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align arg for detectFace

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Sefik Ilkin Serengil 2021-07-30 17:06:16 +03:00
parent 412ca5743b
commit b4631f1562
2 changed files with 6 additions and 2 deletions
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4
deepface/DeepFace.py
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@ -779,7 +779,7 @@ def stream(db_path = '', model_name ='VGG-Face', detector_backend = 'opencv', di
realtime.analysis(db_path, model_name, detector_backend, distance_metric, enable_face_analysis realtime.analysis(db_path, model_name, detector_backend, distance_metric, enable_face_analysis
, source = source, time_threshold = time_threshold, frame_threshold = frame_threshold) , source = source, time_threshold = time_threshold, frame_threshold = frame_threshold)
def detectFace(img_path, detector_backend = 'opencv', enforce_detection = True): def detectFace(img_path, detector_backend = 'opencv', enforce_detection = True, align = True):
""" """
This function applies pre-processing stages of a face recognition pipeline including detection and alignment This function applies pre-processing stages of a face recognition pipeline including detection and alignment
@ -794,7 +794,7 @@ def detectFace(img_path, detector_backend = 'opencv', enforce_detection = True):
""" """
img = functions.preprocess_face(img = img_path, detector_backend = detector_backend img = functions.preprocess_face(img = img_path, detector_backend = detector_backend
, enforce_detection = enforce_detection)[0] #preprocess_face returns (1, 224, 224, 3) , enforce_detection = enforce_detection, align = align)[0] #preprocess_face returns (1, 224, 224, 3)
return img[:, :, ::-1] #bgr to rgb return img[:, :, ::-1] #bgr to rgb
#--------------------------- #---------------------------

4
deepface/commons/functions.py
View File

@ -153,10 +153,14 @@ def preprocess_face(img, target_size=(224, 224), grayscale = False, enforce_dete
#--------------------------------------------------- #---------------------------------------------------
#normalizing the image pixels
img_pixels = image.img_to_array(img) img_pixels = image.img_to_array(img)
img_pixels = np.expand_dims(img_pixels, axis = 0) img_pixels = np.expand_dims(img_pixels, axis = 0)
img_pixels /= 255 #normalize input in [0, 1] img_pixels /= 255 #normalize input in [0, 1]
#---------------------------------------------------
if return_region == True: if return_region == True:
return img_pixels, region return img_pixels, region
else: else: