[WIP] New pipe

[horcham]

Thank you for your contribution to the MindOCR repo.
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• You have read the Contributing Guidelines on pull requests
• Your code builds clean without any errors or warnings
• You are using approved terminology
• You have added unit tests

Motivation

• 在线推理流水线升级，串行 -> 拓扑
• 在线推理流水线，命令

python pipeline/infer.py \
   --input_images_dir=deploy/py_infer/example/dataset/layout \
   --layout_algorithm=YOLOV8 \
   --layout_model_name_or_config=configs/layout/yolov8/yolov8n.yaml \
   --det_algorithm=DB \
   --det_model_name_or_config=configs/det/dbnet/db_r50_icdar15.yaml \
   --rec_algorithm=CRNN \
   --rec_model_name_or_config=configs/rec/crnn/crnn_resnet34.yaml \
   --cls_algorithm=MV3 \
   --cls_model_name_or_config=configs/cls/mobilenetv3/cls_mv3.yaml \
   --res_save_dir=res \
   --show_log=False \
   --vis_pipeline_save_dir=res \
   --visual_pipeline=False

支持模式：
DET, REC, CLS, DET_REC, DET_CLS_REC, LAYOUT, LAYOUT_DET_REC, LAYOUT_DET_CLS_REC

• 支持离线、在线混推，使用方法

  • 在yaml文件中定义predict
  • 需新增字段

    predict:
      # backend: MindSpore
      backend: MindSporeLite
      deive_target: Ascend
      device_id: 0
      max_device_memory: 8GB
      amp_level: O0
      mode: 0
      # ckpt_load_path: /root/.mindspore/models/dbnet_resnet50-c3a4aa24.ckpt
      ckpt_load_path: /data3/psw/zhanghongquan/experiment/new_pipe/mindocr/tools/output_folder/convert_folder/dbnet_resnet50_lite_dynamic.mindir
      ...

  • 在yaml的predict中配置以下字段
    • backend: 可选MindSpore, MindSporeLite
    • deive_target: 可选Ascend, CPU，GPU. CPU，GPU未测试
    • device_id：该模型运行的设备
    • max_device_memory：MindSpore模式下最大显存
    • amp_level：优化选项
    • ckpt_load_path：MindSpore模式下为ckpt，MindSporeLite模式下为mindir

• 流水线可视化，可实时分析性能瓶颈

 0. Node:HandoutNode0, Has Processed:801, input queue:32     : 100%|███████████████████████████|32/32
 1. Node:DecodeNode0, Has Processed:784, input queue:16      : 100%|███████████████████████████|16/16
 2. Node:DetPreNode0, Has Processed:767, input queue:16      : 100%|███████████████████████████|16/16
 3. Node:DetInferNode0, Has Processed:750, input queue:15    :  94%|█████████████████████████▎ |15/16
 4. Node:DetPostNode0, Has Processed:734, input queue:16     : 100%|███████████████████████████|16/16
 5. Node:ClsPreNode0, Has Processed:717, input queue:16      : 100%|███████████████████████████|16/16
 6. Node:ClsInferNode0, Has Processed:700, input queue:16    : 100%|███████████████████████████|16/16
 7. Node:ClsPostNode0, Has Processed:683, input queue:16     : 100%|███████████████████████████|16/16
 8. Node:RecPreNode0, Has Processed:666, input queue:16      : 100%|███████████████████████████|16/16
 9. Node:RecInferNode0, Has Processed:649, input queue:16    : 100%|███████████████████████████|16/16
 10. Node:RecPostNode0, Has Processed:632, input queue:16    : 100%|███████████████████████████|16/16
 11. Node:CollectNode0, Has Processed:615, input queue:16    : 100%|███████████████████████████|16/16

• 线性流水线升级为拓扑流水线
• 加入Layout节点
• 加入TableMaster节点
• 功能测试

  • 全离线模型

    • layout：yolov8
    • det：dbnet_resnet60

      pipeline/infer.py --input_images_dir=deploy/py_infer/example/dataset/layout --det_model_name_or_config=configs/det/dbnet/db_r50_icdar15.yaml --det_model_name_or_config=deploy/py_infer/src/configs/det/ppocr/ch_PP-OCRv4_det_cml.yaml --res_save_dir=res --show_log=False

    • rec：crnn_resnet34

      pipeline/infer.py --input_images_dir=deploy/py_infer/example/dataset/layout --rec_algorithm=CRNN --rec_model_name_or_config=configs/rec/crnn/crnn_resnet34.yaml --res_save_dir=res --show_log=False

    • det_rec_cls

      pipeline/infer.py --input_images_dir=deploy/py_infer/example/dataset/layout --det_algorithm=DB --det_model_name_or_config=configs/det/dbnet/db_r50_icdar15.yaml --rec_algorithm=CRNN --rec_model_name_or_config=configs/rec/crnn/crnn_resnet34.yaml --cls_algorithm=MV3 --cls_model_name_or_config=configs/cls/mobilenetv3/cls_mv3.yaml --res_save_dir=res --show_log=False --vis_pipeline_save_dir=res --visual_pipeline=False

    • layout_det_rec_cls

      python /pipeline/infer.py --input_images_dir=deploy/py_infer/example/dataset/layout --layout_algorithm=YOLOV8 --layout_model_name_or_config=configs/layout/yolov8/yolov8n.yaml --det_algorithm=DB --det_model_name_or_config=configs/det/dbnet/db_r50_icdar15.yaml --rec_algorithm=CRNN --rec_model_name_or_config=configs/rec/crnn/crnn_resnet34.yaml --cls_algorithm=MV3 --cls_model_name_or_config=configs/cls/mobilenetv3/cls_mv3.yaml --res_save_dir=res --show_log=False --vis_pipeline_save_dir=res --visual_pipeline=False

      demo结果
      
      

  • 全在线模型

    • det_rec_cls
    • layout_det_rec_cls

  • 离线、在线模型

    • det_rec_cls，离线_在线_离线
    • layout_det_rec_cls，离线_在线_离线_在线

(Write your motivation for proposed changes here.)

Test Plan

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Related Issues and PRs

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