新增功能，获取案子全部原始图片

Dockerfile

@@ -15,6 +15,7 @@ ENV PYTHONUNBUFFERED=1 \
 COPY requirements.txt /app/requirements.txt
 COPY packages /app/packages
 RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo '$TZ' > /etc/timezone \
+    && python3 -m pip install --upgrade pip \
     && pip install --no-cache-dir -r requirements.txt \
     && pip uninstall -y onnxruntime onnxruntime-gpu \
     && pip install onnxruntime-gpu==1.18.0 --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/

Dockerfile.dev

@@ -0,0 +1,33 @@
+# 使用官方的paddle镜像作为基础
+FROM ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlex/paddlex:paddlex3.1.2-paddlepaddle3.0.0-gpu-cuda12.6-cudnn9.5-trt10.5
+
+# 设置工作目录
+WORKDIR /app
+
+# 设置环境变量
+ENV PYTHONUNBUFFERED=1 \
+    # 设置时区
+    TZ=Asia/Shanghai \
+    # 设置pip镜像地址，加快安装速度
+    PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
+
+# 安装language-pack-en和openssh-server
+RUN apt update && \
+    apt install -y language-pack-en && \
+    apt install -y openssh-server
+
+# 配置SSH服务
+RUN mkdir /var/run/sshd && \
+    # 设置root密码，可根据需要修改
+    echo 'root:fcb0102' | chpasswd && \
+    # 允许root登录SSH
+    sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
+
+# 将当前目录内容复制到容器的/app内
+COPY . /app
+
+# 暴露22端口
+EXPOSE 22
+
+# 启动SSH服务
+CMD ["/usr/sbin/sshd", "-D"]

check_ie_result/check_ie_result.py

@@ -14,7 +14,7 @@ from ucloud import ufile
 from util import image_util
 
 
-def check_ie_result(pk_phhd):
+def check_ie_result(pk_phhd, need_to_annotation=True):
     os.makedirs(f"./check_result/{pk_phhd}", exist_ok=True)
     json_result = {"pk_phhd": pk_phhd}
     session = MysqlSession()
@@ -46,10 +46,13 @@ def check_ie_result(pk_phhd):
         ZxPhrec.pk_phhd == pk_phhd).all()
     for phrec in phrecs:
         img_name = phrec.cfjaddress
+        img_path = ufile.get_private_url(img_name, "drg2015")
+        if not img_path:
             img_path = ufile.get_private_url(img_name)
 
         response = requests.get(img_path)
         image = Image.open(BytesIO(response.content)).convert("RGB")
+        if need_to_annotation:
             font_size = image.width * image.height / 200000
             font = ImageFont.truetype("./font/simfang.ttf", size=font_size)
 
@@ -85,6 +88,9 @@ def check_ie_result(pk_phhd):
                             draw.text((box[0], box[3]), value["text"], fill="blue", font=font)  # 在矩形下方绘制文本
                     os.makedirs(f"./check_result/{pk_phhd}/{ocr_item.id}", exist_ok=True)
                     image.save(f"./check_result/{pk_phhd}/{ocr_item.id}/{img_name}")
+        else:
+            os.makedirs(f"./check_result/{pk_phhd}/0", exist_ok=True)
+            image.save(f"./check_result/{pk_phhd}/0/{img_name}")
     session.close()
 
     # 自定义JSON处理器
@@ -99,4 +105,4 @@ def check_ie_result(pk_phhd):
 
 
 if __name__ == '__main__':
-    check_ie_result(0)
+    check_ie_result(5640504)

docker-compose.dev.yml

@@ -0,0 +1,26 @@
+services:
+  fcb_ai_dev:
+    image: fcb_ai_dev:0.0.10
+    build:
+      context: .
+      dockerfile: Dockerfile.dev
+    # 容器名称，可自定义
+    container_name: fcb_ai_dev
+    hostname: fcb_ai_dev
+    # 始终重启容器
+    restart: always
+    # 端口映射，根据需要修改主机端口
+    ports:
+      - "8022:22"
+    # 数据卷映射，根据实际路径修改
+    volumes:
+      - ./log:/app/log
+      - ./model:/app/model
+    # 启用GPU支持
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ '0', '1' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'

docker-compose.yml

@@ -1,6 +1,6 @@
 x-env:
   &template
-  image: fcb_photo_review:1.15.4
+  image: fcb_photo_review:1.15.7
   restart: always
 
 x-review:

