提取错误 #1029

YANGtzeRi · 2024-11-19T11:03:04Z

Description of the bug | 错误描述

完成本地部署后提取文档出现错误
2024-11-19 19:01:46.298 | INFO | magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 0, last_page_cost_time: 0.0
2024-11-19 19:01:48.628 | INFO | magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 1, last_page_cost_time: 2.33
2024-11-19 19:01:48.748 | ERROR | api.analysis.pdf_ext:analysis_pdf:50 - Traceback (most recent call last):
File "D:\Yangtze\GitHub\MinerU\projects\web_demo\web_demo\api\analysis\pdf_ext.py", line 42, in analysis_pdf
pipe.pipe_parse()
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\pipe\UNIPipe.py", line 50, in pipe_parse
self.pdf_mid_data = parse_ocr_pdf(self.pdf_bytes, self.model_list, self.image_writer,
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\user_api.py", line 59, in parse_ocr_pdf
pdf_info_dict = parse_pdf_by_ocr(
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\pdf_parse_by_ocr.py", line 14, in parse_pdf_by_ocr
return pdf_parse_union(dataset,
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\pdf_parse_union_core_v2.py", line 654, in pdf_parse_union
page_info = parse_page_core(
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\pdf_parse_union_core_v2.py", line 541, in parse_page_core
spans = ocr_cut_image_and_table(
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\pre_proc\cut_image.py", line 17, in ocr_cut_image_and_table
span['image_path'] = cut_image(span['bbox'], page_id, page, return_path=return_path('images'),
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\libs\pdf_image_tools.py", line 31, in cut_image
imageWriter.write(byte_data, img_hash256_path, AbsReaderWriter.MODE_BIN)
File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\rw\DiskReaderWriter.py", line 41, in write
with open(abspath, "wb") as f:
FileNotFoundError: [Errno 2] No such file or directory: 'D:\Yangtze\GitHub\MinerU\projects\web_demo\web_demo\static/analysis_pdf/3b547652aeedd05cbcb1249efe2ebcb3405844486675188b4c1ad17f9517536d1732014031_Multipath_chirp_signal_detection_based_on_biorthogonal_fourier_transform/images\43feeaa3f1f8c0a362ccbff693581ce943d1e106eb396cdcea4eeabef0e37f71.jpg'

2024-11-19 19:01:48.751 | ERROR | api.analysis.pdf_ext:analysis_pdf_task:134 - Traceback (most recent call last):
File "D:\Yangtze\GitHub\MinerU\projects\web_demo\web_demo\api\analysis\pdf_ext.py", line 94, in analysis_pdf_task
md_content, bbox_info = analysis_pdf(image_url_prefix, image_dir, pdf_bytes, is_ocr)
TypeError: cannot unpack non-iterable NoneType object

2024-11-19 19:01:48.779 | INFO | api.analysis.pdf_ext:analysis_pdf_task:167 - all task finished!
Exception in thread Thread-10 (analysis_pdf_task):
Traceback (most recent call last):
File "D:\Yangtze\GitHub\MinerU\projects\web_demo\web_demo\api\analysis\pdf_ext.py", line 94, in analysis_pdf_task
md_content, bbox_info = analysis_pdf(image_url_prefix, image_dir, pdf_bytes, is_ocr)
TypeError: cannot unpack non-iterable NoneType object

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\yangt.conda\envs\MinerU\lib\threading.py", line 1016, in _bootstrap_inner
self.run()
File "C:\Users\yangt.conda\envs\MinerU\lib\threading.py", line 953, in run
self._target(*self._args, **self._kwargs)
File "D:\Yangtze\GitHub\MinerU\projects\web_demo\web_demo\api\analysis\pdf_ext.py", line 144, in analysis_pdf_task
raise ApiException(code=500, msg="PDF parsing failed", msgZH="pdf解析失败")
common.error_types.ApiException: 500 Internal Server Error: PDF parsing failed

How to reproduce the bug | 如何复现

本地环境 Environment info:

sys.platform win32
Python 3.10.15 | packaged by Anaconda, Inc. | (main, Oct 3 2024, 07:22:19) [MSC v.1929 64 bit (AMD64)]
numpy 1.26.3
detectron2 0.6 @C:\Users\yangt.conda\envs\MinerU\lib\site-packages\detectron2
Compiler MSVC 194033811
CUDA compiler not available
DETECTRON2_ENV_MODULE
PyTorch 2.3.1+cu118 @C:\Users\yangt.conda\envs\MinerU\lib\site-packages\torch
PyTorch debug build False
torch._C._GLIBCXX_USE_CXX11_ABI False
GPU available Yes
GPU 0 NVIDIA GeForce RTX 4060 Laptop GPU (arch=8.9)
Driver version 551.76
CUDA_HOME C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.3
Pillow 10.2.0
torchvision 0.18.1+cu118 @C:\Users\yangt.conda\envs\MinerU\lib\site-packages\torchvision
torchvision arch flags C:\Users\yangt.conda\envs\MinerU\lib\site-packages\torchvision_C.pyd; cannot find cuobjdump
fvcore 0.1.5.post20221221
iopath 0.1.9
cv2 4.6.0

PyTorch built with:

C++ Version: 201703
MSVC 192930154
Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v3.3.6 (Git Hash 86e6af5974177e513fd3fee58425e1063e7f1361)
OpenMP 2019
LAPACK is enabled (usually provided by MKL)
CPU capability usage: AVX2
CUDA Runtime 11.8
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_37,code=compute_37
CuDNN 8.7
Magma 2.5.4
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=C:/actions-runner/_work/pytorch/pytorch/builder/windows/tmp_bin/sccache-cl.exe, CXX_FLAGS=/DWIN32 /D_WINDOWS /GR /EHsc /Zc:__cplusplus /bigobj /FS /utf-8 -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE /wd4624 /wd4068 /wd4067 /wd4267 /wd4661 /wd4717 /wd4244 /wd4804 /wd4273, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=2.3.1, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=OFF, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=OFF, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,

