1， 部署开发环境
(ppoc) H:\work\daodan_move\PaddleOCR-main>pip list
Package Version
------------------------- -----------
aiofiles 24.1.0
aiohappyeyeballs 2.6.1
aiohttp 3.11.18
aiosignal 1.3.2
albucore 0.0.13
albumentations 1.4.10
altgraph 0.17.4
annotated-types 0.7.0
anyio 4.9.0
astor 0.8.1
async-timeout 4.0.3
attrs 25.3.0
backoff 2.2.1
beautifulsoup4 4.13.4
cachetools 5.5.2
certifi 2025.1.31
cffi 1.17.1
chardet 5.2.0
charset-normalizer 3.4.2
chinese_calendar 1.10.0
click 8.2.1
colorama 0.4.6
colorlog 6.9.0
contourpy 1.3.2
cryptography 45.0.2
cssselect 1.3.0
cssutils 2.11.1
cycler 0.12.1
Cython 3.1.1
dataclasses-json 0.6.7
decorator 5.2.1
decord 0.6.0
distro 1.9.0
emoji 2.14.1
et_xmlfile 2.0.0
exceptiongroup 1.2.2
faiss-cpu 1.8.0.post1
filelock 3.18.0
filetype 1.2.0
fire 0.7.0
fonttools 4.58.0
frozenlist 1.6.0
fsspec 2025.5.0
ftfy 6.3.1
GPUtil 1.4.0
greenlet 3.2.2
h11 0.14.0
html5lib 1.1
httpcore 1.0.8
httpx 0.28.1
huggingface-hub 0.31.4
idna 3.10
imageio 2.37.0
imagesize 1.4.1
imgaug 0.4.0
jieba 0.42.1
Jinja2 3.1.6
jiter 0.10.0
joblib 1.5.0
jsonpatch 1.33
jsonpointer 3.0.0
kiwisolver 1.4.8
langchain 0.2.17
langchain-community 0.2.17
langchain-core 0.2.43
langchain-openai 0.1.25
langchain-text-splitters 0.2.4
langdetect 1.0.9
langsmith 0.1.147
lazy_loader 0.4
lmdb 1.6.2
lxml 5.4.0
MarkupSafe 3.0.2
marshmallow 3.26.1
matplotlib 3.10.3
more-itertools 10.7.0
multidict 6.4.4
mypy_extensions 1.1.0
nest-asyncio 1.6.0
networkx 3.4.2
nltk 3.9.1
numpy 1.24.4
nvidia-cublas-cu11 11.11.3.6
nvidia-cuda-nvrtc-cu11 11.8.89
nvidia-cuda-runtime-cu11 11.8.89
nvidia-cudnn-cu11 8.9.4.19
nvidia-cufft-cu11 10.9.0.58
nvidia-curand-cu11 10.3.0.86
nvidia-cusolver-cu11 11.4.1.48
nvidia-cusparse-cu11 11.7.5.86
olefile 0.47
openai 1.63.2
opencv-contrib-python 4.10.0.84
opencv-python 4.5.5.64
opencv-python-headless 4.10.0.84
openpyxl 3.1.5
opt-einsum 3.3.0
orjson 3.10.18
packaging 24.2
paddleocr 2.9.1
paddlepaddle-gpu 3.0.0rc0
paddlex 3.0.0rc0
pandas 2.2.3
Parsley 1.3
pefile 2023.2.7
pillow 11.1.0
pip 25.1.1
premailer 3.10.0
prettytable 3.16.0
propcache 0.3.1
protobuf 6.30.2
psutil 7.0.0
py-cpuinfo 9.0.0
pyclipper 1.3.0.post6
pycocotools 2.0.8
pycparser 2.22
pydantic 2.11.5
pydantic_core 2.33.2
pyinstaller 6.13.0
pyinstaller-hooks-contrib 2025.4
PyMuPDF 1.26.0
pyparsing 3.2.3
pypdf 5.5.0
pyquaternion 0.9.9
python-dateutil 2.9.0.post0
python-docx 1.1.2
python-iso639 2025.2.18
python-magic 0.4.27
python-oxmsg 0.0.2
pytz 2025.2
pywin32-ctypes 0.2.3
PyYAML 6.0.2
RapidFuzz 3.13.0
regex 2024.11.6
requests 2.32.3
requests-toolbelt 1.0.0
ruamel.yaml 0.18.10
ruamel.yaml.clib 0.2.12
safetensors 0.5.3
scikit-image 0.25.2
scikit-learn 1.6.1
scipy 1.15.3
sentencepiece 0.2.0
setuptools 80.8.0
shapely 2.1.1
six 1.17.0
sniffio 1.3.1
soundfile 0.13.1
soupsieve 2.7
SQLAlchemy 2.0.41
tenacity 8.5.0
termcolor 3.1.0
threadpoolctl 3.6.0
tifffile 2025.5.10
tiktoken 0.9.0
