百度飞桨(PaddlePaddle)是百度推出的一款深度学习平台,旨在为开发者提供强大的深度学习框架和工具。飞桨提供了包括OCR(光学字符识别)在内的多种功能,可以帮助开发者在各种应用中实现高效的文本识别。官网链接:https://www.paddlepaddle.org.cn/。
初次使用,安装:
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple paddlepaddle
验证安装,使用 python 进入 python 解释器,输入 import paddle ,再输入 paddle.utils.run_check()。
python
Python 3.8.10 (tags/v3.8.10:3d8993a, May 3 2021, 11:48:03) [MSC v.1928 64 bit (AMD64)] on win32
Type “help”, “copyright”, “credits” or “license” for more information.import paddle
paddle.utils.run_check()
Running verify PaddlePaddle program …
I0904 17:11:21.570567 15712 interpretercore.cc:237] New Executor is Running.
I0904 17:11:21.702833 15712 interpreter_util.cc:518] Standalone Executor is Used.
PaddlePaddle works well on 1 CPU.
PaddlePaddle is installed successfully! Let’s start deep learning with PaddlePaddle now.
飞桨文字识别开发套件PaddleOCR,旨在打造一套丰富、领先且实用的OCR工具库,开源了基于PP-OCR实用的超轻量中英文OCR模型、通用中英文OCR模型,以及德法日韩等多语言OCR模型。并提供上述模型训练方法和多种预测部署方式。同时开源文本风格数据合成工具Style-Text和半自动文本图像标注工具PPOCRLable。
飞桨OCR文字简明识别过程如下图所示。
如果你有企业中明确的 OCR 垂类应用需求,我们推荐你使用训压推一站式全流程高效率开发平台 PaddleX,助力 AI 技术快速落地。
首先,下载shapely安装包(地址:https://www.lfd.uci.edu/~gohlke/pythonlibs/),并安装。
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple e:\software\python\Shapely-1.8.2-cp38-cp38-win_amd64.whl
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple paddleocr
通用OCR文字识别,首个样例。
from paddleocr import PaddleOCR, draw_ocr
# Paddleocr目前支持的多语言语种可以通过修改lang参数进行切换
# 例如`ch`, `en`, `fr`, `german`, `korean`, `japan`
ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
img_path = './imgs/11.jpg'
result = ocr.ocr(img_path, cls=True)
for idx in range(len(result)):
res = result[idx]
for line in res:
print(line)
# 显示结果
from PIL import Image
result = result[0]
image = Image.open(img_path).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='./fonts/simfang.ttf')
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
我的python环境,供参考:
PP-Structure是一个基于PaddlePaddle的表格结构识别工具包,可以帮助开发者快速进行表格结构的识别和提取。
图表识别,输入图像如下图,带水印的网页表格:
官方示例代码:
import os
import cv2
from paddleocr import PPStructure,draw_structure_result,save_structure_res
table_engine = PPStructure(show_log=True)
save_folder = 'output'
img_path = 'img/12.jpg'
img = cv2.imread(img_path)
result = table_engine(img)
save_structure_res(result, save_folder,os.path.basename(img_path).split('.')[0])
for line in result:
line.pop('img')
print(line)
from PIL import Image
font_path = 'C:\Windows\Fonts\simfang.ttf' # PaddleOCR下提供字体包
image = Image.open(img_path).convert('RGB')
im_show = draw_structure_result(image, result,font_path=font_path)
im_show = Image.fromarray(im_show)
im_show.save('result2.jpg')
download https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar to
C:\Users\xiaoyw/.paddleocr/whl\table\ch_ppstructure_mobile_v2.0_SLANet_infer\ch_ppstructure_mobile_v2.0_SLANet_infer.tar
100%| 10.3M/10.3M [00:01<00:00, 6.69MiB/s]
download https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar to
C:\Users\xiaoyw/.paddleocr/whl\layout\picodet_lcnet_x1_0_fgd_layout_cdla_infer\picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar
100%|| 10.1M/10.1M [00:00<00:00, 10.2MiB/s]
参考:
VipSoft. 百度飞桨(PaddlePaddle) - PaddleHub OCR 文字识别简单使用. 博客园. 2023.05
汽车人. Pytorch 和 TensorFlow 和 PaddlePaddle 这三个框架有什么区别?. 知乎. 2022.08
https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/ppstructure/docs/quickstart.md
附件:
Package Version
------------------------- -----------
anyio 4.0.0
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
arrow 1.2.3
astor 0.8.1
asttokens 2.3.0
async-lru 2.0.4
attrdict 2.0.1
attrs 23.1.0
Babel 2.12.1
backcall 0.2.0
bce-python-sdk 0.8.90
beautifulsoup4 4.12.2
bleach 6.0.0
blinker 1.6.2
cachetools 5.3.1
certifi 2023.7.22
cffi 1.15.1
charset-normalizer 3.2.0
click 8.1.7
colorama 0.4.6
comm 0.1.4
contourpy 1.1.0
cssselect 1.2.0
cssutils 2.7.1
cycler 0.11.0
Cython 3.0.2
debugpy 1.6.7.post1
decorator 5.1.1
defusedxml 0.7.1
dnspython 2.4.2
et-xmlfile 1.1.0
exceptiongroup 1.1.3
executing 1.2.0
fastjsonschema 2.18.0
fire 0.5.0
flask 2.3.3
flask-babel 3.1.0
fonttools 4.42.1
fqdn 1.5.1
future 0.18.3
h11 0.14.0
httpcore 0.17.3
httpx 0.24.1
idna 3.4
imageio 2.31.3
imgaug 0.4.0
importlib-metadata 6.8.0
importlib-resources 6.0.1
ipykernel 6.25.1
ipython 8.12.2
ipython-genutils 0.2.0
ipywidgets 8.1.0
isoduration 20.11.0
itsdangerous 2.1.2
jedi 0.19.0
Jinja2 3.1.2
joblib 1.3.2
json5 0.9.14
jsonpointer 2.4
jsonschema 4.19.0
jsonschema-specifications 2023.7.1
kiwisolver 1.4.5
lazy-loader 0.3
lmdb 1.4.1
lxml 4.9.3
MarkupSafe 2.1.3
matplotlib 3.7.2
matplotlib-inline 0.1.6
mistune 3.0.1
nbclient 0.8.0
nbconvert 7.8.0
nbformat 5.9.2
nest-asyncio 1.5.7
networkx 3.1
notebook 7.0.3
notebook-shim 0.2.3
numpy 1.24.4
opencv-contrib-python 4.6.0.66
opencv-python 4.6.0.66
openpyxl 3.1.2
opt-einsum 3.3.0
overrides 7.4.0
packaging 23.1
paddle-bfloat 0.1.7
paddleocr 2.7.0.2
paddlepaddle 2.5.1
pandas 2.0.3
pandocfilters 1.5.0
parso 0.8.3
pdf2docx 0.5.6
pickleshare 0.7.5
Pillow 10.0.0
pip 21.1.1
pkgutil-resolve-name 1.3.10
platformdirs 3.10.0
premailer 3.10.0
prometheus-client 0.17.1
prompt-toolkit 3.0.39
protobuf 3.20.2
psutil 5.9.5
pure-eval 0.2.2
pyclipper 1.3.0.post4
pycparser 2.21
pycryptodome 3.18.0
Pygments 2.16.1
pymongo 4.5.0
PyMuPDF 1.20.2
pyparsing 3.0.9
python-dateutil 2.8.2
python-docx 0.8.11
python-json-logger 2.0.7
pytz 2023.3
PyWavelets 1.4.1
pywin32 306
pywinpty 2.0.11
PyYAML 6.0.1
pyzmq 25.1.1
qtconsole 5.4.4
QtPy 2.4.0
rapidfuzz 3.2.0
rarfile 4.0
referencing 0.30.2
requests 2.31.0
rfc3339-validator 0.1.4
rfc3986-validator 0.1.1
rpds-py 0.10.0
scikit-image 0.21.0
scikit-learn 1.3.0
scipy 1.10.1
Send2Trash 1.8.2
setuptools 56.0.0
Shapely 1.8.2
six 1.16.0
sniffio 1.3.0
soupsieve 2.5
stack-data 0.6.2
termcolor 2.3.0
terminado 0.17.1
threadpoolctl 3.2.0
tifffile 2023.7.10
tinycss2 1.2.1
tomli 2.0.1
tornado 6.3.3
tqdm 4.66.1
traitlets 5.9.0
typing-extensions 4.7.1
tzdata 2023.3
uri-template 1.3.0
urllib3 2.0.4
visualdl 2.5.3
wcwidth 0.2.6
webcolors 1.13
webencodings 0.5.1
websocket-client 1.6.2
werkzeug 2.3.7
widgetsnbextension 4.0.8
zipp 3.16.2