[11/19 19:00:52 detectron2]: Command line arguments: {'config_file': 'C:\Users\yangt\.conda\envs\MinerU\lib\site-packages\magic_pdf\resources\model_config\layoutlmv3\layoutlmv3_base_inference.yaml', 'resume': False, 'eval_only': False, 'num_gpus': 1, 'num_machines': 1, 'machine_rank': 0, 'dist_url': 'tcp://127.0.0.1:57823', 'opts': ['MODEL.WEIGHTS', 'C:\Users\yangt\.cache\modelscope\hub\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth']}
[11/19 19:00:52 detectron2]: Contents of args.config_file=C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\resources\model_config\layoutlmv3\layoutlmv3_base_inference.yaml:
AUG:
DETR: true
CACHE_DIR: ~/cache/huggingface
CUDNN_BENCHMARK: false
DATALOADER:
ASPECT_RATIO_GROUPING: true
FILTER_EMPTY_ANNOTATIONS: false
NUM_WORKERS: 4
REPEAT_THRESHOLD: 0.0
SAMPLER_TRAIN: TrainingSampler
DATASETS:
PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000
PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000
PROPOSAL_FILES_TEST: []
PROPOSAL_FILES_TRAIN: []
TEST:

scihub_train
TRAIN:
scihub_train
GLOBAL:
HACK: 1.0
ICDAR_DATA_DIR_TEST: ''
ICDAR_DATA_DIR_TRAIN: ''
INPUT:
CROP:
ENABLED: true
SIZE:
- 384
- 600
  TYPE: absolute_range
  FORMAT: RGB
  MASK_FORMAT: polygon
  MAX_SIZE_TEST: 1333
  MAX_SIZE_TRAIN: 1333
  MIN_SIZE_TEST: 800
  MIN_SIZE_TRAIN:
480
512
544
576
608
640
672
704
736
768
800
MIN_SIZE_TRAIN_SAMPLING: choice
RANDOM_FLIP: horizontal
MODEL:
ANCHOR_GENERATOR:
ANGLES:
- - -90
  - 0
  - 90
    ASPECT_RATIOS:
- - 0.5
  - 1.0
  - 2.0
    NAME: DefaultAnchorGenerator
    OFFSET: 0.0
    SIZES:
- - 32
- - 64
- - 128
- - 256
- - 512
    BACKBONE:
    FREEZE_AT: 2
    NAME: build_vit_fpn_backbone
    CONFIG_PATH: ''
    DEVICE: cuda
    FPN:
    FUSE_TYPE: sum
    IN_FEATURES:
- layer3
- layer5
- layer7
- layer11
  NORM: ''
  OUT_CHANNELS: 256
  IMAGE_ONLY: true
  KEYPOINT_ON: false
  LOAD_PROPOSALS: false
  MASK_ON: true
  META_ARCHITECTURE: VLGeneralizedRCNN
  PANOPTIC_FPN:
  COMBINE:
  ENABLED: true
  INSTANCES_CONFIDENCE_THRESH: 0.5
  OVERLAP_THRESH: 0.5
  STUFF_AREA_LIMIT: 4096
  INSTANCE_LOSS_WEIGHT: 1.0
  PIXEL_MEAN:
127.5
127.5
127.5
PIXEL_STD:
127.5
127.5
127.5
PROPOSAL_GENERATOR:
MIN_SIZE: 0
NAME: RPN
RESNETS:
DEFORM_MODULATED: false
DEFORM_NUM_GROUPS: 1
DEFORM_ON_PER_STAGE:
- false
- false
- false
- false
  DEPTH: 50
  NORM: FrozenBN
  NUM_GROUPS: 1
  OUT_FEATURES:
- res4
  RES2_OUT_CHANNELS: 256
  RES5_DILATION: 1
  STEM_OUT_CHANNELS: 64
  STRIDE_IN_1X1: true
  WIDTH_PER_GROUP: 64
  RETINANET:
  BBOX_REG_LOSS_TYPE: smooth_l1
  BBOX_REG_WEIGHTS:
- 1.0
- 1.0
- 1.0
- 1.0
  FOCAL_LOSS_ALPHA: 0.25
  FOCAL_LOSS_GAMMA: 2.0
  IN_FEATURES:
- p3
- p4
- p5
- p6
- p7
  IOU_LABELS:
- 0
- -1
- 1
  IOU_THRESHOLDS:
- 0.4
- 0.5
  NMS_THRESH_TEST: 0.5
  NORM: ''
  NUM_CLASSES: 10
  NUM_CONVS: 4
  PRIOR_PROB: 0.01
  SCORE_THRESH_TEST: 0.05
  SMOOTH_L1_LOSS_BETA: 0.1
  TOPK_CANDIDATES_TEST: 1000
  ROI_BOX_CASCADE_HEAD:
  BBOX_REG_WEIGHTS:
- - 10.0
  - 10.0
  - 5.0
  - 5.0
- - 20.0
  - 20.0
  - 10.0
  - 10.0
- - 30.0
  - 30.0
  - 15.0
  - 15.0
    IOUS:
- 0.5
- 0.6
- 0.7
  ROI_BOX_HEAD:
  BBOX_REG_LOSS_TYPE: smooth_l1
  BBOX_REG_LOSS_WEIGHT: 1.0
  BBOX_REG_WEIGHTS:
- 10.0
- 10.0
- 5.0
- 5.0
  CLS_AGNOSTIC_BBOX_REG: true
  CONV_DIM: 256
  FC_DIM: 1024
  NAME: FastRCNNConvFCHead
  NORM: ''
  NUM_CONV: 0
  NUM_FC: 2
  POOLER_RESOLUTION: 7
  POOLER_SAMPLING_RATIO: 0
  POOLER_TYPE: ROIAlignV2
  SMOOTH_L1_BETA: 0.0
  TRAIN_ON_PRED_BOXES: false
  ROI_HEADS:
  BATCH_SIZE_PER_IMAGE: 512
  IN_FEATURES:
- p2
- p3
- p4
- p5
  IOU_LABELS:
- 0
- 1
