import os
########################文字检测########################
##文字检测引擎 
pwd = os.getcwd()
opencvFlag = 'keras' ##keras,opencv,darknet，模型性能 keras>darknet>opencv
IMGSIZE = (608,608)## yolo3 输入图像尺寸
## keras 版本anchors
keras_anchors = '8,11, 8,16, 8,23, 8,33, 8,48, 8,97, 8,139, 8,198, 8,283'
class_names = ['none','text',]
kerasTextModel=os.path.join(pwd,"models","text.h5")##keras版本模型权重文件

############## darknet yolo  ##############
darknetRoot = os.path.join(os.path.curdir,"darknet")## yolo 安装目录
yoloCfg     = os.path.join(pwd,"models","text.cfg")
yoloWeights = os.path.join(pwd,"models","text.weights")
yoloData    = os.path.join(pwd,"models","text.data")
############## darknet yolo  ##############

########################文字检测########################

## GPU选择及启动GPU序号
GPU = True##OCR 是否启用GPU
GPUID=0##调用GPU序号

## nms选择,支持cython,gpu,python
nmsFlag='gpu'## cython/gpu/python ##容错性 优先启动GPU，其次是cpython 最后是python
if not GPU:
    nmsFlag='cython'


##vgg文字方向检测模型
DETECTANGLE=True##是否进行文字方向检测
AngleModelPb = os.path.join(pwd,"models","Angle-model.pb")
AngleModelPbtxt = os.path.join(pwd,"models","Angle-model.pbtxt")


######################OCR模型######################
##是否启用LSTM crnn模型
##OCR模型是否调用LSTM层
LSTMFLAG = True
##模型选择 True:中英文模型 False:英文模型
ocrFlag = 'torch'##ocr模型 支持 keras  torch版本
chinsesModel = True
ocrModelKeras = os.path.join(pwd,"models","ocr-dense-keras.h5")##keras版本OCR，暂时支持dense
if chinsesModel:
    if LSTMFLAG:
        ocrModel  = os.path.join(pwd,"models","ocr-lstm.pth")
    else:
        ocrModel = os.path.join(pwd,"models","ocr-dense.pth")
else:
        ##纯英文模型
        LSTMFLAG=True
        ocrModel = os.path.join(pwd,"models","ocr-english.pth")
######################OCR模型######################