github/deepface
1
1
Fork 0
mirror of https://github.com/serengil/deepface.git synced 2025-06-07 12:05:22 +00:00
Code Issues Packages Projects Releases Wiki Activity

face recognition models as global

Browse Source
This commit is contained in:
Sefik Ilkin Serengil 2021-06-24 00:11:06 +03:00
parent 9f31012ef4
commit e0809bf490
2 changed files with 17 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
deepface/DeepFace.py
View File

@ -35,6 +35,8 @@ def build_model(model_name):
built deepface model
"""
global model_obj, model_label
models = {
'VGG-Face': VGGFace.loadModel,
'OpenFace': OpenFace.loadModel,
@ -43,22 +45,25 @@ def build_model(model_name):
'DeepID': DeepID.loadModel,
'Dlib': DlibWrapper.loadModel,
'ArcFace': ArcFace.loadModel,
'Emotion': Emotion.loadModel,
'Age': Age.loadModel,
'Gender': Gender.loadModel,
'Race': Race.loadModel
}
model = models.get(model_name)
if not "model_obj" in globals() or model_label != model_name:
if model:
model = model()
model_obj = models.get(model_name)
if model_obj:
model_obj = model_obj()
model_label = model_name
#print('Using {} model backend'.format(model_name))
return model
else:
raise ValueError('Invalid model_name passed - {}'.format(model_name))
return model_obj
def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric = 'cosine', model = None, enforce_detection = True, detector_backend = 'opencv', align = True):
"""

7
tests/unit_tests.py
View File

@ -186,8 +186,8 @@ metrics = ['cosine', 'euclidean', 'euclidean_l2']
passed_tests = 0; test_cases = 0
for model in models:
prebuilt_model = DeepFace.build_model(model)
print(model," is built")
#prebuilt_model = DeepFace.build_model(model)
#print(model," is built")
for metric in metrics:
for instance in dataset:
img1 = instance[0]
@ -195,7 +195,8 @@ for model in models:
result = instance[2]
resp_obj = DeepFace.verify(img1, img2
, model_name = model, model = prebuilt_model
, model_name = model
#, model = prebuilt_model
, distance_metric = metric)
prediction = resp_obj["verified"]