  IOU_THRESHOLDS:
- 0.5
  NAME: CascadeROIHeads
  NMS_THRESH_TEST: 0.5
  NUM_CLASSES: 10
  POSITIVE_FRACTION: 0.25
  PROPOSAL_APPEND_GT: true
  SCORE_THRESH_TEST: 0.05
  ROI_KEYPOINT_HEAD:
  CONV_DIMS:
- 512
- 512
- 512
- 512
- 512
- 512
- 512
- 512
  LOSS_WEIGHT: 1.0
  MIN_KEYPOINTS_PER_IMAGE: 1
  NAME: KRCNNConvDeconvUpsampleHead
  NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: true
  NUM_KEYPOINTS: 17
  POOLER_RESOLUTION: 14
  POOLER_SAMPLING_RATIO: 0
  POOLER_TYPE: ROIAlignV2
  ROI_MASK_HEAD:
  CLS_AGNOSTIC_MASK: false
  CONV_DIM: 256
  NAME: MaskRCNNConvUpsampleHead
  NORM: ''
  NUM_CONV: 4
  POOLER_RESOLUTION: 14
  POOLER_SAMPLING_RATIO: 0
  POOLER_TYPE: ROIAlignV2
  RPN:
  BATCH_SIZE_PER_IMAGE: 256
  BBOX_REG_LOSS_TYPE: smooth_l1
  BBOX_REG_LOSS_WEIGHT: 1.0
  BBOX_REG_WEIGHTS:
- 1.0
- 1.0
- 1.0
- 1.0
  BOUNDARY_THRESH: -1
  CONV_DIMS:
- -1
  HEAD_NAME: StandardRPNHead
  IN_FEATURES:
- p2
- p3
- p4
- p5
- p6
  IOU_LABELS:
- 0
- -1
- 1
  IOU_THRESHOLDS:
- 0.3
- 0.7
  LOSS_WEIGHT: 1.0
  NMS_THRESH: 0.7
  POSITIVE_FRACTION: 0.5
  POST_NMS_TOPK_TEST: 1000
  POST_NMS_TOPK_TRAIN: 2000
  PRE_NMS_TOPK_TEST: 1000
  PRE_NMS_TOPK_TRAIN: 2000
  SMOOTH_L1_BETA: 0.0
  SEM_SEG_HEAD:
  COMMON_STRIDE: 4
  CONVS_DIM: 128
  IGNORE_VALUE: 255
  IN_FEATURES:
- p2
- p3
- p4
- p5
  LOSS_WEIGHT: 1.0
  NAME: SemSegFPNHead
  NORM: GN
  NUM_CLASSES: 10
  VIT:
  DROP_PATH: 0.1
  IMG_SIZE:
- 224
- 224
  NAME: layoutlmv3_base
  OUT_FEATURES:
- layer3
- layer5
- layer7
- layer11
  POS_TYPE: abs
  WEIGHTS:
  OUTPUT_DIR:
  SCIHUB_DATA_DIR_TRAIN: ~/publaynet/layout_scihub/train
  SEED: 42
  SOLVER:
  AMP:
  ENABLED: true
  BACKBONE_MULTIPLIER: 1.0
  BASE_LR: 0.0002
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: 2000
  CLIP_GRADIENTS:
  CLIP_TYPE: full_model
  CLIP_VALUE: 1.0
  ENABLED: true
  NORM_TYPE: 2.0
  GAMMA: 0.1
  GRADIENT_ACCUMULATION_STEPS: 1
  IMS_PER_BATCH: 32
  LR_SCHEDULER_NAME: WarmupCosineLR
  MAX_ITER: 20000
  MOMENTUM: 0.9
  NESTEROV: false
  OPTIMIZER: ADAMW
  REFERENCE_WORLD_SIZE: 0
  STEPS:
10000
WARMUP_FACTOR: 0.01
WARMUP_ITERS: 333
WARMUP_METHOD: linear
WEIGHT_DECAY: 0.05
WEIGHT_DECAY_BIAS: null
WEIGHT_DECAY_NORM: 0.0
TEST:
AUG:
ENABLED: false
FLIP: true
MAX_SIZE: 4000
MIN_SIZES:
- 400
- 500
- 600
- 700
- 800
- 900
- 1000
- 1100
- 1200
  DETECTIONS_PER_IMAGE: 100
  EVAL_PERIOD: 1000
  EXPECTED_RESULTS: []
  KEYPOINT_OKS_SIGMAS: []
  PRECISE_BN:
  ENABLED: false
  NUM_ITER: 200
  VERSION: 2
  VIS_PERIOD: 0

Operating system | 操作系统

Windows

Python version | Python 版本

3.10

Software version | 软件版本 (magic-pdf --version)

0.9.x

Device mode | 设备模式

cuda

myhloli · 2024-11-19T11:04:54Z

命令行功功能可以正常使用吗？

YANGtzeRi · 2024-11-20T15:18:46Z

正常有几个warning
但是运行提取就出现这些错误
Press CTRL+C to quit
127.0.0.1 - - [20/Nov/2024 23:17:22] "GET / HTTP/1.1" 200 -
127.0.0.1 - - [20/Nov/2024 23:17:22] "GET /assets/index-DTW6q3XL.css HTTP/1.1" 304 -
127.0.0.1 - - [20/Nov/2024 23:17:22] "GET /assets/index-B7sj4yiQ.js HTTP/1.1" 304 -
127.0.0.1 - - [20/Nov/2024 23:17:22] "GET /iconfont.js HTTP/1.1" 304 -
127.0.0.1 - - [20/Nov/2024 23:17:23] "GET /assets/logo-o6JtYmb9.svg HTTP/1.1" 304 -
127.0.0.1 - - [20/Nov/2024 23:17:23] "GET /api/v2/extract/list?pageNo=1&pageSize=100 HTTP/1.1" 200 -
127.0.0.1 - - [20/Nov/2024 23:17:23] "GET /assets/pdf-upload-V5jR-ID_.png HTTP/1.1" 304 -
127.0.0.1 - - [20/Nov/2024 23:17:23] "GET /logo.svg HTTP/1.1" 200 -
2024-11-20 23:17:26.605 | ERROR | api.extentions:handle_error:33 - An error occurred: 'NoneType' object has no attribute 'status'
Traceback (most recent call last):