document/PaddleOCR命令.md

@@ -0,0 +1,153 @@
+# PaddleOCR
+
+------
+
+## 数据集
+
+该部分内容均在PPOCRLabel目录下进行
+
+```bash
+# 进入PPOCRLabel目录
+cd .\PPOCRLabel\
+```
+
+### 打标
+
+可以对PPOCRLabel.py直接使用PyCharm中的Run，但是默认是英文的
+
+```bash
+# 以中文运行打标应用
+python PPOCRLabel.py --lang ch
+# 含有关键词提取的打标
+python PPOCRLabel.py --lang ch --kie True
+```
+
+### 划分数据集
+
+```bash
+python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../train_data/drivingData
+```
+
+------
+
+## 检测模型
+
+先回到项目根目录
+
+### 训练
+
+```bash
+python tools/train.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_student.yml
+```
+
+### 测试
+
+```bash
+python tools/infer_det.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_student.yml -o Global.pretrained_model=output/det_v4_bankcard/best_accuracy.pdparams Global.infer_img=train_data/drivingData/1.jpg
+```
+
+### 恢复训练
+
+```bash
+python tools/train.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_student.yml -o Global.checkpoints=./output/det_v4_bankcard/latest
+```
+
+------
+
+## 识别模型
+
+### 训练
+
+```bash
+python tools/train.py -c configs/rec/PP-OCRv4/ch_PP-OCRv4_rec_ampO2_ultra.yml
+```
+
+### 测试
+
+```bash
+python tools/infer_rec.py -c configs/rec/PP-OCRv4/ch_PP-OCRv4_rec_ampO2_ultra.yml -o Global.pretrained_model=output/rec_v4_bankcard/best_accuracy.pdparams Global.infer_img=train_data/drivingData/crop_img/1_crop_0.jpg
+```
+
+------
+
+## 推理模型
+
+### 检测模型转换
+
+```bash
+python tools/export_model.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_student.yml -o Global.pretrained_model=output/det_v4_bankcard/best_accuracy.pdparams
+```
+
+### 识别模型转换
+
+```bash
+python tools/export_model.py -c configs/rec/PP-OCRv4/ch_PP-OCRv4_rec_ampO2_ultra.yml -o Global.pretrained_model=output/rec_v4_bankcard/best_accuracy.pdparams
+```
+
+### 检测识别测试
+
+```bash
+python tools/infer/predict_system.py --det_model_dir=inference_model/det_v4_bankcard --rec_model_dir=inference_model/rec_v4_bankcard --rec_char_dict_path=ppocr/utils/num_dict.txt --image_dir=train_data/drivingData/1.jpg
+```
+
+------
+
+## 移动端模型
+
+### 检测模型转换
+
+```bash
+paddle_lite_opt --model_file=inference_model/det_v4_bankcard/inference.pdmodel  --param_file=inference_model/det_v4_bankcard/inference.pdiparams  --optimize_out=inference_model/det_v4_nb_bankcard --valid_targets=arm  --optimize_out_type=naive_buffer
+```
+
+### 识别模型转换
+
+```bash
+paddle_lite_opt --model_file=inference_model/rec_v4_bankcard/inference.pdmodel  --param_file=inference_model/rec_v4_bankcard/inference.pdiparams  --optimize_out=inference_model/rec_v4_nb_bankcard --valid_targets=arm  --optimize_out_type=naive_buffer
+```
+
+------
+
+------
+
+# PaddleNLP
+
+## 数据集
+
+使用Label Studio进行数据标注，安装过程省略
+
+```bash
+# 打开Anaconda Prompt
+# 激活安装Label Studio的环境
+conda activate label-studio
+# 启动Label Studio
+label-studio start
+```
+
+[打标流程](https://github.com/PaddlePaddle/PaddleNLP/blob/develop/applications/information_extraction/label_studio_doc.md)
+
+### 数据转换
+
+```bash
+# 进入PaddleNLP\applications\information_extraction后执行
+python label_studio.py --label_studio_file ./document/data/label_studio.json --save_dir ./document/data --splits 0.8 0.1 0.1 --task_type ext
+```
+
+
+
+------
+
+## 训练模型
+
+```bash
+# 进入PaddleNLP\applications\information_extraction\document后执行(双卡训练)
+python -u -m paddle.distributed.launch --gpus "0,1" finetune.py --device gpu --logging_steps 5 --save_steps 25 --eval_steps 25 --seed 42 --model_name_or_path uie-x-base --output_dir ./checkpoint/model_best --train_path data/train.txt --dev_path data/dev.txt --max_seq_len 512 --per_device_train_batch_size 8 --per_device_eval_batch_size 8 --num_train_epochs 10 --learning_rate 1e-5 --do_train --do_eval --do_export --export_model_dir ./checkpoint/model_best --overwrite_output_dir --disable_tqdm False --metric_for_best_model eval_f1 --load_best_model_at_end True --save_total_limit 1
+```
+
+------
+
+参考：
+
+[PaddleOCR训练属于自己的模型详细教程](https://blog.csdn.net/qq_52852432/article/details/131817619?utm_medium=distribute.pc_relevant.none-task-blog-2~default~baidujs_baidulandingword~default-0-131817619-blog-124628731.235^v40^pc_relevant_3m_sort_dl_base1&spm=1001.2101.3001.4242.1&utm_relevant_index=3)
+[端侧部署](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/deploy/lite/readme_ch.md)
+[PaddleNLP关键信息抽取](https://blog.csdn.net/z5z5z5z56/article/details/130346646)

