detection") == "true", enforce_detection=
align=input_args.get("align", True) if type(input_args.get("align", True)) is bool else input_args.get("align") == "true", bool(input_args.get("enforce_detection", True))
if isinstance((input_args.get("enforce_detection", True)), bool)
else input_args.get("enforce_detection") == "true",
align=
bool(input_args.get("align", True))
if isinstance((input_args.get("align", True)), bool)
else input_args.get("align") == "true",
expand_percentage=int(input_args.get("expand_percentage", 0)), expand_percentage=int(input_args.get("expand_percentage", 0)),
normalization=input_args.get("normalization", "base"), normalization=input_args.get("normalization", "base"),
anti_spoofing=input_args.get("anti_spoofing", False) if type(input_args.get("anti_spoofing", False)) is bool else input_args.get("anti_spoofing") == "true", anti_spoofing=
max_faces=None if input_args.get("max_faces", None) is None else int(input_args.get("max_faces")), bool(input_args.get("anti_spoofing", False))
if isinstance((input_args.get("anti_spoofing", False)), bool)
else input_args.get("anti_spoofing") == "true",
max_faces=
None
if input_args.get("max_faces", None) is None
else int(input_args.get("max_faces", 0)),
) )
logger.debug(obj) logger.debug(obj)
@ -120,13 +132,28 @@ def verify():
model_name=input_args.get("model_name", "VGG-Face"), model_name=input_args.get("model_name", "VGG-Face"),
detector_backend=input_args.get("detector_backend", "opencv"), detector_backend=input_args.get("detector_backend", "opencv"),
distance_metric=input_args.get("distance_metric", "cosine"), distance_metric=input_args.get("distance_metric", "cosine"),
enforce_detection=input_args.get("enforce_detection", True) if type(input_args.get("enforce_detection", True)) is bool else input_args.get("enforce_detection") == "true", enforce_detection=
align=input_args.get("align", True) if type(input_args.get("align", True)) is bool else input_args.get("align") == "true", bool(input_args.get("enforce_detection", True))
if isinstance((input_args.get("enforce_detection", True)), bool)
else input_args.get("enforce_detection") == "true",
align=
bool(input_args.get("align", True))
if isinstance((input_args.get("align", True)), bool)
else input_args.get("align") == "true",
expand_percentage=int(input_args.get("expand_percentage", 0)), expand_percentage=int(input_args.get("expand_percentage", 0)),
normalization=input_args.get("normalization", "base"), normalization=input_args.get("normalization", "base"),
silent=input_args.get("silent", False) if type(input_args.get("silent", False)) is bool else input_args.get("silent") == "true", silent=
threshold=None if input_args.get("threshold", None) is None else float(input_args.get("threshold")), bool(input_args.get("silent", False))
anti_spoofing=input_args.get("anti_spoofing", False) if type(input_args.get("anti_spoofing", False)) is bool else input_args.get("anti_spoofing") == "true", if isinstance((input_args.get("silent", False)), bool)
else input_args.get("silent") == "true",
threshold=
None
if input_args.get("threshold", None) is None
else float(input_args.get("threshold", 0)),
anti_spoofing=
bool(input_args.get("anti_spoofing", False))
if isinstance((input_args.get("anti_spoofing", False)), bool)
else input_args.get("anti_spoofing") == "true",
) )
logger.debug(verification) logger.debug(verification)
@ -164,11 +191,23 @@ def analyze():
img_path=img, img_path=img,
actions=actions, actions=actions,
detector_backend=input_args.get("detector_backend", "opencv"), detector_backend=input_args.get("detector_backend", "opencv"),
enforce_detection=input_args.get("enforce_detection", True) if type(input_args.get("enforce_detection", True)) is bool else input_args.get("enforce_detection") == "true", enforce_detection=
align=input_args.get("align", True) if type(input_args.get("align", True)) is bool else input_args.get("align") == "true", bool(input_args.get("enforce_detection", True))
if isinstance((input_args.get("enforce_detection", True)), bool)
else input_args.get("enforce_detection") == "true",
align=
bool(input_args.get("align", True))
if isinstance((input_args.get("align", True)), bool)
else input_args.get("align") == "true",
expand_percentage=int(input_args.get("expand_percentage", 0)), expand_percentage=int(input_args.get("expand_percentage", 0)),
silent=input_args.get("silent", False) if type(input_args.get("silent", False)) is bool else input_args.get("silent") == "true", silent=
anti_spoofing=input_args.get("anti_spoofing", False) if type(input_args.get("anti_spoofing", False)) is bool else input_args.get("anti_spoofing") == "true", bool(input_args.get("silent", False))
if isinstance((input_args.get("silent", False)), bool)
else input_args.get("silent") == "true",
anti_spoofing=
bool(input_args.get("anti_spoofing", False))
if isinstance((input_args.get("anti_spoofing", False)), bool)
else input_args.get("anti_spoofing") == "true",
) )
logger.debug(demographies) logger.debug(demographies)