Merge branch 'yuanshao'

人脸识别/getface.py

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+# coding = utf-8
+# 圈出图片中所有的人脸
+import numpy as np
+import math
+import cv2
+import dlib
+
+path = '/Users/yanshao/Desktop/img/timg.jpeg'
+Model = '/Users/yanshao/dlib/shape_predictor_5_face_landmarks.dat'
+
+# 首先把图片转化为方形
+
+detector = dlib.get_frontal_face_detector()
+predictor = dlib.shape_predictor(Model)
+
+
+def preprocess():
+    image = cv2.imread(path)
+    height, width, chl = image.shape[0], image.shape[1], image.shape[2]
+    rec = int(max(height, width) * 1.5)
+    pic = np.zeros((rec, rec, chl), np.uint8)
+    baseh, basew = (rec - height) // 2, (rec - width) // 2
+    pic[baseh:height + baseh, basew:width + basew] = image
+    return pic, rec
+
+
+# 为了检测出图片中的所有人脸，我们每次把图片翻转45度
+def get_dist(point1, point2):
+    return math.sqrt((point1[0]-point2[0])*(point1[0]-point2[0]) +
+                     (point1[1]-point2[1])*(point1[1]-point2[1]))
+
+
+def get_pos(point, M):
+    return np.linalg.solve([[M[0][0], M[0][1]],
+                            [M[1][0], M[1][1]]],
+                            [point[0]-M[0][2], point[1]-M[1][2]]).astype(np.int32)
+
+
+pic, rec = preprocess()
+center = (rec//2,rec//2)
+list = []
+for ang in range(0, 8):
+    M = cv2.getRotationMatrix2D(center, 45*ang, 1)
+    pic2 = cv2.warpAffine(pic, M, (rec, rec))
+    dets = detector(pic2, 1)
+    print(len(dets))
+    for face in dets:
+        left, right, top, bot = face.left(), face.right(), face.top(), face.bottom()
+        LT, RB = get_pos((left, top), M), get_pos((right, bot), M)
+        list.append(((LT[0]+RB[0])//2, (LT[1]+RB[1])//2, (right-left)//2))
+
+    cv2.destroyAllWindows()
+
+length = len(list)
+for i in range(0, length):
+    flag = False
+    for j in range(0, i):
+        if get_dist(list[i], list[j]) < list[i][2]+list[j][2]:
+            flag = True
+    if not flag:
+        cv2.circle(pic, (list[i][0], list[i][1]), list[i][2], (0, 255, 0))
+
+cv2.imshow("img", pic)
+cv2.waitKey(0)
+cv2.destroyAllWindows()

数据库设计表

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+User表:
+UsedID(主键)
+UserName
+总金额
+用户头像
+
+寄送信息:(单个用户可以对应到多个地址)
+MessageId(主键)
+UserId(主键)
+Address
+tel-phone
+
+封面展示:(每一本书对应一张需要展示的图片)
+bookId(主键)
+Image
+
+Book表:
+BookId(主键)
+BookName
+价格
+Author
+引言
+大分类
+
+简介表:(反正简介不会超过太多张对吧)
+bookId(主键)
+引言(这样我们经过排序之后就可以展示书本简介)
+简介图片
+
+
+购物车:
+UserId(主键)
+BookId(主键)
+数量
+
+
+订单表:(我们甚至可以由这个计算出每本书销售数量)
+UserId(主键)
+MessageId(主键)
+BookId(主键)
+Statue：待付款,待发货，待收货，待评价，订单已经完成，退货中