document/paddle镜像自带依赖.md

@@ -0,0 +1,329 @@
+anyio               4.0.0
+astor               0.8.1
+certifi             2019.11.28
+chardet             3.0.4
+dbus-python         1.2.16
+decorator           5.1.1
+distro-info         0.23+ubuntu1.1
+exceptiongroup      1.1.3
+h11                 0.14.0
+httpcore            1.0.2
+httpx               0.25.1
+idna                2.8
+numpy               1.26.2
+opt-einsum          3.3.0
+paddlepaddle-gpu    2.6.1.post120
+Pillow              10.1.0
+pip                 24.0
+protobuf            4.25.0
+PyGObject           3.36.0
+python-apt          2.0.1+ubuntu0.20.4.1
+requests            2.22.0
+requests-unixsocket 0.2.0
+setuptools          68.2.2
+six                 1.14.0
+sniffio             1.3.0
+unattended-upgrades 0.1
+urllib3             1.25.8
+
+
+
+
+
+
+
+ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:3.1.0-gpu-cuda12.9-cudnn9.9:
+
+python:3.10.12
+
+Package                  Version
+------------------------ ----------
+anyio                    4.9.0
+certifi                  2025.6.15
+decorator                5.2.1
+exceptiongroup           1.3.0
+h11                      0.16.0
+httpcore                 1.0.9
+httpx                    0.28.1
+idna                     3.10
+networkx                 3.4.2
+numpy                    2.2.6
+nvidia-cublas-cu12       12.9.0.13
+nvidia-cuda-cccl-cu12    12.9.27
+nvidia-cuda-cupti-cu12   12.9.19
+nvidia-cuda-nvrtc-cu12   12.9.41
+nvidia-cuda-runtime-cu12 12.9.37
+nvidia-cudnn-cu12        9.9.0.52
+nvidia-cufft-cu12        11.4.0.6
+nvidia-cufile-cu12       1.14.0.30
+nvidia-curand-cu12       10.3.10.19
+nvidia-cusolver-cu12     11.7.4.40
+nvidia-cusparse-cu12     12.5.9.5
+nvidia-cusparselt-cu12   0.7.1
+nvidia-nccl-cu12         2.26.5
+nvidia-nvjitlink-cu12    12.9.41
+nvidia-nvtx-cu12         12.9.19
+opt-einsum               3.3.0
+paddlepaddle-gpu         3.1.0
+pillow                   11.2.1
+pip                      25.1.1
+protobuf                 6.31.1
+setuptools               59.6.0
+sniffio                  1.3.1
+typing_extensions        4.14.0
+wheel                    0.37.1
+
+
+
+
+
+ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlex/paddlex:paddlex3.1.2-paddlepaddle3.0.0-gpu-cuda12.6-cudnn9.5-trt10.5
+
+python:3.10.18
+
+Package                   Version              Editable project location
+------------------------- -------------------- -------------------------
+aiohappyeyeballs          2.6.1
+aiohttp                   3.12.13
+aiosignal                 1.4.0
+aistudio_sdk              0.3.5
+albucore                  0.0.13+pdx
+albumentations            1.4.10+pdx
+alembic                   1.16.2
+annotated-types           0.7.0
+anyio                     4.9.0
+astor                     0.8.1
+asttokens                 3.0.0
+async-timeout             4.0.3
+attrdict3                 2.0.2
+attrs                     25.3.0
+babel                     2.17.0
+bce-python-sdk            0.9.35
+beautifulsoup4            4.13.4
+blinker                   1.9.0
+cachetools                6.1.0
+certifi                   2019.11.28
+cffi                      1.17.1
+chardet                   3.0.4
+charset-normalizer        3.4.2
+chinese-calendar          1.8.0
+click                     8.2.1
+cloudpickle               3.1.1
+colorama                  0.4.6
+colorlog                  6.9.0
+ConfigSpace               1.2.1
+contourpy                 1.3.2
+cssselect                 1.3.0
+cssutils                  2.11.1
+cycler                    0.12.1
+Cython                    3.1.2
+dataclasses-json          0.6.7
+datasets                  3.6.0
+dbus-python               1.2.16
+decorator                 5.2.1
+decord                    0.6.0
+descartes                 1.1.0
+dill                      0.3.4
+distro                    1.9.0
+distro-info               0.23+ubuntu1.1
+easydict                  1.13
+einops                    0.8.1
+et_xmlfile                2.0.0
+exceptiongroup            1.2.2
+executing                 2.2.0
+faiss-cpu                 1.8.0.post1
+fastapi                   0.116.0
+filelock                  3.18.0
+fire                      0.7.0
+FLAML                     2.3.5
+Flask                     3.1.1
+flask-babel               4.0.0
+fonttools                 4.58.5
+frozenlist                1.7.0
+fsspec                    2025.3.0
+ftfy                      6.3.1
+future                    1.0.0
+gast                      0.3.3
+GPUtil                    1.4.0
+greenlet                  3.2.3
+h11                       0.14.0
+h5py                      3.14.0
+hf-xet                    1.1.5
+hpbandster                0.7.4
+httpcore                  1.0.7
+httpx                     0.28.1
+httpx-sse                 0.4.1
+huggingface-hub           0.33.2
+idna                      2.8
+imageio                   2.37.0
+imagesize                 1.4.1
+imgaug                    0.4.0+pdx
+ipython                   8.37.0
+itsdangerous              2.2.0
+jedi                      0.19.2
+jieba                     0.42.1
+Jinja2                    3.1.6
+jiter                     0.10.0
+joblib                    1.5.1
+jsonpatch                 1.33
+jsonpointer               3.0.0
+jsonschema                4.24.0
+jsonschema-specifications 2025.4.1
+kiwisolver                1.4.8
+langchain                 0.3.26
+langchain-community       0.3.27
+langchain-core            0.3.68
+langchain-openai          0.3.27
+langchain-text-splitters  0.3.8
+langsmith                 0.4.4
+lapx                      0.5.11.post1
+lazy_loader               0.4
+llvmlite                  0.44.0
+lmdb                      1.6.2
+lxml                      6.0.0
+Mako                      1.3.10
+markdown-it-py            3.0.0
+MarkupSafe                3.0.2
+marshmallow               3.26.1
+matplotlib                3.5.3
+matplotlib-inline         0.1.7
+mdurl                     0.1.2
+more-itertools            10.7.0
+motmetrics                1.4.0
+msgpack                   1.1.1
+multidict                 6.6.3
+multiprocess              0.70.12.2
+mypy_extensions           1.1.0
+netifaces                 0.11.0
+networkx                  3.4.2
+numba                     0.61.2
+numpy                     1.24.4
+nuscenes-devkit           1.1.11+pdx
+onnx                      1.17.0
+onnxoptimizer             0.3.13
+openai                    1.93.1
+opencv-contrib-python     4.10.0.84
+openpyxl                  3.1.5
+opt-einsum                3.3.0
+optuna                    4.4.0
+orjson                    3.10.18
+packaging                 24.2
+paddle2onnx               2.0.2rc3
+paddle3d                  0.0.0
+paddleclas                2.6.0
+paddledet                 0.0.0
+paddlefsl                 1.1.0
+paddlenlp                 2.8.0.post0
+paddlepaddle-gpu          3.0.0
+paddleseg                 0.0.0.dev0
+paddlets                  1.1.0
+paddlex                   3.1.2                /root/PaddleX
+pandas                    1.3.5
+parso                     0.8.4
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+pip                       25.1.1
+polygraphy                0.49.24
+ppvideo                   2.3.0
+premailer                 3.10.0
+prettytable               3.16.0
+prompt_toolkit            3.0.51
+propcache                 0.3.2
+protobuf                  6.30.1
+psutil                    7.0.0
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+pure_eval                 0.2.3
+py-cpuinfo                9.0.0
+pyarrow                   20.0.0
+pybind11                  2.13.6
+pybind11-stubgen          2.5.1
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+pydantic-settings         2.10.1
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+PyGObject                 3.36.0
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+pypandoc                  1.15
+pyparsing                 3.2.3
+pypdfium2                 4.30.1
+pyquaternion              0.9.9
+Pyro4                     4.82
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+python-dateutil           2.9.0.post0
+python-docx               1.2.0
+python-dotenv             1.1.1
+pytz                      2025.2
+PyWavelets                1.3.0
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+RapidFuzz                 3.13.0
+rarfile                   4.2
+ray                       2.47.1
+referencing               0.36.2
+regex                     2024.11.6
+requests                  2.32.4
+requests-toolbelt         1.0.0
+requests-unixsocket       0.2.0
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+rpds-py                   0.26.0
+ruamel.yaml               0.18.14
+ruamel.yaml.clib          0.2.12
+safetensors               0.5.3
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+scikit-learn              1.3.2
+scipy                     1.15.3
+seaborn                   0.13.2
+sentencepiece             0.2.0
+seqeval                   1.2.2
+serpent                   1.41
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+shap                      0.48.0
+Shapely                   1.8.5.post1
+shellingham               1.5.4
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+sklearn                   0.0
+slicer                    0.0.8
+sniffio                   1.3.1
+soundfile                 0.13.1
+soupsieve                 2.7
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+stack-data                0.6.3
+starlette                 0.46.2
+statsmodels               0.14.1
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+termcolor                 3.1.0
+terminaltables            3.1.10
+threadpoolctl             3.6.0
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+tiktoken                  0.9.0
+tokenizers                0.19.1
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+tool_helpers              0.1.2
+tqdm                      4.67.1
+traitlets                 5.14.3
+typeguard                 4.4.4
+typer                     0.16.0
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+typing-inspect            0.9.0
+typing-inspection         0.4.1
+tzdata                    2025.2
+ujson                     5.10.0
+unattended-upgrades       0.1
+urllib3                   1.25.8
+uvicorn                   0.35.0
+visualdl                  2.5.3
+Wand                      0.6.13
+wcwidth                   0.2.13
+Werkzeug                  3.1.3
+xmltodict                 0.14.2
+xxhash                    3.5.0
+yacs                      0.1.8
+yarl                      1.20.1
+zstandard                 0.23.0

