描述: Python项目基于easyocr模块实现大数据通信行程卡图片识别信息获取，并采用Flask框架进行识别数据返回，供大家分享食用，请大家多多star支持或者关注微信公众号哟!
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B站专栏 : https://www.bilibili.com/read/cv16911816
Github项目: https://github.com/WeiyiGeek/SecOpsDev/tree/master/Project/Python/EasyOCR/Travelcodeocr
pip install flask
pip install easyocr
pip install gevent
pip install gevent-websocket镜像构建
~$ cd /opt/images/easyocr/
/opt/images/easyocr$ ls
Dockerfile EasyOCR
$ docker build -t harbor.weiyigeek.top/python/easyocr-healthcode:v1.6.2 .
$ docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
harbor.weiyigeek.top/python/easyocr-healthcode v1.6.2 940a65f8a6ec 18 hours ago 7.39GB# 脚本启动命令
python ./setup.py --imgdir=/imgs --logdir=/logs --ip=0.0.0.0 --port=8000 --gpu=True
# 使用k8s的StatefulSet资源控制器部署Pod （此处我在GPU服务器上运行的）
$ kubectl create ns devtest
$ kubectl apply -f healthcode-sts.yaml
$ kubectl get pod -n devtest
NAME READY STATUS RESTARTS AGE
healthcode-0-5 1/1 Running 0 15h
healthcode-0-4 1/1 Running 0 15h
healthcode-0-3 1/1 Running 0 15h
healthcode-0-2 1/1 Running 0 15h
healthcode-0-1 1/1 Running 0 15h
healthcode-0-0 1/1 Running 0 15h
# 查看 GPU 服务器使用情况
nvidia-smi
Fri Dec 9 10:08:32 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.19.01 Driver Version: 465.19.01 CUDA Version: 11.3 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA Tesla V1... Off | 00000000:1B:00.0 Off | 0 |
| N/A 41C P0 36W / 250W | 6697MiB / 32510MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA Tesla V1... Off | 00000000:1D:00.0 Off | 0 |
| N/A 51C P0 53W / 250W | 9489MiB / 32510MiB | 14% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 NVIDIA Tesla V1... Off | 00000000:3D:00.0 Off | 0 |
| N/A 53C P0 42W / 250W | 5611MiB / 32510MiB | 20% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 NVIDIA Tesla V1... Off | 00000000:3F:00.0 Off | 0 |
| N/A 37C P0 35W / 250W | 10555MiB / 32510MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 4 NVIDIA Tesla V1... Off | 00000000:40:00.0 Off | 0 |
| N/A 45C P0 51W / 250W | 5837MiB / 32510MiB | 5% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 5 NVIDIA Tesla V1... Off | 00000000:41:00.0 Off | 0 |
| N/A 37C P0 37W / 250W | 10483MiB / 32510MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 167660 C python 6693MiB |
| 1 N/A N/A 166790 C python 9485MiB |
| 2 N/A N/A 165941 C python 5607MiB |
| 3 N/A N/A 165032 C python 10551MiB |
| 4 N/A N/A 164226 C python 5833MiB |
| 5 N/A N/A 163344 C python 10479MiB |
+-----------------------------------------------------------------------------+使用截图
v2版本:
# 脚本启动
python .\setup.py
# Using CPU. Note: This module is much faster with a GPU.
# * Serving Flask app 'index' (lazy loading)
# * Environment: production
# WARNING: This is a development server. Do not use it in a production deployment.
# Use a production WSGI server instead.
# * Debug mode: on
# * Running on all addresses (0.0.0.0)
# WARNING: This is a development server. Do not use it in a production deployment.
# * Running on http://127.0.0.1:8000
# * Running on http://10.20.172.106:8000 (Press CTRL+C to quit)
# * Restarting with stat
# Using CPU. Note: This module is much faster with a GPU.
# * Debugger is active!
# * Debugger PIN: 115-313-307
- # 指定健康码图片文件
> http://127.0.0.1:8000/api/v1/ocr/health?action=jkm&file=20220809/118d180d2dc540109d9ab2e22b1529ea.jpg
{"code": 200, "msg": "成功获取健康码图片数据为有健康码状态.", "data": {"file": "20220809/118d180d2dc540109d9ab2e22b1529ea.jpg", "type": "黄码"}}
- # 指定行程码图片文件
> http://127.0.0.1:8000/api/v1/ocr/health?action=xcm&file=20220530/001c35d7ac9844e78c15783bf7fda815.png
{"code": 200, "msg": "成功获取行程码数据.", "data": {"file": "20220809/001c35d7ac9844e78c15783bf7fda815.png", "type": "绿色", "phone": "153****2031", "date": "2022.08.09", "time": "08:34:10", "travel": "重庆市"}}
- # 批量扫描目录中的行程码图片文件
> http://127.0.0.1:8000/tools/ocr?dir=20220530
- # 上传行程码识别
> http://127.0.0.1:8000/tools/upload/ocrV1 版本
- # 指定行程码图片文件
> http://127.0.0.1:8000/tools/ocr?file=20220530/0a1e948e90964d42b435d63c9f0aa268.png
- # 批量扫描目录中的行程码图片文件
> http://127.0.0.1:8000/tools/ocr?dir=20220530
- # 上传行程码识别
> http://127.0.0.1:8000/tools/upload/ocrV2版本:
V1 版本