File "C:\Users\yangt.conda\envs\MinerU\lib\threading.py", line 973, in _bootstrap
self._bootstrap_inner()
│ └ <function Thread._bootstrap_inner at 0x00000233F4D983A0>
└ <Thread(Thread-9 (process_request_thread), started daemon 11200)>

File "C:\Users\yangt.conda\envs\MinerU\lib\threading.py", line 1016, in _bootstrap_inner
self.run()
│ └ <function Thread.run at 0x00000233F4D980D0>
└ <Thread(Thread-9 (process_request_thread), started daemon 11200)>

File "C:\Users\yangt.conda\envs\MinerU\lib\threading.py", line 953, in run
self._target(*self._args, **self._kwargs)
│ │ │ │ │ └ {}
│ │ │ │ └ <Thread(Thread-9 (process_request_thread), started daemon 11200)>
│ │ │ └ (<socket.socket fd=1604, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0, laddr=('127.0.0.1', 5559), raddr...
│ │ └ <Thread(Thread-9 (process_request_thread), started daemon 11200)>
│ └ <bound method ThreadingMixIn.process_request_thread of <werkzeug.serving.ThreadedWSGIServer object at 0x00000233ACB77AF0>>
└ <Thread(Thread-9 (process_request_thread), started daemon 11200)>

File "C:\Users\yangt.conda\envs\MinerU\lib\socketserver.py", line 683, in process_request_thread
self.finish_request(request, client_address)
│ │ │ └ ('127.0.0.1', 11836)
│ │ └ <socket.socket fd=1604, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0, laddr=('127.0.0.1', 5559), raddr=...
│ └ <function BaseServer.finish_request at 0x00000233F4D99D80>
└ <werkzeug.serving.ThreadedWSGIServer object at 0x00000233ACB77AF0>

File "C:\Users\yangt.conda\envs\MinerU\lib\socketserver.py", line 360, in finish_request
self.RequestHandlerClass(request, client_address, self)
│ │ │ │ └ <werkzeug.serving.ThreadedWSGIServer object at 0x00000233ACB77AF0>
│ │ │ └ ('127.0.0.1', 11836)
│ │ └ <socket.socket fd=1604, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0, laddr=('127.0.0.1', 5559), raddr=...
│ └ <class 'werkzeug.serving.WSGIRequestHandler'>
└ <werkzeug.serving.ThreadedWSGIServer object at 0x00000233ACB77AF0>

File "C:\Users\yangt.conda\envs\MinerU\lib\socketserver.py", line 747, in init
self.handle()
│ └ <function WSGIRequestHandler.handle at 0x00000233F6BD49D0>
└ <werkzeug.serving.WSGIRequestHandler object at 0x00000233ACBAF6A0>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\werkzeug\serving.py", line 398, in handle
super().handle()

File "C:\Users\yangt.conda\envs\MinerU\lib\http\server.py", line 433, in handle
self.handle_one_request()
│ └ <function BaseHTTPRequestHandler.handle_one_request at 0x00000233F6962290>
└ <werkzeug.serving.WSGIRequestHandler object at 0x00000233ACBAF6A0>

File "C:\Users\yangt.conda\envs\MinerU\lib\http\server.py", line 421, in handle_one_request
method()
└ <bound method WSGIRequestHandler.run_wsgi of <werkzeug.serving.WSGIRequestHandler object at 0x00000233ACBAF6A0>>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\werkzeug\serving.py", line 370, in run_wsgi
execute(self.server.app)
│ │ │ └ <Flask 'api.extentions'>
│ │ └ <werkzeug.serving.ThreadedWSGIServer object at 0x00000233ACB77AF0>
│ └ <werkzeug.serving.WSGIRequestHandler object at 0x00000233ACBAF6A0>
└ <function WSGIRequestHandler.run_wsgi..execute at 0x00000233ACB4BD00>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\werkzeug\serving.py", line 331, in execute
application_iter = app(environ, start_response)
│ │ └ <function WSGIRequestHandler.run_wsgi..start_response at 0x00000233ACB4BC70>
│ └ {'wsgi.version': (1, 0), 'wsgi.url_scheme': 'http', 'wsgi.input': <_io.BufferedReader name=1604>, 'wsgi.errors': <_io.TextIOW...
└ <Flask 'api.extentions'>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask\app.py", line 1536, in call
return self.wsgi_app(environ, start_response)
│ │ │ └ <function WSGIRequestHandler.run_wsgi..start_response at 0x00000233ACB4BC70>
│ │ └ {'wsgi.version': (1, 0), 'wsgi.url_scheme': 'http', 'wsgi.input': <_io.BufferedReader name=1604>, 'wsgi.errors': <_io.TextIOW...
│ └ <function Flask.wsgi_app at 0x00000233F7486E60>
└ <Flask 'api.extentions'>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask\app.py", line 1511, in wsgi_app
response = self.full_dispatch_request()
│ └ <function Flask.full_dispatch_request at 0x00000233F7486680>
└ <Flask 'api.extentions'>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask\app.py", line 917, in full_dispatch_request
rv = self.dispatch_request()
│ └ <function Flask.dispatch_request at 0x00000233F74865F0>
└ <Flask 'api.extentions'>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask\app.py", line 902, in dispatch_request
return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) # type: ignore[no-any-return]
│ │ │ │ │ │ └ {}
│ │ │ │ │ └ 'analysis.analysistaskprogressview'
│ │ │ │ └ <Rule '/api/v2/extract/task/progress' (GET, OPTIONS, HEAD) -> analysis.analysistaskprogressview>
│ │ │ └ {'static': <function Flask.init.. at 0x00000233F90440D0>, 'analysis.uploadpdfview': <function View.as_vie...
│ │ └ <Flask 'api.extentions'>
│ └ <function Flask.ensure_sync at 0x00000233F7486830>
└ <Flask 'api.extentions'>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask_restful_init_.py", line 489, in wrapper
resp = resource(*args, **kwargs)
│ │ └ {}
│ └ ()
└ <function View.as_view..view at 0x00000233ABFB7130>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask\views.py", line 110, in view
return current_app.ensure_sync(self.dispatch_request)(**kwargs) # type: ignore[no-any-return]
│ │ │ └ {}
│ │ └ <function Resource.dispatch_request at 0x00000233F749A560>
│ └ <api.analysis.analysis_view.AnalysisTaskProgressView object at 0x00000233ACBAEC50>
└ <Flask 'api.extentions'>

File "C:\Users\yangt.conda\envs\MinerU\lib\site-packages\flask_restful_init_.py", line 604, in dispatch_request
resp = meth(*args, **kwargs)
│ │ └ {}
│ └ ()
└ <bound method AnalysisTaskProgressView.get of <api.analysis.analysis_view.AnalysisTaskProgressView object at 0x00000233ACBAEC...

File "D:\Yangtze\GitHub\MinerU\projects\web_demo\web_demo\api\analysis\analysis_view.py", line 38, in get
"status": analysis_pdf.status,
└ None

AttributeError: 'NoneType' object has no attribute 'status'
127.0.0.1 - - [20/Nov/2024 23:17:26] "GET /api/v2/extract/task/progress?id=2 HTTP/1.1" 500 -

然后我就没办法删除这个pdf了，就已知这样。

YANGtzeRi · 2024-11-20T15:27:37Z

测试运行的时候第二个有warning我不知道有没有影响
2024-11-20 23:25:29.926 | INFO | magic_pdf.libs.pdf_check:detect_invalid_chars:57 - cid_count: 0, text_len: 8, cid_chars_radio: 0.0
2024-11-20 23:25:29.929 | WARNING | magic_pdf.filter.pdf_classify_by_type:classify:334 - pdf is not classified by area and text_len, by_image_area: False, by_text: False, by_avg_words: False, by_img_num: True, by_text_layout: False, by_img_narrow_strips: False, by_invalid_chars: True
import tensorrt_llm failed, if do not use tensorrt, ignore this message
import lmdeploy failed, if do not use lmdeploy, ignore this message
2024-11-20 23:25:44.665 | INFO | magic_pdf.model.pdf_extract_kit:init:68 - DocAnalysis init, this may take some times, layout_model: layoutlmv3, apply_formula: True, apply_ocr: True, apply_table: False, table_model: rapid_table, lang: None
2024-11-20 23:25:44.665 | INFO | magic_pdf.model.pdf_extract_kit:init:77 - using device: cuda
2024-11-20 23:25:44.665 | INFO | magic_pdf.model.pdf_extract_kit:init:79 - using models_dir: C:\Users\yangt.cache\modelscope\hub\opendatalab\PDF-Extract-Kit-1___0/models
CustomVisionEncoderDecoderModel init
VariableUnimerNetModel init
VariableUnimerNetPatchEmbeddings init
VariableUnimerNetModel init
VariableUnimerNetPatchEmbeddings init
CustomMBartForCausalLM init
CustomMBartDecoder init
[11/20 23:25:51 detectron2]: Rank of current process: 0. World size: 1
[11/20 23:25:52 detectron2]: Environment info:

sys.platform win32
Python 3.10.15 | packaged by Anaconda, Inc. | (main, Oct 3 2024, 07:22:19) [MSC v.1929 64 bit (AMD64)]
numpy 1.26.3
detectron2 0.6 @C:\Users\yangt.conda\envs\MinerU\lib\site-packages\detectron2
Compiler MSVC 194033811
CUDA compiler not available
DETECTRON2_ENV_MODULE
PyTorch 2.3.1+cu118 @C:\Users\yangt.conda\envs\MinerU\lib\site-packages\torch
PyTorch debug build False
torch._C._GLIBCXX_USE_CXX11_ABI False
GPU available Yes
GPU 0 NVIDIA GeForce RTX 4060 Laptop GPU (arch=8.9)
Driver version 551.76
CUDA_HOME C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8
Pillow 10.2.0
torchvision 0.18.1+cu118 @C:\Users\yangt.conda\envs\MinerU\lib\site-packages\torchvision
torchvision arch flags C:\Users\yangt.conda\envs\MinerU\lib\site-packages\torchvision_C.pyd; cannot find cuobjdump
fvcore 0.1.5.post20221221
iopath 0.1.9
cv2 4.6.0

PyTorch built with:

C++ Version: 201703
MSVC 192930154
Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v3.3.6 (Git Hash 86e6af5974177e513fd3fee58425e1063e7f1361)
OpenMP 2019
LAPACK is enabled (usually provided by MKL)
CPU capability usage: AVX2
CUDA Runtime 11.8
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_37,code=compute_37
CuDNN 8.7
Magma 2.5.4
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=C:/actions-runner/_work/pytorch/pytorch/builder/windows/tmp_bin/sccache-cl.exe, CXX_FLAGS=/DWIN32 /D_WINDOWS /GR /EHsc /Zc:__cplusplus /bigobj /FS /utf-8 -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE /wd4624 /wd4068 /wd4067 /wd4267 /wd4661 /wd4717 /wd4244 /wd4804 /wd4273, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=2.3.1, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=OFF, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=OFF, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,

[11/20 23:25:52 detectron2]: Command line arguments: {'config_file': 'C:\Users\yangt\.conda\envs\MinerU\lib\site-packages\magic_pdf\resources\model_config\layoutlmv3\layoutlmv3_base_inference.yaml', 'resume': False, 'eval_only': False, 'num_gpus': 1, 'num_machines': 1, 'machine_rank': 0, 'dist_url': 'tcp://127.0.0.1:57823', 'opts': ['MODEL.WEIGHTS', 'C:\Users\yangt\.cache\modelscope\hub\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth']}
[11/20 23:25:52 detectron2]: Contents of args.config_file=C:\Users\yangt.conda\envs\MinerU\lib\site-packages\magic_pdf\resources\model_config\layoutlmv3\layoutlmv3_base_inference.yaml:
AUG:
DETR: true
CACHE_DIR: ~/cache/huggingface
CUDNN_BENCHMARK: false
DATALOADER:
ASPECT_RATIO_GROUPING: true
FILTER_EMPTY_ANNOTATIONS: false
NUM_WORKERS: 4
REPEAT_THRESHOLD: 0.0
SAMPLER_TRAIN: TrainingSampler
DATASETS:
PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000
PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000
PROPOSAL_FILES_TEST: []
PROPOSAL_FILES_TRAIN: []
TEST:

scihub_train
TRAIN:
scihub_train
GLOBAL:
HACK: 1.0
ICDAR_DATA_DIR_TEST: ''
ICDAR_DATA_DIR_TRAIN: ''
INPUT:
CROP:
ENABLED: true
SIZE:
- 384
- 600
  TYPE: absolute_range
  FORMAT: RGB
  MASK_FORMAT: polygon
  MAX_SIZE_TEST: 1333
  MAX_SIZE_TRAIN: 1333
  MIN_SIZE_TEST: 800
  MIN_SIZE_TRAIN:
480
512
544
576
608
640
672
704
736
768
800
MIN_SIZE_TRAIN_SAMPLING: choice
RANDOM_FLIP: horizontal
MODEL:
ANCHOR_GENERATOR:
ANGLES:
- - -90
  - 0
  - 90
    ASPECT_RATIOS:
- - 0.5
  - 1.0
  - 2.0
    NAME: DefaultAnchorGenerator
    OFFSET: 0.0
    SIZES:
- - 32
- - 64
- - 128
- - 256
- - 512
    BACKBONE:
    FREEZE_AT: 2
    NAME: build_vit_fpn_backbone
    CONFIG_PATH: ''
    DEVICE: cuda
    FPN:
    FUSE_TYPE: sum
    IN_FEATURES:
- layer3
- layer5
- layer7
- layer11
  NORM: ''
  OUT_CHANNELS: 256
  IMAGE_ONLY: true
  KEYPOINT_ON: false
  LOAD_PROPOSALS: false
  MASK_ON: true
  META_ARCHITECTURE: VLGeneralizedRCNN
  PANOPTIC_FPN:
  COMBINE:
  ENABLED: true
  INSTANCES_CONFIDENCE_THRESH: 0.5
  OVERLAP_THRESH: 0.5
  STUFF_AREA_LIMIT: 4096
  INSTANCE_LOSS_WEIGHT: 1.0
  PIXEL_MEAN:
127.5
127.5
127.5
PIXEL_STD:
127.5
127.5
127.5
PROPOSAL_GENERATOR:
MIN_SIZE: 0
NAME: RPN
RESNETS:
DEFORM_MODULATED: false
DEFORM_NUM_GROUPS: 1
DEFORM_ON_PER_STAGE:
- false
- false
- false
- false
  DEPTH: 50
  NORM: FrozenBN
  NUM_GROUPS: 1
  OUT_FEATURES:
- res4
  RES2_OUT_CHANNELS: 256
  RES5_DILATION: 1
  STEM_OUT_CHANNELS: 64
  STRIDE_IN_1X1: true
  WIDTH_PER_GROUP: 64
  RETINANET:
  BBOX_REG_LOSS_TYPE: smooth_l1
  BBOX_REG_WEIGHTS:
- 1.0
- 1.0
- 1.0
- 1.0
  FOCAL_LOSS_ALPHA: 0.25
  FOCAL_LOSS_GAMMA: 2.0
  IN_FEATURES:
- p3
- p4
- p5
- p6
- p7
  IOU_LABELS:
- 0
- -1
- 1
  IOU_THRESHOLDS:
- 0.4
- 0.5
  NMS_THRESH_TEST: 0.5
  NORM: ''
  NUM_CLASSES: 10
  NUM_CONVS: 4
  PRIOR_PROB: 0.01
  SCORE_THRESH_TEST: 0.05
  SMOOTH_L1_LOSS_BETA: 0.1
  TOPK_CANDIDATES_TEST: 1000
  ROI_BOX_CASCADE_HEAD:
  BBOX_REG_WEIGHTS:
- - 10.0
  - 10.0
  - 5.0
  - 5.0
- - 20.0
  - 20.0
  - 10.0
  - 10.0
- - 30.0
  - 30.0
  - 15.0
  - 15.0
    IOUS:
- 0.5
- 0.6
- 0.7
  ROI_BOX_HEAD:
  BBOX_REG_LOSS_TYPE: smooth_l1
  BBOX_REG_LOSS_WEIGHT: 1.0
  BBOX_REG_WEIGHTS:
- 10.0
- 10.0
- 5.0
- 5.0
  CLS_AGNOSTIC_BBOX_REG: true
  CONV_DIM: 256
  FC_DIM: 1024
  NAME: FastRCNNConvFCHead
  NORM: ''
  NUM_CONV: 0
  NUM_FC: 2
  POOLER_RESOLUTION: 7
  POOLER_SAMPLING_RATIO: 0
  POOLER_TYPE: ROIAlignV2
  SMOOTH_L1_BETA: 0.0
  TRAIN_ON_PRED_BOXES: false
  ROI_HEADS:
  BATCH_SIZE_PER_IMAGE: 512
  IN_FEATURES:
- p2
- p3
- p4
- p5
  IOU_LABELS:
- 0
- 1
  IOU_THRESHOLDS:
- 0.5
  NAME: CascadeROIHeads
  NMS_THRESH_TEST: 0.5
  NUM_CLASSES: 10
  POSITIVE_FRACTION: 0.25
  PROPOSAL_APPEND_GT: true
  SCORE_THRESH_TEST: 0.05
  ROI_KEYPOINT_HEAD:
  CONV_DIMS:
- 512
- 512
- 512
- 512
- 512
- 512
- 512
- 512
  LOSS_WEIGHT: 1.0
  MIN_KEYPOINTS_PER_IMAGE: 1
  NAME: KRCNNConvDeconvUpsampleHead
  NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: true
  NUM_KEYPOINTS: 17
  POOLER_RESOLUTION: 14
  POOLER_SAMPLING_RATIO: 0
  POOLER_TYPE: ROIAlignV2
  ROI_MASK_HEAD:
  CLS_AGNOSTIC_MASK: false
  CONV_DIM: 256
  NAME: MaskRCNNConvUpsampleHead
  NORM: ''
  NUM_CONV: 4
  POOLER_RESOLUTION: 14
  POOLER_SAMPLING_RATIO: 0
  POOLER_TYPE: ROIAlignV2
  RPN:
  BATCH_SIZE_PER_IMAGE: 256
  BBOX_REG_LOSS_TYPE: smooth_l1
  BBOX_REG_LOSS_WEIGHT: 1.0
  BBOX_REG_WEIGHTS:
- 1.0
- 1.0
- 1.0
- 1.0
  BOUNDARY_THRESH: -1
  CONV_DIMS:
- -1
  HEAD_NAME: StandardRPNHead
  IN_FEATURES:
- p2
- p3
- p4
- p5
- p6
  IOU_LABELS:
- 0
- -1
- 1
  IOU_THRESHOLDS:
- 0.3
- 0.7
  LOSS_WEIGHT: 1.0
  NMS_THRESH: 0.7
  POSITIVE_FRACTION: 0.5
  POST_NMS_TOPK_TEST: 1000
  POST_NMS_TOPK_TRAIN: 2000
  PRE_NMS_TOPK_TEST: 1000
  PRE_NMS_TOPK_TRAIN: 2000
  SMOOTH_L1_BETA: 0.0
  SEM_SEG_HEAD:
  COMMON_STRIDE: 4
  CONVS_DIM: 128
  IGNORE_VALUE: 255
  IN_FEATURES:
- p2
- p3
- p4
- p5
  LOSS_WEIGHT: 1.0
  NAME: SemSegFPNHead
  NORM: GN
  NUM_CLASSES: 10
  VIT:
  DROP_PATH: 0.1
  IMG_SIZE:
- 224
- 224
  NAME: layoutlmv3_base
  OUT_FEATURES:
- layer3
- layer5
- layer7
- layer11
  POS_TYPE: abs
  WEIGHTS:
  OUTPUT_DIR:
  SCIHUB_DATA_DIR_TRAIN: ~/publaynet/layout_scihub/train
  SEED: 42
  SOLVER:
  AMP:
  ENABLED: true
  BACKBONE_MULTIPLIER: 1.0
  BASE_LR: 0.0002
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: 2000
  CLIP_GRADIENTS:
  CLIP_TYPE: full_model
  CLIP_VALUE: 1.0
  ENABLED: true
  NORM_TYPE: 2.0
  GAMMA: 0.1
  GRADIENT_ACCUMULATION_STEPS: 1
  IMS_PER_BATCH: 32
  LR_SCHEDULER_NAME: WarmupCosineLR
  MAX_ITER: 20000
  MOMENTUM: 0.9
  NESTEROV: false
  OPTIMIZER: ADAMW
  REFERENCE_WORLD_SIZE: 0
  STEPS:
10000
WARMUP_FACTOR: 0.01
WARMUP_ITERS: 333
WARMUP_METHOD: linear
WEIGHT_DECAY: 0.05
WEIGHT_DECAY_BIAS: null
WEIGHT_DECAY_NORM: 0.0
TEST:
AUG:
ENABLED: false
FLIP: true
MAX_SIZE: 4000
MIN_SIZES:
- 400
- 500
- 600
- 700
- 800
- 900
- 1000
- 1100
- 1200
  DETECTIONS_PER_IMAGE: 100
  EVAL_PERIOD: 1000
  EXPECTED_RESULTS: []
  KEYPOINT_OKS_SIGMAS: []
  PRECISE_BN:
  ENABLED: false
  NUM_ITER: 200
  VERSION: 2
  VIS_PERIOD: 0