photo_mask/auto_photo_mask.py

@@ -62,7 +62,7 @@ def find_boxes(content, layout, offset=0, length=None, improve=False, image_path
             captured_image, offset_x, offset_y = image_util.expand_to_a4_size(captured_image)
             cv2.imwrite(temp_file.name, captured_image)
         try:
-            layouts = util.get_ocr_layout(OCR, temp_file.name)
+            layouts, _ = util.get_ocr_layout(OCR, temp_file.name)
         except TypeError:
             # 如果是类型错误，大概率是没识别到文字
             layouts = []
@@ -100,7 +100,7 @@ def get_mask_layout(image, name, id_card_num):
     result = []
     try:
         try:
-            layouts = util.get_ocr_layout(OCR, temp_file.name)
+            layouts, _ = util.get_ocr_layout(OCR, temp_file.name)
             # layouts = OCR.parse({"doc": temp_file.name})["layout"]
         except TypeError:
             # 如果是类型错误，大概率是没识别到文字
@@ -198,7 +198,7 @@ def mask_photo(img_url, name, id_card_num, color=(255, 255, 255)):
         return do_mask, i
 
     # 打开图片
-    image = image_util.read(img_url)
+    image, _ = image_util.read(img_url)
     if image is None:
         return False, image
     original_image = image

photo_mask/photo_mask_error_check.py

@@ -23,7 +23,7 @@ def check_error(error_ocr):
 
     image = mask_photo(img_url, name, id_card_num, (0, 0, 0))[1]
     final_img_url = ufile.get_private_url(error_ocr.cfjaddress, "drg100")
-    final_image = image_util.read(final_img_url)
+    final_image, _ = image_util.read(final_img_url)
     return image_util.combined(final_image, image)
 
