为什么不继续执行了？ #1854
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bug
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可能是paddle-ocr的版本错误，建议去官网下载适配版本 |
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Description of the bug | 错误描述
(MinerU) C:\soft\MinerU\input>magic-pdf -p small_ocr.pdf -o ./output
import tensorrt_llm failed, if do not use tensorrt, ignore this message
import lmdeploy failed, if do not use lmdeploy, ignore this message
2025-03-05 21:20:31.860 | INFO | magic_pdf.data.dataset:init:156 - lang: None
2025-03-05 21:20:33.325 | INFO | magic_pdf.libs.pdf_check:detect_invalid_chars:67 - cid_count: 0, text_len: 8, cid_chars_radio: 0.0
2025-03-05 21:20:33.335 | WARNING | magic_pdf.filter.pdf_classify_by_type:classify:335 - OCR needed based on classification result, by_image_area: False, by_text: False, by_avg_words: False, by_img_num: True, by_img_narrow_strips: False, by_invalid_chars: True
2025-03-05 21:20:33.345 | INFO | magic_pdf.model.pdf_extract_kit:init:78 - DocAnalysis init, this may take some times, layout_model: layoutlmv3, apply_formula: True, apply_ocr: True, apply_table: True, table_model: tablemaster, lang: None
2025-03-05 21:20:33.349 | INFO | magic_pdf.model.pdf_extract_kit:init:92 - using device: cuda
2025-03-05 21:20:33.351 | INFO | magic_pdf.model.pdf_extract_kit:init:96 - using models_dir: C:\Users\Administrator.cache\modelscope\hub\models\opendatalab\PDF-Extract-Kit-1___0/models
CustomVisionEncoderDecoderModel init
VariableUnimerNetModel init
VariableUnimerNetPatchEmbeddings init
VariableUnimerNetModel init
VariableUnimerNetPatchEmbeddings init
CustomMBartForCausalLM init
CustomMBartDecoder init
[03/05 21:21:08 detectron2]: Rank of current process: 0. World size: 1
[03/05 21:21:10 detectron2]: Environment info:
sys.platform win32
Python 3.10.0 | packaged by conda-forge | (default, Nov 10 2021, 13:20:59) [MSC v.1916 64 bit (AMD64)]
numpy 1.26.3
detectron2 0.6 @C:\ProgramData\anaconda3\envs\MinerU\lib\site-packages\detectron2
Compiler MSVC 194033811
CUDA compiler not available
DETECTRON2_ENV_MODULE
PyTorch 2.3.1+cu118 @C:\ProgramData\anaconda3\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 3090 (arch=8.6)
Driver version 572.16
CUDA_HOME C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8
Pillow 11.0.0
torchvision 0.18.1+cu118 @C:\ProgramData\anaconda3\envs\MinerU\lib\site-packages\torchvision
torchvision arch flags C:\ProgramData\anaconda3\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:
[03/05 21:21:10 detectron2]: Command line arguments: {'config_file': 'C:\ProgramData\anaconda3\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\Administrator\.cache\modelscope\hub\models\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth']}
[03/05 21:21:10 detectron2]: Contents of args.config_file=C:\ProgramData\anaconda3\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:
TRAIN:
GLOBAL:
HACK: 1.0
ICDAR_DATA_DIR_TEST: ''
ICDAR_DATA_DIR_TRAIN: ''
INPUT:
CROP:
ENABLED: true
SIZE:
TYPE: absolute_range
FORMAT: RGB
MASK_FORMAT: polygon
MAX_SIZE_TEST: 1333
MAX_SIZE_TRAIN: 1333
MIN_SIZE_TEST: 800
MIN_SIZE_TRAIN:
MIN_SIZE_TRAIN_SAMPLING: choice
RANDOM_FLIP: horizontal
MODEL:
ANCHOR_GENERATOR:
ANGLES:
ASPECT_RATIOS:
NAME: DefaultAnchorGenerator
OFFSET: 0.0
SIZES:
BACKBONE:
FREEZE_AT: 2
NAME: build_vit_fpn_backbone
CONFIG_PATH: ''
DEVICE: cuda
FPN:
FUSE_TYPE: sum
IN_FEATURES:
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:
PIXEL_STD:
PROPOSAL_GENERATOR:
MIN_SIZE: 0
NAME: RPN
RESNETS:
DEFORM_MODULATED: false
DEFORM_NUM_GROUPS: 1
DEFORM_ON_PER_STAGE:
DEPTH: 50
NORM: FrozenBN
NUM_GROUPS: 1
OUT_FEATURES:
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:
FOCAL_LOSS_ALPHA: 0.25
FOCAL_LOSS_GAMMA: 2.0
IN_FEATURES:
IOU_LABELS:
IOU_THRESHOLDS:
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:
IOUS:
ROI_BOX_HEAD:
BBOX_REG_LOSS_TYPE: smooth_l1
BBOX_REG_LOSS_WEIGHT: 1.0
BBOX_REG_WEIGHTS:
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:
IOU_LABELS:
IOU_THRESHOLDS:
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:
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:
BOUNDARY_THRESH: -1
CONV_DIMS:
HEAD_NAME: StandardRPNHead
IN_FEATURES:
IOU_LABELS:
IOU_THRESHOLDS:
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:
LOSS_WEIGHT: 1.0
NAME: SemSegFPNHead
NORM: GN
NUM_CLASSES: 10
VIT:
DROP_PATH: 0.1
IMG_SIZE:
NAME: layoutlmv3_base
OUT_FEATURES:
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:
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:
DETECTIONS_PER_IMAGE: 100
EVAL_PERIOD: 1000
EXPECTED_RESULTS: []
KEYPOINT_OKS_SIGMAS: []
PRECISE_BN:
ENABLED: false
NUM_ITER: 200
VERSION: 2
VIS_PERIOD: 0
[03/05 21:21:15 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from C:\Users\Administrator.cache\modelscope\hub\models\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth ...
[03/05 21:21:15 fvcore.common.checkpoint]: [Checkpointer] Loading from c:\Users\Administrator.cache\modelscope\hub\models\opendatalab\PDF-Extract-Kit-1___0/models\Layout/LayoutLMv3/model_final.pth ...
How to reproduce the bug | 如何复现
Operating system | 操作系统
Windows
Python version | Python 版本
3.10
Software version | 软件版本 (magic-pdf --version)
1.0.x
Device mode | 设备模式
cuda
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