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from deepface import DeepFace
# pylint: disable=broad-except
def represent(img_path, model_name, detector_backend, enforce_detection, align):
try:
result = {}
embedding_objs = DeepFace.represent(
img_path=img_path,
model_name=model_name,
detector_backend=detector_backend,
enforce_detection=enforce_detection,
align=align,
)
result["results"] = embedding_objs
return result
except Exception as err:
return {"error": f"Exception while representing: {str(err)}"}, 400
def verify(
img1_path, img2_path, model_name, detector_backend, distance_metric, enforce_detection, align
):
try:
obj = DeepFace.verify(
img1_path=img1_path,
img2_path=img2_path,
model_name=model_name,
detector_backend=detector_backend,
distance_metric=distance_metric,
align=align,
enforce_detection=enforce_detection,
)
return obj
except Exception as err:
return {"error": f"Exception while verifying: {str(err)}"}, 400
def analyze(img_path, actions, detector_backend, enforce_detection, align):
try:
result = {}
demographies = DeepFace.analyze(
img_path=img_path,
actions=actions,
detector_backend=detector_backend,
enforce_detection=enforce_detection,
align=align,
silent=True,
)
result["results"] = demographies
return result
except Exception as err:
return {"error": f"Exception while analyzing: {str(err)}"}, 400
def find(img_path, db_path, model_name, detector_backend, distance_metric, enforce_detection, align):
try:
obj = DeepFace.find(
img_path=img_path,
db_path=db_path,
model_name=model_name,
detector_backend=detector_backend,
distance_metric=distance_metric,
align=align,
enforce_detection=enforce_detection,
)
return obj
except Exception as err:
return {"error": f"Exception while Findind: {str(err)}"}, 400
def sync_datasets():
try:
DeepFace.sync_datasets()
return {'data': 'synced successfully'}, 200
except Exception as e:
return {'error': str(e)}, 400
def delete_pkls():
try:
DeepFace.delete_pkls()
return {'data': 'pkl files deleted successfully'}, 200
except Exception as e:
return {'error': str(e)}, 400 |