tokenizers 0.19.1
tomli 2.2.1
tqdm 4.67.1
transformers 4.40.0
typing_extensions 4.13.2
typing-inspect 0.9.0
typing-inspection 0.4.1
tzdata 2025.2
ujson 5.10.0
unstructured 0.17.2
unstructured-client 0.35.0
urllib3 2.4.0
wcwidth 0.2.13
webencodings 0.5.1
wheel 0.45.1
wrapt 1.17.2
yarl 1.20.0
(ppoc) H:\work\daodan_move\PaddleOCR-main>2，准备代码
91.py
from paddleocr import PaddleOCR
# 初始化 PaddleOCR 实例
# ocr = PaddleOCR(
# use_doc_orientation_classify=False,
# use_doc_unwarping=False,
# use_textline_orientation=False)
# # 对示例图像执行 OCR 推理
# result = ocr.predict(
# input="https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_002.png")
# # 可视化结果并保存 json 结果
# for res in result:
# res.print()
# res.save_to_img("output")
# res.save_to_json("output")
from paddleocr import PaddleOCR
import os
import time
ocr = PaddleOCR(use_angle_cls=False, lang="ch",device='gpu:0',
det_model_dir=r"./inference/hx_mobile_det",
rec_model_dir=r".inference/hx_mobile_rec") # need to run only once to download and load model into memory
# img_path = './imgs/11.jpg'
datapath=r"./data/data2"
datalist=os.listdir(datapath)
for itimg in datalist:
imgpath=os.path.join(datapath,itimg)
start=time.time()
result = ocr.ocr(imgpath, cls=False)
end=time.time()
print(result)
# print("22222222222222222222",end-start)
print(f"Program execution time: {end-start} seconds")
# for idx in range(len(result)):
# res = result[idx]
# for line in res:
# print(line)
# det_model_dir=, cls_model_dir=r"./.paddleocr/whl\cls\ch_ppocr_mobile_v2.0_cls_infer", rec_model_dir=r"./.paddleocr/whl\rec\ch\ch_PP-OCRv4_rec_infer"3,准备91.spec文件
# -*- mode: python ; coding: utf-8 -*-
block_cipher = None
a = Analysis(['91.py'],
pathex=['H:\\work\\anaconda3\\envs\\ppoc\\Lib\\site-packages\\paddleocr', 'H:\\work\\anaconda3\\envs\\ppoc\\Lib\\site-packages\\paddle\\libs'],
binaries=[('H:\\work\\anaconda3\\envs\\ppoc\\Lib\\site-packages\\paddle\\libs', '.')],
datas=[],
hiddenimports=[],
hookspath=['.'],
runtime_hooks=[],
excludes=['matplotlib'],
win_no_prefer_redirects=False,
win_private_assemblies=False,
cipher=block_cipher,
noarchive=False)
pyz = PYZ(a.pure, a.zipped_data,
cipher=block_cipher)
exe = EXE(pyz,
a.scripts,
[],
exclude_binaries=True,
name='91',
debug=False,
bootloader_ignore_signals=False,
strip=False,
upx=True,
console=True)
coll = COLLECT(exe,
a.binaries,
a.zipfiles,
a.datas,
strip=False,
upx=True,
upx_exclude=[],
name='91')4，运行
pyinstaller -y 91.spec5,复制文件
复制完成后如下图所示：
a，将.inference复制到91.exe同目录下；
b，将.inference复制到91.exe同目录下；
c,将data图片数据复制到91.exe同目录下；
e,将H:\work\anaconda3\envs\ppoc\Lib\site-packages\paddle 下的libs复制到91.exe同目录下；
将H:\work\anaconda3\envs\ppoc\Lib\site-packages\paddleocr 下的ppocr复制到91.exe目录下和_internel目录下
f,将H:\work\anaconda3\envs\ppoc\Lib\site-packages\paddleocr 下的tools复制到_internel目录下
h,将 H:\work\anaconda3\envs\ppoc\Lib\site-packages下的Cython复制到_internel目录下
6，在cmd里面运行可执行文件。