用excel中的数据进行svr预测

import cv2
import numpy as np
import xlrd

def LoadPredictDataFromExcel():
    #文件位置
    ExcelFile=xlrd.open_workbook(r'..\0221_To_Teves训练数据.xlsx')
#获取目标EXCEL文件sheet名
    print (ExcelFile.sheet_names())

    sheet = ExcelFile.sheet_by_name('Sheet1')
#打印sheet的名称，行数，列数
    print (sheet.name,sheet.nrows,sheet.ncols)
#获取整行或者整列的值
    BackgroundDist = sheet.col_values(5)

    ForegroundDist = sheet.col_values(1)

    ForegroundArea = sheet.col_values(2)

    offset = sheet.col_values(3)

    BackgroundDist.pop(0)

    ForegroundDist.pop(0)

    ForegroundArea.pop(0)

    offset.pop(0)

    data = np.vstack((BackgroundDist, ForegroundDist, ForegroundArea))

    data = data.transpose()

    data = np.array(data,dtype='float32')

return data, offset

if __name__ == '__main__':
    data, offset  = LoadPredictDataFromExcel()

    SVR = cv2.ml.SVM_load('SVRModel.xml')#('NearModelPara.xml')

    result = SVR.predict(data)


    result = result[1].ravel()

    result = result.tolist()
print(result)
print(offset)
for i in range(len(result)):
        for j in range(len(offset)):
            flag = 0
            if offset[j] == result[i]:
                flag = 1
                break
        if flag == 0:
            print(result[i])