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https://github.com/serengil/deepface.git
synced 2025-06-08 12:35:22 +00:00
common align procedure added for opencv and mtcnn
This commit is contained in:
Şefik Serangil
parent
394c34f470
commit
7f6d9075d1
@ -17,6 +17,7 @@ import subprocess
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import tensorflow as tf
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import keras
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import bz2
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from deepface.commons import distance
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def loadBase64Img(uri):
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encoded_data = uri.split(',')[1]
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@ -24,12 +25,6 @@ def loadBase64Img(uri):
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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return img
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def distance(a, b):
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x1 = a[0]; y1 = a[1]
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x2 = b[0]; y2 = b[1]
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return math.sqrt(((x2 - x1) * (x2 - x1)) + ((y2 - y1) * (y2 - y1)))
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def initializeFolder():
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home = str(Path.home())
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@ -309,6 +304,53 @@ def detect_face(img, detector_backend = 'opencv', grayscale = False, enforce_det
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return 0
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def alignment_procedure(img, left_eye, right_eye):
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#this function aligns given face in img based on left and right eye coordinates
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left_eye_x, left_eye_y = left_eye
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right_eye_x, right_eye_y = right_eye
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#-----------------------
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#find rotation direction
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if left_eye_y > right_eye_y:
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point_3rd = (right_eye_x, left_eye_y)
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direction = -1 #rotate same direction to clock
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else:
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point_3rd = (left_eye_x, right_eye_y)
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direction = 1 #rotate inverse direction of clock
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#-----------------------
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#find length of triangle edges
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a = distance.findEuclideanDistance(np.array(left_eye), np.array(point_3rd))
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b = distance.findEuclideanDistance(np.array(right_eye), np.array(point_3rd))
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c = distance.findEuclideanDistance(np.array(right_eye), np.array(left_eye))
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#-----------------------
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#apply cosine rule
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if b != 0 and c != 0: #this multiplication causes division by zero in cos_a calculation
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cos_a = (b*b + c*c - a*a)/(2*b*c)
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angle = np.arccos(cos_a) #angle in radian
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angle = (angle * 180) / math.pi #radian to degree
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#-----------------------
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#rotate base image
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if direction == -1:
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angle = 90 - angle
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img = Image.fromarray(img)
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img = np.array(img.rotate(direction * angle))
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#-----------------------
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return img #return img anyway
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def align_face(img, detector_backend = 'opencv'):
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home = str(Path.home())
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@ -336,7 +378,7 @@ def align_face(img, detector_backend = 'opencv'):
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df = pd.DataFrame(items, columns = ["length", "idx"]).sort_values(by=['length'], ascending=False)
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eyes = eyes[df.idx.values[0:2]]
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eyes = eyes[df.idx.values[0:2]] #eyes variable stores the largest 2 eye
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#-----------------------
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#decide left and right eye
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@ -351,51 +393,12 @@ def align_face(img, detector_backend = 'opencv'):
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#-----------------------
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#find center of eyes
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left_eye_center = (int(left_eye[0] + (left_eye[2] / 2)), int(left_eye[1] + (left_eye[3] / 2)))
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left_eye_x = left_eye_center[0]; left_eye_y = left_eye_center[1]
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left_eye = (int(left_eye[0] + (left_eye[2] / 2)), int(left_eye[1] + (left_eye[3] / 2)))
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right_eye = (int(right_eye[0] + (right_eye[2]/2)), int(right_eye[1] + (right_eye[3]/2)))
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right_eye_center = (int(right_eye[0] + (right_eye[2]/2)), int(right_eye[1] + (right_eye[3]/2)))
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right_eye_x = right_eye_center[0]; right_eye_y = right_eye_center[1]
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img = alignment_procedure(img, left_eye, right_eye)
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#-----------------------
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#find rotation direction
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if left_eye_y > right_eye_y:
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point_3rd = (right_eye_x, left_eye_y)
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direction = -1 #rotate same direction to clock
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else:
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point_3rd = (left_eye_x, right_eye_y)
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direction = 1 #rotate inverse direction of clock
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#-----------------------
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#find length of triangle edges
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a = distance(left_eye_center, point_3rd)
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b = distance(right_eye_center, point_3rd)
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c = distance(right_eye_center, left_eye_center)
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#-----------------------
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#apply cosine rule
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if b != 0 and c != 0: #this multiplication causes division by zero in cos_a calculation
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cos_a = (b*b + c*c - a*a)/(2*b*c)
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angle = np.arccos(cos_a) #angle in radian
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angle = (angle * 180) / math.pi #radian to degree
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#-----------------------
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#rotate base image
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if direction == -1:
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angle = 90 - angle
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img = Image.fromarray(img)
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img = np.array(img.rotate(direction * angle))
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return img
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else:
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return img
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return img #return img anyway
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elif detector_backend == 'dlib':
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@ -417,7 +420,7 @@ def align_face(img, detector_backend = 'opencv'):
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#------------------------------
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import dlib
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import dlib #this is not a must dependency in deepface
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detector = dlib.get_frontal_face_detector()
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sp = dlib.shape_predictor(home+"/.deepface/weights/shape_predictor_5_face_landmarks.dat")
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@ -427,10 +430,9 @@ def align_face(img, detector_backend = 'opencv'):
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if len(detections) > 0:
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detected_face = detections[0]
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img_shape = sp(img, detected_face)
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img_aligned = dlib.get_face_chip(img, img_shape)
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return img_aligned
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else:
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return img
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img = dlib.get_face_chip(img, img_shape, size = img.shape[0])
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return img #return img anyway
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elif detector_backend == 'mtcnn':
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from mtcnn import MTCNN
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@ -444,48 +446,9 @@ def align_face(img, detector_backend = 'opencv'):
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left_eye = keypoints["left_eye"]
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right_eye = keypoints["right_eye"]
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left_eye_x, left_eye_y = left_eye
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right_eye_x, right_eye_y = right_eye
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#-----------------------
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#find rotation direction
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img = alignment_procedure(img, left_eye, right_eye)
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if left_eye_y > right_eye_y:
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point_3rd = (right_eye_x, left_eye_y)
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direction = -1 #rotate same direction to clock
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else:
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point_3rd = (left_eye_x, right_eye_y)
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direction = 1 #rotate inverse direction of clock
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#-----------------------
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#find length of triangle edges
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a = distance(left_eye, point_3rd)
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b = distance(right_eye, point_3rd)
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c = distance(right_eye, left_eye)
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#-----------------------
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#apply cosine rule
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if b != 0 and c != 0: #this multiplication causes division by zero in cos_a calculation
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cos_a = (b*b + c*c - a*a)/(2*b*c)
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angle = np.arccos(cos_a) #angle in radian
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angle = (angle * 180) / math.pi #radian to degree
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#-----------------------
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#rotate base image
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if direction == -1:
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angle = 90 - angle
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img = Image.fromarray(img)
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img = np.array(img.rotate(direction * angle))
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return img #return img anyway
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else:
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return img
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return img #return img anyway
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def preprocess_face(img, target_size=(224, 224), grayscale = False, enforce_detection = True, detector_backend = 'opencv'):
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