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updated PR to remove model parameter

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This commit is contained in:
Ronald Pereira 2023-01-26 11:49:56 -03:00
parent d24aeae030
commit 6e6215e4b9
1 changed files with 2 additions and 7 deletions
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deepface/DeepFace.py
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@ -494,7 +494,7 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
return resp_obj return resp_obj
def represent(img_path, model_name = 'VGG-Face', model = None, enforce_detection = True, detector_backend = 'opencv', align = True, normalization = 'base'): def represent(img_path, model_name = 'VGG-Face', enforce_detection = True, detector_backend = 'opencv', align = True, normalization = 'base'):
""" """
This function represents facial images as vectors. The function uses convolutional neural networks models to generate vector embeddings. This function represents facial images as vectors. The function uses convolutional neural networks models to generate vector embeddings.
@ -504,10 +504,6 @@ def represent(img_path, model_name = 'VGG-Face', model = None, enforce_detection
model_name (string): VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace model_name (string): VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace
model: Built deepface model. A face recognition model is built every call of verify function. You can pass pre-built face recognition model optionally if you will call verify function several times. Consider to pass model if you are going to call represent function in a for loop.
model = DeepFace.build_model('VGG-Face')
enforce_detection (boolean): If no face could not be detected in an image, then this function will return exception by default. enforce_detection (boolean): If no face could not be detected in an image, then this function will return exception by default.
Set this to False not to have this exception. This might be convenient for low resolution images. Set this to False not to have this exception. This might be convenient for low resolution images.
@ -522,8 +518,7 @@ def represent(img_path, model_name = 'VGG-Face', model = None, enforce_detection
""" """
resp_objs = [] resp_objs = []
if model is None: model = build_model(model_name)
model = build_model(model_name)
#--------------------------------- #---------------------------------
# we started to run pre-process in verification. so, this can be skipped if it is coming from verification. # we started to run pre-process in verification. so, this can be skipped if it is coming from verification.