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progress bar

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Sefik Ilkin Serengil 2021-07-10 22:20:27 +03:00
parent 07df6b812e
commit 8d304056a8
1 changed files with 10 additions and 7 deletions
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17
deepface/DeepFace.py
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@ -65,7 +65,7 @@ def build_model(model_name):
return model_obj[model_name]
def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric = 'cosine', model = None, enforce_detection = True, detector_backend = 'opencv', align = True):
def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric = 'cosine', model = None, enforce_detection = True, detector_backend = 'opencv', align = True, prog_bar = True):
"""
This function verifies an image pair is same person or different persons.
@ -90,6 +90,8 @@ def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric =
detector_backend (string): set face detector backend as retinaface, mtcnn, opencv, ssd or dlib
prog_bar (boolean): enable/disable a progress bar
Returns:
Verify function returns a dictionary. If img1_path is a list of image pairs, then the function will return list of dictionary.
@ -138,8 +140,7 @@ def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric =
#------------------------------
#calling deepface in a for loop causes lots of progress bars. this prevents it.
disable_option = False if len(img_list) > 1 else True
disable_option = (False if len(img_list) > 1 else True) or not prog_bar
pbar = tqdm(range(0,len(img_list)), desc='Verification', disable = disable_option)
@ -279,7 +280,7 @@ def analyze(img_path, actions = ['emotion', 'age', 'gender', 'race'] , models =
enforce_detection (boolean): The function throws exception if a face could not be detected. Set this to True if you don't want to get exception. This might be convenient for low resolution images.
detector_backend (string): set face detector backend as retinaface, mtcnn, opencv, ssd or dlib.
prog_bar (boolean): enable/disable a progress bar
Returns:
The function returns a dictionary. If img_path is a list, then it will return list of dictionary.
@ -456,7 +457,7 @@ def analyze(img_path, actions = ['emotion', 'age', 'gender', 'race'] , models =
return resp_obj
def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine', model = None, enforce_detection = True, detector_backend = 'opencv', align = True):
def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine', model = None, enforce_detection = True, detector_backend = 'opencv', align = True, prog_bar = True):
"""
This function applies verification several times and find an identity in a database
@ -478,6 +479,8 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
detector_backend (string): set face detector backend as retinaface, mtcnn, opencv, ssd or dlib
prog_bar (boolean): enable/disable a progress bar
Returns:
This function returns pandas data frame. If a list of images is passed to img_path, then it will return list of pandas data frame.
"""
@ -552,7 +555,7 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
representations = []
pbar = tqdm(range(0,len(employees)), desc='Finding representations')
pbar = tqdm(range(0,len(employees)), desc='Finding representations', disable = prog_bar)
#for employee in employees:
for index in pbar:
@ -597,7 +600,7 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
resp_obj = []
global_pbar = tqdm(range(0,len(img_paths)), desc='Analyzing')
global_pbar = tqdm(range(0, len(img_paths)), desc='Analyzing', disable = prog_bar)
for j in global_pbar:
img_path = img_paths[j]