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n_pre.py
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'''
主函数，识别图片的同时，将识别出的文字分类，看是否属于店铺名
'''
from paddleocr import PaddleOCR
from lstm import test
import os
import re
from paddleocr import PaddleOCR
from tools.infer.utility import draw_ocr
from PIL import Image
import pandas as pd
import wx
import wx.xrc
# from miaoshu import miaoshu_test
# 图形开始
app = wx.App()
window = wx.Frame(None, title = u"实时识别状态展示", size = (969,150),style = wx.DEFAULT_FRAME_STYLE|wx.TAB_TRAVERSAL)
window.SetSizeHints( wx.DefaultSize, wx.DefaultSize )
gbSizer3 = wx.GridBagSizer( 0, 0 )
gbSizer3.SetFlexibleDirection( wx.BOTH )
gbSizer3.SetNonFlexibleGrowMode( wx.FLEX_GROWMODE_SPECIFIED )
window.m_staticText10 = wx.StaticText( window, wx.ID_ANY, u"正在识别：", wx.DefaultPosition, wx.DefaultSize, 0 )
window.m_staticText10.Wrap( -1 )
gbSizer3.Add( window.m_staticText10, wx.GBPosition( 0, 0 ), wx.GBSpan( 1, 1 ), wx.ALL, 5 )
window.m_staticText11 = wx.StaticText( window, wx.ID_ANY, u"图片名字", wx.DefaultPosition, wx.DefaultSize, 0 )
window.m_staticText11.Wrap( -1 )
window.m_staticText11.SetForegroundColour( wx.Colour( 255, 0, 0 ) )
window.m_staticText11.SetMinSize( wx.Size( 800,30 ) )
gbSizer3.Add( window.m_staticText11, wx.GBPosition( 0, 1 ), wx.GBSpan( 1, 1 ), wx.ALL, 5 )
window.m_staticText12 = wx.StaticText( window, wx.ID_ANY, u"进度：", wx.DefaultPosition, wx.DefaultSize, 0 )
window.m_staticText12.Wrap( -1 )
gbSizer3.Add( window.m_staticText12, wx.GBPosition( 1, 0 ), wx.GBSpan( 1, 1 ), wx.ALL, 5 )
window.m_staticText13 = wx.StaticText( window, wx.ID_ANY, u"正在识别的图片：", wx.DefaultPosition, wx.DefaultSize, 0 )
window.m_staticText13.Wrap( -1 )
gbSizer3.Add( window.m_staticText13, wx.GBPosition( 2, 0 ), wx.GBSpan( 1, 1 ), wx.ALL, 5 )
window.m_gauge1 = wx.Gauge( window, wx.ID_ANY, 100, wx.DefaultPosition, wx.DefaultSize, wx.GA_HORIZONTAL )
window.m_gauge1.SetValue( 0 )
window.m_gauge1.SetMinSize( wx.Size( 800,-1 ) )
gbSizer3.Add( window.m_gauge1, wx.GBPosition( 1, 1 ), wx.GBSpan( 1, 1 ), wx.ALL, 5 )
window.SetSizer( gbSizer3 )
window.Layout()
window.Centre( wx.BOTH )
#图形结束
def pre_save(img_path,save_path,csv_path,m_filePicker11=None):
ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
i = 0
names =[]
#abels = []
imgs=[]
one_qian_pic_path = ""
one_hou_pic_path = ""
#存放所有的图片路径
n_qian_pic_path = []
n_hou_pic_path = []
j=0
stR = ""
# 启动窗口
window.Show(True)
jindu_len = len(os.listdir(img_path)) + 2
print("共："+str(jindu_len-2))
window.m_gauge1.SetRange(jindu_len)
dangqian_jindu = 1
n=0
for img in os.listdir(img_path):
n+=1
window.m_staticText11.SetLabel("正在识别："+img_path+'/'+img)
print("当前正在识别"+str(dangqian_jindu)+"-->"+"正在识别："+img_path+'/'+img)
window.m_gauge1.SetValue(dangqian_jindu)
dangqian_jindu = dangqian_jindu + 1
#动态显示进度条
if dangqian_jindu==jindu_len:
window.m_gauge1.SetValue(dangqian_jindu)
print(img_path+'/'+img)
i+=1
result = ocr.ocr(img_path+'/'+img, cls=True)
image = Image.open(img_path+'/'+img).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
im_show = draw_ocr(image, boxes, txts, scores, font_path='/doc/simfang.ttf')
im_show = Image.fromarray(im_show)
# im_show.show()
# im_show.save是保存识别后的图片
sp = save_path+"/"+img
im_show.save(sp)
print("图片保存的位置："+sp)
#存储所有的图片路径
n_qian_pic_path.append(img_path+'/'+img)
n_hou_pic_path.append(save_path+"/"+img)
if j==0:
one_hou_pic_path = save_path+"/"+img
one_qian_pic_path = img_path+'/'+img
j = j + 1
if str(result) == "None":
continue
for line in result:
texts = line[1][0]
if texts == "":
continue
if texts in names:
continue
texts = re.findall('[\u4e00-\u9fa50-9]+', texts, re.S) # 只要字符串中的中文，字母，数字
texts = "".join(texts)
label = test.pre(texts)
if len(texts) < 3:
label = "非商铺名"
if label == "商铺名":
#print(texts, " ：", label)
stR = stR + str(img) + ":" + str(texts) + "\n"
imgs.append(img)
#labels.append(label)
names.append(texts)
dataframe = pd.DataFrame({'图片名': imgs, '商铺名称': names})
if csv_path[-3:]=="xls":
dataframe.to_excel(csv_path, index=True)
elif csv_path[-3:]=="csv":
dataframe.to_csv(csv_path, index=True,sep=',')
else:
print("请选择csv或者xls文件")
stR = stR + "\n" + "共识别了" + str(n) + "张图片" + "\n" + "共检测出商铺名" + str(i) + "个\n"
dangqian_jindu = dangqian_jindu + 1
window.m_gauge1.SetValue(dangqian_jindu)
print("当前正在识别" + str(dangqian_jindu))
print(i)
return stR,one_qian_pic_path,one_hou_pic_path,n_qian_pic_path,n_hou_pic_path
# # # # 分别问图片的地址和保存scv数据文件的地址
# img_path = r'img\new_img'
# save_path = r"F:\chrome\zrbdata\data\result"
# csv_path = r'F:\chrome\zrbdata\data\result5.csv'
# pre_save(img_path,save_path,csv_path)