def count_1():
    # cap = cv2.VideoCapture('http://192.168.1.104:8080/shot.jpg')
    
    型号 = v4.get()

    reta = os.path.isfile(r"./imgs/" + 型号 + 'temp.jpg')
    if not reta: 
        a = showinfo(title="样本确认", message="没有样本,请先登录!")
        cv2.destroyAllWindows()
        return()
    
    img1 = cv2.imread(r"./imgs/" + 型号 + 'temp.jpg',0)

    config = {'host':'127.0.0.1',
            'user':'******',
            'password':'******',
            'port':'3306',
            'database':'test',
            'charset':'utf8'
            }
    try:
        conn = mysql.connector.Connect(**config)
    except mysql.connector.Error as e:
        print('connect fails!{}'.format(e))

    cursor = conn.cursor()
#查
    try:
        sql = "SELECT * FROM  prov WHERE XH = %s" 
        cursor.execute(sql,(型号,))
        sel_data = cursor.fetchone()
        print(sel_data)
    except mysql.connector.Error as e:
        print('query error!{}'.format(e))
    finally:
        cursor.close()
        conn.close()

    cv2.namedWindow("image")
    try:
        w,h,threshold = sel_data[1],sel_data[2],sel_data[3]
    except:
        w = img1.shape[1]
        h = img1.shape[0]
        threshold = 69#0.78#0.80 #0.63
    if w < img1.shape[1] or  h < img1.shape[0]:
        w = img1.shape[1]
        h = img1.shape[0]
        threshold = 69#0.78#0.80 #0.63

        
    cv2.createTrackbar('w','image',w,255,nothing)
    cv2.createTrackbar('h','image',h,255,nothing)
    cv2.createTrackbar('threshold','image',threshold,100,nothing)

    cap = cv2.VideoCapture(0)
    i=0
    while(1):
        ret,image1 = cap.read()
        i += 1
        if i == 20:
            break
    cap.release()

    while(1):
            
        w = cv2.getTrackbarPos('w','image')
        h = cv2.getTrackbarPos('h','image')
        threshold = cv2.getTrackbarPos('threshold','image')/100

        if img1.shape[1] > 1.1*w or img1.shape[0] > 1.1*h:
            a = showinfo(title="w|h确认", message="w|h数值过小,请再试一次!")
            cv2.destroyAllWindows()
            break
        
        img = cv2.resize(image1,(800,600),interpolation = cv2.INTER_CUBIC)

        rectangles = []
        counter = 1
        scaleFactor =2#1.25
        scale = 1
        font = cv2.FONT_HERSHEY_PLAIN

        #寻找roi轮廓并作形状比较,<0.1 填充矩形	
        for resized in pyramid(img,scaleFactor):
            scale = float(img.shape[1]) / float(resized.shape[1])
            for (x,y,roi) in sliding_window(resized,20,(w,h)):

                if roi.shape[1] != w or roi.shape[0] != h:
                    #print("here")
                    continue

                try:

                    img2 = cv2.cvtColor(roi,cv2.COLOR_BGR2GRAY)
                    ret = cv2.matchTemplate(img2,img1,cv2.TM_CCOEFF_NORMED)
                    # 3.这边是Python/Numpy的知识,后面解释
                    loc = np.where(ret >= threshold)  # 匹配程度大于%80的坐标y,x
                            
                    for pt in zip(*loc[::-1]):  # *号表示可选参数
                        rx,ry,rx2,ry2 = int(x*scale),int(y*scale),int((x+w)*scale),int((y+h)*scale)
                        rectangles.append([rx,ry,rx2,ry2,(ret[pt[0],pt[1]])])

                except:
                    pass
                
                counter += 1

        windows = np.array(rectangles)

        boxes = nms(windows,1)
        if len(boxes) > 0:
            a = boxes.tolist()
            c = [] 
            for i in a: 
                if i not in c: 
                    c.append(i) 
            a = c
        else:
            a = [] 

        for (x,y,x2,y2,score) in a:
            cv2.rectangle(img,(int(x),int(y)),(int(x2),int(y2)),(0,0,255),1)
            cv2.putText(img,"%f"%score,(int(x),int(y)),font,1,(0,0,255))
        v2.set(len(a))