[11/20 23:25:53 d2.checkpoint. [11/20 23:25:53 fvcore.common.checkpoint]: 2024-11-20 23:25:58.307 | INFO 2024-11-20 23:25:58.307 | INFO 2024-11-20 23:26:01.428 | INFO 2024-11-20 23:26:02.194 | INFO 2024-11-20 23:26:02.198 | INFO 2024-11-20 23:26:02.370 | INFO 2024-11-20 23:26:03.631 | INFO 2024-11-20 23:26:03.631 | INFO 2024-11-20 23:26:04.894 | INFO 2024-11-20 23:26:05.080 | INFO 2024-11-20 23:26:05.817 | INFO 2024-11-20 23:26:06.012 | INFO 2024-11-20 23:26:06.796 | INFO 2024-11-20 23:26:06.796 | INFO 2024-11-20 23:26:07.810 | INFO 2024-11-20 23:26:07.968 | INFO 2024-11-20 23:26:07.968 | INFO 2024-11-20 23:26:08.147 | INFO 2024-11-20 23:26:08.771 | INFO 2024-11-20 23:26:08.771 | INFO 2024-11-20 23:26:09.806 | INFO 2024-11-20 23:26:09.961 | INFO 2024-11-20 23:26:09.962 | INFO 2024-11-20 23:26:10.138 | INFO 2024-11-20 23:26:10.660 | INFO 2024-11-20 23:26:10.661 | INFO 2024-11-20 23:26:11.651 | INFO 2024-11-20 23:26:11.804 | INFO 2024-11-20 23:26:11.804 | INFO 2024-11-20 23:26:11.972 | INFO 2024-11-20 23:26:12.560 | INFO 2024-11-20 23:26:12.561 | INFO 2024-11-20 23:26:13.589 | INFO 2024-11-20 23:26:13.741 | INFO 2024-11-20 23:26:13.742 | INFO 2024-11-20 23:26:13.922 | INFO 2024-11-20 23:26:14.475 | INFO 2024-11-20 23:26:14.475 | INFO 2024-11-20 23:26:15.492 | INFO 2024-11-20 23:26:15.648 | INFO 2024-11-20 23:26:16.220 | INFO 2024-11-20 23:26:16.391 | INFO 2024-11-20 23:26:16.930 | INFO 2024-11-20 23:26:16.931 | INFO 2024-11-20 23:26:17.969 | INFO 2024-11-20 23:26:18.125 | INFO 2024-11-20 23:26:18.126 | INFO 2024-11-20 23:26:18.300 | INFO 2024-11-20 23:26:18.872 | INFO 2024-11-20 23:26:18.873 | INFO 2024-11-20 23:26:19.025 | INFO 2024-11-20 23:26:19.026 | INFO 2024-11-20 23:26:19.187 | INFO 2024-11-20 23:26:20.664 | INFO 2024-11-20 23:26:20.705 | INFO 2024-11-20 23:26:20.737 | INFO 2024-11-20 23:26:20.764 | INFO 2024-11-20 23:26:20.791 | INFO 2024-11-20 23:26:20.818 | INFO 2024-11-20 23:26:20.846 | INFO 2024-11-20 23:26:21.226 | INFO 2024-11-20 23:26:21.259 | INFO 2024-11-20 23:26:21.260 | INFO detection_checkpoint]: [DetectionCheckpointer] Loading from C:\Users\yangt.cache\modelscope\hub\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth ...
[Checkpointer] Loading from c:\Users\yangt.cache\modelscope\hub\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth ...
| magic_pdf.model.pdf_extract_kit:init:137 - DocAnalysis init done!
| magic_pdf.model.doc_analyze_by_custom_model:custom_model_init:131 - model init cost: 28.377976417541504
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 2.27
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.74
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 0, mfr time: 0.0
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.17
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 1.26
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 4.47-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 1.26
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.16
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 4, mfr time: 0.74
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.19
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.78
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 3.16-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 1.01
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.14
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 0, mfr time: 0.0
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.18
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.62
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 1.97-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 1.03
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.13
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 0, mfr time: 0.0
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.18
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.52
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 1.89-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 0.99
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.13
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 0, mfr time: 0.0
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.17
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.59
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 1.9-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 1.02
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.13
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 0, mfr time: 0.0
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.18
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.55
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 1.91-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 1.01
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.13
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 3, mfr time: 0.57
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.17
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.54
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 2.45-----
| magic_pdf.model.pdf_extract_kit:call:153 - layout detection time: 1.03
| magic_pdf.model.pdf_extract_kit:call:161 - mfd time: 0.13
| magic_pdf.model.pdf_extract_kit:call:168 - formula nums: 0, mfr time: 0.0
| magic_pdf.model.sub_modules.model_utils:clean_vram:51 - gc time: 0.17
| magic_pdf.model.pdf_extract_kit:call:194 - ocr time: 0.57
| magic_pdf.model.pdf_extract_kit:call:226 - -----page total time: 1.94-----
| magic_pdf.model.doc_analyze_by_custom_model:doc_analyze:176 - gc time: 0.15
| magic_pdf.model.doc_analyze_by_custom_model:doc_analyze:180 - doc analyze time: 19.86, speed: 0.4 pages/second
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 0, last_page_cost_time: 0.0
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 1, last_page_cost_time: 1.48
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 2, last_page_cost_time: 0.04
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 3, last_page_cost_time: 0.03
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 4, last_page_cost_time: 0.03
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 5, last_page_cost_time: 0.03
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 6, last_page_cost_time: 0.03
| magic_pdf.pdf_parse_union_core_v2:pdf_parse_union:647 - page_id: 7, last_page_cost_time: 0.03
| magic_pdf.pipe.UNIPipe:pipe_mk_markdown:62 - uni_pipe mk mm_markdown finished
| magic_pdf.pipe.UNIPipe:pipe_mk_uni_format:57 - uni_pipe mk content list finished
| magic_pdf.tools.common:do_parse:193 - local output dir is ./output\small_ocr\auto

YANGtzeRi added the bug Something isn't working label Nov 19, 2024

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提取错误 #1029

提取错误 #1029

YANGtzeRi commented Nov 19, 2024

myhloli commented Nov 19, 2024

YANGtzeRi commented Nov 20, 2024

YANGtzeRi commented Nov 20, 2024

提取错误 #1029

提取错误 #1029

Comments

YANGtzeRi commented Nov 19, 2024

Description of the bug | 错误描述

How to reproduce the bug | 如何复现

Operating system | 操作系统

Python version | Python 版本

Software version | 软件版本 (magic-pdf --version)

Device mode | 设备模式

myhloli commented Nov 19, 2024

YANGtzeRi commented Nov 20, 2024

YANGtzeRi commented Nov 20, 2024