python 处理excel 识别图片文字 转换成表格内容输出
pycharm idea 开发利器啊(主要为了进入活动)处理内容就是将图片生成文字将文字再处理成excel 这里都是代码。。需要会点的才会点。。好像很废话。那么识别文字如何做的呢。
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pycharm idea 开发利器啊(主要为了进入活动)
# This is a sample Python script.
import os
import re
import requests
# Press Shift+F10 to execute it or replace it with your code.
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
import urllib
import pytesseract
from PIL import Image
# 读写2003 excel
import xlrd
import xlwt
# 读写2007 excel
import openpyxl
def deal_space():
pass
def deal_excel():
parentPath = "txt\\final_text"
outPut = "新建 XLSX 工作表.xlsx"
wb = xlwt.Workbook()
for (root, dirs, files) in os.walk(parentPath):
for filename in files:
filename_full_path = os.path.join(root, filename)
print("filename_full_path " + filename_full_path)
sheet = wb.add_sheet(filename.replace(".txt", ""))
with open(filename_full_path, encoding="utf-8", mode="r") as f:
context = f.readlines()
value = []
value.append( ['序号', "单位名称", "资质类别"])
index = 0
for x in context:
text = x.replace("\n", "")
if text:
index = index + 1
value.append([index] + text.split("#"))
print(value)
for i in range(0, len(value)):
for j in range(0, len(value[i])):
print(value[i][j])
sheet.write(i, j, value[i][j])
# value = [["名称", "价格", "出版社", "语言"],
# ["如何高效读懂一本书", "22.3", "机械工业出版社", "中文"],
# ["暗时间", "32.4", "人民邮电出版社", "中文"],
# ["拆掉思维里的墙", "26.7", "机械工业出版社", "中文"]]
# continue
wb.save(outPut)
print("写入数据成功!")
pass
def main():
# 下载图片
# downloadPic()
# 将图片二进制程序化
# hex_pic()
# 识别图片存取到一个文件党章
# generate_text()
# 处理空格
# deal_space()
# 处理xml
deal_excel()
def hex_pic():
img = Image.open('pic/origin/02.jpg')
# 模式L”为灰色图像,它的每个像素用8个bit表示,0表示黑,255表示白,其他数字表示不同的灰度。
Img = img.convert('L')
Img.save("pic\\hex_pic\\02.jpg")
# # 自定义灰度界限,大于这个值为黑色,小于这个值为白色
# threshold = 200
#
# table = []
# for i in range(256):
# if i < threshold:
# table.append(0)
# else:
# table.append(1)
#
# # 图片二值化
# photo = Img.point(table, '1')
# photo.save("test2.png")
# # 识别图片内容
# import pytesseract
# img_path = 'test2.png'
#
# text = pytesseract.image_to_string(Image.open(img_path))
for (root, dirs, files) in os.walk("pic/origin"):
for filename in files:
filename_full_path = os.path.join(root, filename)
print("filename_full_path " + filename_full_path)
img = Image.open(filename_full_path)
# 模式L”为灰色图像,它的每个像素用8个bit表示,0表示黑,255表示白,其他数字表示不同的灰度。
Img = img.convert('L')
Img.save(filename_full_path.replace("hex_pic", "origin"))
# 根据图片生成每个text
def generate_text():
parent_path = "pic/origin/"
# 批量添加namespace|
# 列出windows目录下的所有文件和文件名
res = ""
for (root, dirs, files) in os.walk(parent_path):
for filename in files:
filename_full_path = os.path.join(root, filename)
print("filename_full_path " + filename_full_path)
im = Image.open(filename_full_path)
# 识别文字
# 识别文字,并指定语言
res = pytesseract.image_to_string(im, lang='chi_sim')
# 识别所有图片 认识
with open("txt\\hex_pic\\" + filename.replace(".jpg", ".txt"), encoding="utf-8", mode="w") as f:
f.write(res)
pass
# 步骤1 下载文件到本地
def download_pic():
url = "https://xxxx"
s = requests.Session()
context = s.get(url).text
reg = r'data-original=\"(.*?r.jpg)\"'
res = re.findall(reg, context)
print(res)
res = {}.fromkeys(res).keys()
print(len(res))
print(res)
path = "pic"
index = 0
for x in res:
index = index + 1
text = "0" + str(index) if index <= 9 else str(index)
urllib.request.urlretrieve(x, path + "\\" + text + ".jpg")
# Press the green button in the gutter to run the script.
if __name__ == '__main__':
main()
# See PyCharm help at https://www.jetbrains.com/help/pycharm/
处理内容就是将图片生成文字
将文字再处理成excel 这里都是代码。。需要会点的才会点。。好像很废话。
那么识别文字如何做的呢
用python识别图片
先下载tesseract
下载好了记住安装目录。然后把安装目录设置为环境变量
pip install --upgrade pip
pip install pytesseract
pip install pillow
安装目录里面有一个
tessdata
这个是存放语言识别文件的。
下载地址 :
https://raw.githubusercontent.com/tesseract-ocr/tessdata/4.00/chi_sim.traineddata
这个是中文简体。繁体也可以去下载这个
https://raw.githubusercontent.com/tesseract-ocr/tessdata/4.00/chi_tra.traineddata
下载好了丢进tessdata 即可
识别中文文字
im = Image.open(filename_full_path)
# 识别文字
# 识别文字,并指定语言
res = pytesseract.image_to_string(im, lang='chi_sim')
# 识别所有图片 认识
with open("txt\\hex_pic\\" + filename.replace(".jpg", ".txt"), encoding="utf-8", mode="w") as f:
f.write(res)
识别的结果如果不理想可以先将图片二进制化
img = Image.open(filename_full_path)
# 模式L”为灰色图像,它的每个像素用8个bit表示,0表示黑,255表示白,其他数字表示不同的灰度。
Img = img.convert('L')
Img.save(filename_full_path.replace("hex_pic", "origin"))
然后再次进行处理
parentPath = "txt\\final_text"
outPut = "新建 XLSX 工作表.xlsx"
wb = xlwt.Workbook()
for (root, dirs, files) in os.walk(parentPath):
for filename in files:
filename_full_path = os.path.join(root, filename)
print("filename_full_path " + filename_full_path)
sheet = wb.add_sheet(filename.replace(".txt", ""))
with open(filename_full_path, encoding="utf-8", mode="r") as f:
context = f.readlines()
value = []
value.append( ['序号', "单位名称", "资质类别"])
index = 0
for x in context:
text = x.replace("\n", "")
if text:
index = index + 1
value.append([index] + text.split("#"))
print(value)
for i in range(0, len(value)):
for j in range(0, len(value[i])):
print(value[i][j])
sheet.write(i, j, value[i][j])
# value = [["名称", "价格", "出版社", "语言"],
# ["如何高效读懂一本书", "22.3", "机械工业出版社", "中文"],
# ["暗时间", "32.4", "人民邮电出版社", "中文"],
# ["拆掉思维里的墙", "26.7", "机械工业出版社", "中文"]]
# continue
wb.save(outPut)
print("写入数据成功!")
处理后拿到文本再根据一定格式存好
文件名称就是我们的sheet名称
我们随意的造假数据
然后根据当前文本特点生成表格
最后 查看表格内容
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