 

photo_review.py

@@ -13,14 +13,14 @@ from photo_review import auto_photo_review, SEND_ERROR_EMAIL
 
 # 项目必须从此处启动，否则代码中的相对路径可能导致错误的发生
 if __name__ == '__main__':
-    program_name = '照片审核自动识别脚本'
+    program_name = "照片审核自动识别脚本"
     logging.config.dictConfig(LOGGING_CONFIG)
 
     parser = argparse.ArgumentParser()
     parser.add_argument("--clean", default=False, type=bool, help="是否将识别中的案子改为待识别状态")
     args = parser.parse_args()
     if args.clean:
-        # 主要用于启动时，清除仍在涂抹中的案子
+        # 主要用于启动时，清除仍在识别中的案子
         session = MysqlSession()
         update_flag = (update(ZxPhhd).where(ZxPhhd.exsuccess_flag == "2").values(exsuccess_flag="1"))
         session.execute(update_flag)
@@ -34,7 +34,7 @@ if __name__ == '__main__':
         logging.info(f"【{program_name}】开始运行")
         auto_photo_review.main()
     except Exception as e:
-        error_logger = logging.getLogger('error')
+        error_logger = logging.getLogger("error")
         error_logger.error(traceback.format_exc())
         if SEND_ERROR_EMAIL:
             send_error_email(program_name, repr(e), traceback.format_exc())

photo_review/__init__.py

@@ -2,9 +2,9 @@ import jieba
 from paddlenlp import Taskflow
 from paddleocr import PaddleOCR
 
-'''
+"""
 项目配置
-'''
+"""
 # 每次从数据库获取的案子数量
 PHHD_BATCH_SIZE = 10
 # 没有查询到案子的等待时间(分钟)
@@ -18,35 +18,35 @@ LAYOUT_ANALYSIS = False
 信息抽取关键词配置
 """
 # 患者姓名
-PATIENT_NAME = ['患者姓名']
+PATIENT_NAME = ["患者姓名"]
 # 入院日期
-ADMISSION_DATE = ['入院日期']
+ADMISSION_DATE = ["入院日期"]
 # 出院日期
-DISCHARGE_DATE = ['出院日期']
+DISCHARGE_DATE = ["出院日期"]
 # 发生医疗费
-MEDICAL_EXPENSES = ['费用总额']
+MEDICAL_EXPENSES = ["费用总额"]
 # 个人现金支付
-PERSONAL_CASH_PAYMENT = ['个人现金支付']
+PERSONAL_CASH_PAYMENT = ["个人现金支付"]
 # 个人账户支付
-PERSONAL_ACCOUNT_PAYMENT = ['个人账户支付']
+PERSONAL_ACCOUNT_PAYMENT = ["个人账户支付"]
 # 个人自费金额
-PERSONAL_FUNDED_AMOUNT = ['自费金额', '个人自费']
+PERSONAL_FUNDED_AMOUNT = ["自费金额", "个人自费"]
 # 医保类别
-MEDICAL_INSURANCE_TYPE = ['医保类型']
+MEDICAL_INSURANCE_TYPE = ["医保类型"]
 # 就诊医院
-HOSPITAL = ['医院']
+HOSPITAL = ["医院"]
 # 就诊科室
-DEPARTMENT = ['科室']
+DEPARTMENT = ["科室"]
 # 主治医生
-DOCTOR = ['主治医生']
+DOCTOR = ["主治医生"]
 # 住院号
-ADMISSION_ID = ['住院号']
+ADMISSION_ID = ["住院号"]
 # 医保结算单号码
-SETTLEMENT_ID = ['医保结算单号码']
+SETTLEMENT_ID = ["医保结算单号码"]
 # 年龄
-AGE = ['年龄']
+AGE = ["年龄"]
 # 大写总额
-UPPERCASE_MEDICAL_EXPENSES = ['大写总额']
+UPPERCASE_MEDICAL_EXPENSES = ["大写总额"]
 
 SETTLEMENT_LIST_SCHEMA = \
     (PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES + PERSONAL_CASH_PAYMENT
@@ -58,57 +58,55 @@ DISCHARGE_RECORD_SCHEMA = \
 
 COST_LIST_SCHEMA = PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES
 
-'''
+"""
 别名配置
-'''
+"""
 # 使用别名中的value替换key。考虑到效率问题，只会替换第一个匹配到的key。
 HOSPITAL_ALIAS = {
-    '沐阳': ['沭阳'],
-    '连水': ['涟水'],
-    '唯宁': ['睢宁'],  # 雕宁
-    '九〇四': ['904'],
-    '漂水': ['溧水'],
+    "沐阳": ["沭阳"],
+    "连水": ["涟水"],
+    "唯宁": ["睢宁"],  # 雕宁
+    "九〇四": ["904"],
+    "漂水": ["溧水"],
 }
 DEPARTMENT_ALIAS = {
-    '耳鼻喉': ['耳鼻咽喉'],
-    '急症': ['急诊'],
+    "耳鼻喉": ["耳鼻咽喉"],
+    "急症": ["急诊"],
 }
 
-'''
+"""
 搜索过滤配置
-'''
+"""
 # 默认会过滤单字
-HOSPITAL_FILTER = ['医院', '人民', '第一', '第二', '第三', '大学', '附属']
+HOSPITAL_FILTER = ["医院", "人民", "第一", "第二", "第三", "大学", "附属"]
 
-DEPARTMENT_FILTER = ['医', '伤', '西', '新']
+DEPARTMENT_FILTER = ["医", "伤", "西", "新"]
 
-'''
+"""
 分词配置
-'''
-jieba.suggest_freq(('肿瘤', '医院'), True)
-jieba.suggest_freq(('骨', '伤'), True)
-jieba.suggest_freq(('感染', '性'), True)
-jieba.suggest_freq(('胆', '道'), True)
-jieba.suggest_freq(('脾', '胃'), True)
+"""
+jieba.suggest_freq(("肿瘤", "医院"), True)
+jieba.suggest_freq(("骨", "伤"), True)
+jieba.suggest_freq(("感染", "性"), True)
+jieba.suggest_freq(("胆", "道"), True)
+jieba.suggest_freq(("脾", "胃"), True)
 
-'''
+"""
 模型配置
-'''
-SETTLEMENT_IE = Taskflow('information_extraction', schema=SETTLEMENT_LIST_SCHEMA, model='uie-x-base',
-                         task_path='model/settlement_list_model', layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
-DISCHARGE_IE = Taskflow('information_extraction', schema=DISCHARGE_RECORD_SCHEMA, model='uie-x-base',
-                        task_path='model/discharge_record_model', layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
-COST_IE = Taskflow('information_extraction', schema=COST_LIST_SCHEMA, model='uie-x-base', device_id=1,
-                   task_path='model/cost_list_model', layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
+"""
+SETTLEMENT_IE = Taskflow("information_extraction", schema=SETTLEMENT_LIST_SCHEMA, model="uie-x-base",
+                         task_path="model/settlement_list_model", layout_analysis=LAYOUT_ANALYSIS, precision="fp16")
+DISCHARGE_IE = Taskflow("information_extraction", schema=DISCHARGE_RECORD_SCHEMA, model="uie-x-base",
+                        task_path="model/discharge_record_model", layout_analysis=LAYOUT_ANALYSIS, precision="fp16")
+COST_IE = Taskflow("information_extraction", schema=COST_LIST_SCHEMA, model="uie-x-base", device_id=1,
+                   task_path="model/cost_list_model", layout_analysis=LAYOUT_ANALYSIS, precision="fp16")
 
 OCR = PaddleOCR(
-    gpu_id=1,
-    use_angle_cls=False,
-    show_log=False,
-    det_db_thresh=0.1,
-    det_db_box_thresh=0.3,
-    det_limit_side_len=1248,
-    drop_score=0.3,
-    rec_model_dir='model/ocr/openatom_rec_repsvtr_ch_infer',
-    rec_algorithm='SVTR_LCNet',
-)
+    device="gpu:0",
+    ocr_version="PP-OCRv4",
+    use_textline_orientation=False,
+    # 检测像素阈值，输出的概率图中，得分大于该阈值的像素点才会被认为是文字像素点
+    text_det_thresh=0.1,
+    # 检测框阈值，检测结果边框内，所有像素点的平均得分大于该阈值时，该结果会被认为是文字区域
+    text_det_box_thresh=0.3,
+    )

photo_review/auto_photo_review.py

@@ -36,14 +36,15 @@ def merge_result(result1, result2):
     return result1
 
 
-def ie_temp_image(ie, ocr, image):
+def ie_temp_image(ie, ocr, image, is_screenshot=False):
     with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
         cv2.imwrite(temp_file.name, image)
 
     ie_result = []
     ocr_pure_text = ''
+    angle = '0'
     try:
-        layout = util.get_ocr_layout(ocr, temp_file.name)
+        layout, angle = util.get_ocr_layout(ocr, temp_file.name, is_screenshot)
         if not layout:
             # 无识别结果
             ie_result = []
@@ -61,7 +62,7 @@ def ie_temp_image(ie, ocr, image):
             os.remove(temp_file.name)
         except Exception as e:
             logging.info(f"删除临时文件 {temp_file.name} 时出错", exc_info=e)
-    return ie_result, ocr_pure_text
+    return ie_result, ocr_pure_text, angle
 
 
 # 关键信息提取
@@ -159,7 +160,7 @@ def information_extraction(ie, phrecs, identity):
         if not img_path:
             continue
 
-        image = image_util.read(img_path)
+        image, exif_data = image_util.read(img_path)
         if image is None:
             # 图片可能因为某些原因获取不到
             continue
@@ -175,7 +176,7 @@ def information_extraction(ie, phrecs, identity):
             if text:
                 info_extract = ie(text)[0]
             else:
-                info_extract = ie_temp_image(ie, OCR, image)[0]
+                info_extract = ie_temp_image(ie, OCR, image, True)[0]
             ie_result = {'result': info_extract, 'angle': '0'}
 
             now = util.get_default_datetime()
@@ -193,27 +194,20 @@ def information_extraction(ie, phrecs, identity):
 
             result = merge_result(result, ie_result['result'])
         else:
+            is_screenshot = image_util.is_screenshot(image, exif_data)
             target_images = []
             # target_images += detector.request_book_areas(image)  # 识别文档区域并裁剪
             if not target_images:
                 target_images.append(image)  # 识别失败
             angle_count = defaultdict(int, {'0': 0})  # 分割后图片的最优角度统计
             for target_image in target_images:
-                # dewarped_image = dewarp.dewarp_image(target_image)  # 去扭曲
-                dewarped_image = target_image
-                angles = image_util.parse_rotation_angles(dewarped_image)
-
-                split_results = image_util.split(dewarped_image)
+                split_results = image_util.split(target_image)
                 for split_result in split_results:
                     if split_result['img'] is None or split_result['img'].size == 0:
                         continue
-                    rotated_img = image_util.rotate(split_result['img'], int(angles[0]))
-                    ie_temp_result = ie_temp_image(ie, OCR, rotated_img)
+                    ie_temp_result = ie_temp_image(ie, OCR, split_result['img'], is_screenshot)
                     ocr_text += ie_temp_result[1]
-                    ie_results = [{'result': ie_temp_result[0], 'angle': angles[0]}]
-                    if not ie_results[0]['result'] or len(ie_results[0]['result']) < len(ie.kwargs.get('schema')):
-                        rotated_img = image_util.rotate(split_result['img'], int(angles[1]))
-                        ie_results.append({'result': ie_temp_image(ie, OCR, rotated_img)[0], 'angle': angles[1]})
+                    ie_results = [{'result': ie_temp_result[0], 'angle': ie_temp_result[2]}]
                     now = util.get_default_datetime()
                     best_angle = ['0', 0]
                     for ie_result in ie_results:
@@ -262,18 +256,18 @@ def information_extraction(ie, phrecs, identity):
         session.add_all(zx_ie_results)
         session.commit()
 