        cv2.imshow("image",img)
        q = cv2.waitKey(50) & 0xff 
        
        if q == 13: # Enter
            #name = v5.get()+v4.get()+'.jpg'
            cv2.imwrite("./dinDan/temp.jpg",img)

            config = {'host':'127.0.0.1',
                    'user':'******',
                    'password':'******',
                    'port':'3306',
                    'database':'test',
                    'charset':'utf8'
                    }
            型号 = v4.get()
            try:
                conn = mysql.connector.Connect(**config)
            except mysql.connector.Error as e:
                print('connect fails!{}'.format(e))

            cursor = conn.cursor()

            #改
            try:
                sql = "Update prov Set XH = %s , w = %s ,h = %s ,threshold = %s Where XH = %s"
                cursor.execute(sql,(型号,w,h,int(threshold*100),型号))
            except mysql.connector.Error as e:
                print('Update error!{}'.format(e))

            finally:
                conn.commit()
                cursor.close()
                conn.close()



            break

    cv2.destroyAllWindows()
def count_1():
    #global ret
    # cap = cv2.VideoCapture('http://192.168.1.104:8080/shot.jpg')

    型号 = v4.get()

    reta = os.path.isfile(r"./imgs/" + 型号 + 'temp.jpg')
    if not reta:
        a = showinfo(title="样本确认", message="没有样本,请先登录!")
        cv2.destroyAllWindows()
        return ()

    img1 = cv2.imread(r"./imgs/" + 型号 + 'temp.jpg', 0)

    pathfile = r'dataBase/test.mdb'
    tablename = r'prov'
    conn = mdb_conn(pathfile)
    cur = conn.cursor()

    #查
    sql = "SELECT * FROM " + tablename + " where 型号 = '" + 型号 + "'"
    sel_data = mdb_sel(cur, sql)

    cv2.namedWindow("image")
    try:
        w, h, threshold = sel_data[0][1], sel_data[0][2], sel_data[0][3]
    except:
        w = img1.shape[1]
        h = img1.shape[0]
        threshold = 69  #0.78#0.80 #0.63
    if w < img1.shape[1] or h < img1.shape[0]:
        w = img1.shape[1]
        h = img1.shape[0]
        threshold = 69  #0.78#0.80 #0.63

    cv2.createTrackbar('w', 'image', w, 255, nothing)
    cv2.createTrackbar('h', 'image', h, 255, nothing)
    cv2.createTrackbar('threshold', 'image', threshold, 100, nothing)

    cap = cv2.VideoCapture(1)
    i = 0
    while (1):
        ret, image1 = cap.read()
        i += 1
        if i == 10:
            break
    cap.release()

    while (1):

        w = cv2.getTrackbarPos('w', 'image')
        h = cv2.getTrackbarPos('h', 'image')
        threshold = cv2.getTrackbarPos('threshold', 'image') / 100

        if img1.shape[1] > 1.1 * w or img1.shape[0] > 1.1 * h:
            a = showinfo(title="w|h确认", message="w|h数值过小,请再试一次!")
            cv2.destroyAllWindows()
            break

        img = cv2.resize(image1, (800, 600), interpolation=cv2.INTER_CUBIC)

        rectangles = []
        counter = 1
        scaleFactor = 2  #1.25
        scale = 1
        font = cv2.FONT_HERSHEY_PLAIN

        #寻找roi轮廓并作形状比较,<0.1 填充矩形
        for resized in pyramid(img, scaleFactor):
            scale = float(img.shape[1]) / float(resized.shape[1])
            for (x, y, roi) in sliding_window(resized, 20, (w, h)):

                if roi.shape[1] != w or roi.shape[0] != h:
                    #print("here")
                    continue

                try:

                    img2 = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
                    ret = cv2.matchTemplate(img2, img1, cv2.TM_CCOEFF_NORMED)
                    # 3.这边是Python/Numpy的知识,后面解释
                    loc = np.where(ret >= threshold)  # 匹配程度大于%80的坐标y,x

