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stream bug fixed

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This commit is contained in:
Şefik Serangil 2020-09-08 09:07:08 +03:00
parent 0bd219d9c2
commit a0c06a3792
2 changed files with 6 additions and 6 deletions
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4
deepface/commons/functions.py
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@ -456,8 +456,8 @@ def preprocess_face(img, target_size=(224, 224), grayscale = False, enforce_dete
#we will align base image instead of detected face not have black pixels
img = align_face(img = img, detector_backend = detector_backend)
img = detect_face(img = img, detector_backend = detector_backend, grayscale = grayscale, enforce_detection = False)
img = detect_face(img = img, detector_backend = detector_backend, grayscale = grayscale, enforce_detection = enforce_detection)
img = align_face(img = img, detector_backend = detector_backend)
#--------------------------

8
deepface/commons/realtime.py
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@ -112,7 +112,7 @@ def analysis(db_path, model_name, distance_metric, enable_face_analysis = True):
employee = employees[index]
pbar.set_description("Finding embedding for %s" % (employee.split("/")[-1]))
embedding = []
img = functions.preprocess_face(employee, (input_shape_y, input_shape_x))
img = functions.preprocess_face(img = employee, target_size = (input_shape_y, input_shape_x), enforce_detection = False)
img_representation = model.predict(img)[0,:]
embedding.append(employee)
@ -222,7 +222,7 @@ def analysis(db_path, model_name, distance_metric, enable_face_analysis = True):
if enable_face_analysis == True:
gray_img = functions.preprocess_face(custom_face, (48, 48), True)
gray_img = functions.preprocess_face(img = custom_face, target_size = (48, 48), grayscale = True, enforce_detection = False)
emotion_labels = ['Angry', 'Disgust', 'Fear', 'Happy', 'Sad', 'Surprise', 'Neutral']
emotion_predictions = emotion_model.predict(gray_img)[0,:]
sum_of_predictions = emotion_predictions.sum()
@ -300,7 +300,7 @@ def analysis(db_path, model_name, distance_metric, enable_face_analysis = True):
#-------------------------------
face_224 = functions.preprocess_face(custom_face, (224, 224), False)
face_224 = functions.preprocess_face(img = custom_face, target_size = (224, 224), grayscale = False, enforce_detection = False)
age_predictions = age_model.predict(face_224)[0,:]
apparent_age = Age.findApparentAge(age_predictions)
@ -355,7 +355,7 @@ def analysis(db_path, model_name, distance_metric, enable_face_analysis = True):
#-------------------------------
#face recognition
custom_face = functions.preprocess_face(custom_face, (input_shape_y, input_shape_x))
custom_face = functions.preprocess_face(img = custom_face, target_size = (input_shape_y, input_shape_x), enforce_detection = False)
#check preprocess_face function handled
if custom_face.shape[1:3] == input_shape: