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align.py

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+import cv2
+import numpy as np
+from net.mtcnn import mtcnn
+import utils.utils as utils
+from net.inception import InceptionResNetV1
+
+
+img = cv2.imread('face_dataset/timg.jpg')
+
+# 创建mtcnn对象
+mtcnn_model = mtcnn()
+# 门限函数
+threshold = [0.5,0.7,0.9]
+# 检测人脸
+rectangles = mtcnn_model.detectFace(img, threshold)
+
+draw = img.copy()
+# 转化成正方形
+rectangles = utils.rect2square(np.array(rectangles))
+
+# 载入facenet
+facenet_model = InceptionResNetV1()
+# model.summary()
+model_path = './model_data/facenet_keras.h5'
+facenet_model.load_weights(model_path)
+
+
+for rectangle in rectangles:
+    if rectangle is not None:
+        landmark = (np.reshape(rectangle[5:15],(5,2)) - np.array([int(rectangle[0]),int(rectangle[1])]))/(rectangle[3]-rectangle[1])*160
+
+        crop_img = img[int(rectangle[1]):int(rectangle[3]), int(rectangle[0]):int(rectangle[2])]
+
+        crop_img = cv2.resize(crop_img,(160,160))
+        cv2.imshow("before",crop_img)
+        new_img,_ = utils.Alignment_1(crop_img,landmark)
+        cv2.imshow("two eyes",new_img)
+
+        # std_landmark = np.array([[54.80897114,59.00365493],
+        #                         [112.01078961,55.16622207],
+        #                         [86.90572522,91.41657571],
+        #                         [55.78746897,114.90062758],
+        #                         [113.15320624,111.08135986]])
+        # crop_img = img[int(rectangle[1]):int(rectangle[3]), int(rectangle[0]):int(rectangle[2])]
+        # crop_img = cv2.resize(crop_img,(160,160))
+        # new_img,_ = utils.Alignment_2(crop_img,std_landmark,landmark)
+        # cv2.imshow("affine",new_img)    
+        new_img = np.expand_dims(new_img,0)
+        feature1 = utils.calc_128_vec(facenet_model,new_img)
+
+cv2.waitKey(0)