                    for pt in zip(*loc[::-1]):  # *号表示可选参数
                        rx, ry, rx2, ry2 = int(x * scale), int(y * scale), int(
                            (x + w) * scale), int((y + h) * scale)
                        rectangles.append(
                            [rx, ry, rx2, ry2, (ret[pt[0], pt[1]])])

                except:
                    pass

                counter += 1

        windows = np.array(rectangles)

        boxes = nms(windows, 1)
        if len(boxes) > 0:
            a = boxes.tolist()
            c = []
            for i in a:
                if i not in c:
                    c.append(i)
            a = c
        else:
            a = []

        for (x, y, x2, y2, score) in a:
            cv2.rectangle(img, (int(x), int(y)), (int(x2), int(y2)),
                          (0, 0, 255), 1)
            cv2.putText(img, "%f" % score, (int(x), int(y)), font, 1,
                        (0, 0, 255))
        v2.set(len(a))

        cv2.imshow("image", img)
        q = cv2.waitKey(50) & 0xff
        if q == 13:  # Enter

            #增
            sql = "Insert Into " + tablename + " Values ('" + 型号 + "', " + str(
                w) + ", " + str(h) + ", " + str(threshold * 100) + ")"
            print(sql)
            if mdb_add(conn, cur, sql):
                print("插入成功!")
            else:
                print("插入失败!")
                #改
                sql = "Update " + tablename + " Set 型号 = '" + 型号 + "', w = " + str(
                    w) + ", threshold = " + str(
                        threshold *
                        100) + ", h = " + str(h) + " where 型号 = '" + 型号 + "'"
                if mdb_modi(conn, cur, sql):
                    print("修改成功!")
                else:
                    print("修改失败!")
            cur.close()  #关闭游标
            conn.close()  #关闭数据库连接
            break
    cv2.destroyAllWindows()
while(1):
	
	w = cv2.getTrackbarPos('w','image')
	h = cv2.getTrackbarPos('h','image')
	#w,h = img1.shape[:2]

	img = cv2.imread(test_image)

	rectangles = []
	counter = 1
	scaleFactor =2#1.25
	scale = 1
	font = cv2.FONT_HERSHEY_PLAIN

	#寻找roi轮廓并作形状比较,<0.1 填充矩形
	for resized in pyramid(img,scaleFactor):
		scale = float(img.shape[1]) / float(resized.shape[1])
		for (x,y,roi) in sliding_window(resized,20,(w,h)):
			if roi.shape[1] != w or roi.shape[0] != h:
				continue

			try:
				'''
				'''
				img2 = cv2.cvtColor(roi,cv2.COLOR_BGR2GRAY)
			
				ret = cv2.matchTemplate(img2,img1,cv2.TM_CCOEFF_NORMED)
				'''
				for score1 in ret:
					for score in score1:
						print(score)
img_path = "/home/dvaliu/Downloads/CarData/TestImages/test-10.pgm"

svm, extractor = car_detector()
detect = cv2.xfeatures2d.SIFT_create()

w, h = 100, 40
img = cv2.imread(img_path)
#img = cv2.imread(test_image)

rectangles = []
counter = 1
scaleFactor = 1.25
scale = 1
font = cv2.FONT_HERSHEY_PLAIN

for resized in pyramid(img, scaleFactor):
  scale = float(img.shape[1]) / float(resized.shape[1])
  for (x, y, roi) in sliding_window(resized, 20, (100, 40)):
    if roi.shape[1] != w or roi.shape[0] != h:
      continue

    try:
      bf = bow_features(roi, extractor, detect)
      _, result = svm.predict(bf)
      a, res = svm.predict(bf, flags=cv2.ml.STAT_MODEL_RAW_OUTPUT | cv2.ml.STAT_MODEL_UPDATE_MODEL)
      print "Class: %d, Score: %f, a: %s" % (result[0][0], res[0][0], res)
      score = res[0][0]
      if result[0][0] == 1:
        if score < -1.0:
          rx, ry, rx2, ry2 = int(x * scale), int(y * scale), int((x+w) * scale), int((y+h) * scale)
          rectangles.append([rx, ry, rx2, ry2, abs(score)])