-        # 添加清晰度测试
-        if better_image is None:
-            # 替换后图片默认清晰
-            clarity_result = image_util.parse_clarity(image)
-            unsharp_flag = 0 if (clarity_result[0] == 0 and clarity_result[1] >= 0.8) else 1
-            update_clarity = (update(ZxPhrec).where(ZxPhrec.pk_phrec == phrec.pk_phrec).values(
-                cfjaddress2=json.dumps(clarity_result),
-                unsharp_flag=unsharp_flag,
-            ))
-            session.execute(update_clarity)
-            session.commit()
-        session.close()
+        # # 添加清晰度测试
+        # if better_image is None:
+        #     # 替换后图片默认清晰
+        #     clarity_result = image_util.parse_clarity(image)
+        #     unsharp_flag = 0 if (clarity_result[0] == 0 and clarity_result[1] >= 0.8) else 1
+        #     update_clarity = (update(ZxPhrec).where(ZxPhrec.pk_phrec == phrec.pk_phrec).values(
+        #         cfjaddress2=json.dumps(clarity_result),
+        #         unsharp_flag=unsharp_flag,
+        #     ))
+        #     session.execute(update_clarity)
+        #     session.commit()
+        # session.close()
 
     result['ocr_text'] = ocr_text
     return result
@@ -320,7 +314,7 @@ def save_or_update_ie(table, pk_phhd, data):
     if db_data:
         # 更新
         db_data.update_time = now
-        db_data.creator = HOSTNAME
+        db_data.updater = HOSTNAME
         for k, v in data.items():
             setattr(db_data, k, v)
     else:
@@ -421,6 +415,10 @@ def settlement_task(pk_phhd, settlement_list, identity):
                                      get_best_value_in_keys(settlement_list_ie_result, MEDICAL_EXPENSES))
     settlement_data["medical_expenses_str"] = handle_original_data(parse_money_result[0])
     settlement_data["medical_expenses"] = parse_money_result[1]
+
+    if not settlement_data["settlement_id"]:
+        # 如果没有结算单号就填住院号
+        settlement_data["settlement_id"] = settlement_data["admission_id"]
     save_or_update_ie(ZxIeSettlement, pk_phhd, settlement_data)
 
 

requirements.txt

@@ -1,16 +1,11 @@
-numpy==1.26.4
-onnxconverter-common==1.14.0
+aistudio_sdk==0.2.6
+onnxconverter-common==1.15.0
+onnxruntime-gpu==1.22.0
 OpenCC==1.1.6
-opencv-python==4.6.0.66
 paddle2onnx==1.2.3
-paddleclas==2.5.2
-paddlenlp==2.6.1
-paddleocr==2.7.3
-pillow==10.4.0
+paddlenlp==3.0.0b4
+paddleocr==3.1.1
+PyMuPDF==1.26.3
 pymysql==1.1.1
-requests==2.32.3
-sqlacodegen==2.3.0.post1
-sqlalchemy==1.4.52
-tenacity==8.5.0
-ufile==3.2.9
-zxing-cpp==2.2.0
+ufile==3.2.11
+zxing-cpp==2.3.0

update_dev.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+# 项目更新脚本
+echo "开始更新测试项目..."
+# 备份docker-compose配置
+cp -i docker-compose.dev.yml docker-compose-backup.dev.yml
+# 拉取最新的git
+git pull
+# 构建新镜像
+docker-compose -f docker-compose.dev.yml build
+# 停止旧的容器
+docker-compose -f docker-compose-backup.dev.yml down
+# 启动新的容器
+docker-compose -f docker-compose.dev.yml up -d
+# 删除docker-compose备份
+rm -f docker-compose-backup.dev.yml
+# 查看容器运行情况
+docker ps
+# 查看镜像
+docker images
+# 结束
+echo "测试项目更新完成，请确认容器版本正确，自行删除过期镜像。"

util/image_util.py

@@ -1,9 +1,12 @@
 import logging
 import math
 import urllib.request
+from io import BytesIO
 
 import cv2
 import numpy
+from PIL import Image
+from PIL.ExifTags import TAGS
 from paddleclas import PaddleClas
 from tenacity import retry, stop_after_attempt, wait_random
 
@@ -14,20 +17,36 @@ def read(image_path):
     """
     从网络或本地读取图片
     :param image_path: 网络或本地路径
-    :return: NumPy数组形式的图片
+    :return: NumPy数组形式的图片, EXIF数据
     """
     if image_path.startswith("http"):
         # 发送HTTP请求并获取图像数据
         resp = urllib.request.urlopen(image_path, timeout=60)
         # 将数据读取为字节流
         image_data = resp.read()
+    else:
+        with open(image_path, "rb") as f:
+            image_data = f.read()
+
+    # 解析EXIF信息（基于原始字节流）
+    exif_data = {}
+    try:
+        # 用PIL打开原始字节流
+        with Image.open(BytesIO(image_data)) as img:
+            # 获取EXIF字典
+            exif_info = img._getexif()
+            if exif_info:
+                # 将EXIF标签的数字ID转换为可读名称（如36867对应"DateTimeOriginal"）
+                for tag_id, value in exif_info.items():
+                    tag_name = TAGS.get(tag_id, tag_id)
+                    exif_data[tag_name] = value
+    except Exception as e:
+        logging.error("解析EXIF信息失败", exc_info=e)
     # 将字节流转换为NumPy数组
     image_np = numpy.frombuffer(image_data, numpy.uint8)
     # 解码NumPy数组为OpenCV图像格式
     image = cv2.imdecode(image_np, cv2.IMREAD_COLOR)
-    else:
-        image = cv2.imread(image_path)
-    return image
+    return image, exif_data
 
