提取错误 - Githubissues

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

opendatalab / MinerU