 
 def capture(image, rectangle):
@@ -61,7 +80,7 @@ def split(image, ratio=1.414, overlap=0.05, x_compensation=3):
     """
     split_result = []
     if isinstance(image, str):
-        image = read(image)
+        image, _ = read(image)
     height, width = image.shape[:2]
     hw_ratio = height / width
     wh_ratio = width / height
@@ -268,3 +287,61 @@ def parse_clarity(image):
     except Exception as e:
         logging.error("获取图片清晰度失败", exc_info=e)
     return clarity_result
+
+
+def is_photo_by_exif(exif_tags):
+    """分析EXIF数据判断是否为照片"""
+    # 照片通常包含的EXIF标签
+    photo_tags = [
+        'FNumber',  # 光圈
+        'ExposureTime',  # 曝光时间
+        'ISOSpeedRatings',  # ISO
+        'FocalLength',  # 焦距
+        'LensModel',  # 镜头型号
+        'GPSLatitude'  # GPS位置信息
+    ]
+
+    # 统计照片相关的EXIF标签数量
+    photo_tag_count = 0
+    if exif_tags:
+        for tag in photo_tags:
+            if tag in exif_tags:
+                photo_tag_count += 1
+                # 如果有2个以上照片相关的EXIF标签，倾向于是照片
+                if photo_tag_count >= 2:
+                    return True
+    # 不确定是照片返回False
+    return False
+
+
+def is_screenshot_by_image_features(image):
+    """分析图像特征判断是否为截图"""
+    # 定义边缘像素标准差阈值，小于此阈值则认为图片是截图
+    edge_std_threshold = 20.0
+    try:
+        # 检查边缘像素的一致性（截图边缘通常更整齐）
+        edge_pixels = []
+        # 取图像边缘10像素
+        edge_pixels.extend(image[:10, :].flatten())  # 顶部边缘
+        edge_pixels.extend(image[-10:, :].flatten())  # 底部边缘
+        edge_pixels.extend(image[:, :10].flatten())  # 左侧边缘
+        edge_pixels.extend(image[:, -10:].flatten())  # 右侧边缘
+
+        # 计算边缘像素的标准差（值越小说明越一致）
+        edge_std = numpy.std(edge_pixels)
+        logging.info(f"边缘像素标准差: {edge_std}")
+        return edge_std < edge_std_threshold
+    except Exception as e:
+        logging.error("图像特征分析失败", exc_info=e)
+        return False
+
+
+def is_screenshot(image, exif_tags):
+    """综合判断是否是截图"""
+    # 先检查EXIF数据
+    result_of_exif = is_photo_by_exif(exif_tags)
+    # 如果有明显的照片EXIF信息，直接判断为照片
+    if result_of_exif:
+        return False
+    # 分析图像特征
+    return is_screenshot_by_image_features(image)

util/util.py

@@ -12,9 +12,10 @@ def get_default_datetime():
     return datetime.now().strftime('%Y-%m-%d %H:%M:%S')
 
 
-def get_ocr_layout(ocr, img_path):
+def get_ocr_layout(ocr, img_path, is_screenshot=False):
     """
     获取ocr识别的结果，转为合适的layout形式
+    :param is_screenshot: 是否是截图
     :param ocr: ocr模型
     :param img_path: 图片本地路径
     :return:
@@ -36,18 +37,18 @@ def get_ocr_layout(ocr, img_path):
         return True
 
     layout = []
-    ocr_result = ocr.ocr(img_path, cls=False)
-    ocr_result = ocr_result[0]
+    ocr_result = ocr.predict(input=img_path, use_doc_orientation_classify=not is_screenshot, use_doc_unwarping=not is_screenshot)
+    ocr_result = next(ocr_result)
     if not ocr_result:
-        return layout
-    for segment in ocr_result:
-        box = segment[0]
+        return layout, "0"
+    angle = ocr_result.get("doc_preprocessor_res", {}).get("angle", "0")
+    for i in range(len(ocr_result.get('rec_texts'))):
+        box = ocr_result.get("rec_polys")[i].tolist()
         box = _get_box(box)
         if not _normal_box(box):
             continue
-        text = segment[1][0]
-        layout.append((box, text))
-    return layout
+        layout.append((box, ocr_result.get("rec_texts")[i]))
+    return layout, str(angle)
 
 
 def delete_temp_file(temp_files):

visual_model_test/visual_model_test.py

@@ -24,7 +24,7 @@ def write_visual_result(image, angle=0, layout=None, result=None):
         img_name = img[:last_dot_index]
         img_type = img[last_dot_index + 1:]
 
-    img_array = image_util.read(image)
+    img_array, _ = image_util.read(image)
     if angle != 0:
         img_array = image_util.rotate(img_array, angle)
     with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
@@ -63,7 +63,7 @@ def visual_model_test(model_type, test_img, task_path, schema):
                 img["y_offset"] -= offset_y
 
                 temp_files_paths.append(temp_file.name)
-                parsed_doc = util.get_ocr_layout(
+                parsed_doc, _ = util.get_ocr_layout(
                     PaddleOCR(det_db_box_thresh=0.3, det_db_thresh=0.1, det_limit_side_len=1248, drop_score=0.3,
                               save_crop_res=False),
                     temp_file.name)