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aodianyun /ad-pdf-extract:8760c9da
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=aodianyun/ad-pdf-extract
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run aodianyun/ad-pdf-extract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"aodianyun/ad-pdf-extract:8760c9da25e67ab85d40c0efb56dbc75e2d0553de0f665cd7c8af7c58d6b48a9",
{
input: {
pdf: "http://fm.aodianyun.com/edudoc/sw1.pdf",
method: "auto"
}
}
);
// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun aodianyun/ad-pdf-extract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"aodianyun/ad-pdf-extract:8760c9da25e67ab85d40c0efb56dbc75e2d0553de0f665cd7c8af7c58d6b48a9",
input={
"pdf": "http://fm.aodianyun.com/edudoc/sw1.pdf",
"method": "auto"
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run aodianyun/ad-pdf-extract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-H "Prefer: wait" \
-d $'{
"version": "aodianyun/ad-pdf-extract:8760c9da25e67ab85d40c0efb56dbc75e2d0553de0f665cd7c8af7c58d6b48a9",
"input": {
"pdf": "http://fm.aodianyun.com/edudoc/sw1.pdf",
"method": "auto"
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
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Output
Rendering markdown...
{
"completed_at": "2024-09-26T09:49:47.885257Z",
"created_at": "2024-09-26T09:40:51.628000Z",
"data_removed": false,
"error": null,
"id": "fzwr56bb5hrge0cj5pta96g7m4",
"input": {
"pdf": "http://fm.aodianyun.com/edudoc/sw1.pdf",
"method": "auto"
},
"logs": "start\n/tmp/tmpkkr03214sw1.pdf\n2024-09-26 09:45:07.994 | INFO | magic_pdf.libs.pdf_check:detect_invalid_chars:57 - cid_count: 0, text_len: 6, cid_chars_radio: 0.0\n2024-09-26 09:45:07.994 | 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: True, by_invalid_chars: True\n2024-09-26 09:45:15.442 | INFO | magic_pdf.model.pdf_extract_kit:__init__:180 - DocAnalysis init, this may take some times. apply_layout: True, apply_formula: True, apply_ocr: True, apply_table: False\n2024-09-26 09:45:15.442 | INFO | magic_pdf.model.pdf_extract_kit:__init__:188 - using device: cuda\n2024-09-26 09:45:15.442 | INFO | magic_pdf.model.pdf_extract_kit:__init__:190 - using models_dir: /src/models\nCustomVisionEncoderDecoderModel init\nCustomMBartForCausalLM init\nCustomMBartDecoder init\n[09/26 09:45:34 detectron2]: Rank of current process: 0. World size: 1\n[09/26 09:45:35 detectron2]: Environment info:\n------------------------------- ------------------------------------------------------------------------------------\nsys.platform linux\nPython 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0]\nnumpy 1.26.4\ndetectron2 0.6 @/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/detectron2\nCompiler GCC 11.4\nCUDA compiler not available\nDETECTRON2_ENV_MODULE <not set>\nPyTorch 2.3.1+cu121 @/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/torch\nPyTorch debug build False\ntorch._C._GLIBCXX_USE_CXX11_ABI False\nGPU available Yes\nGPU 0 Tesla T4 (arch=7.5)\nDriver version 535.104.12\nCUDA_HOME /usr/local/cuda\nPillow 10.4.0\ntorchvision 0.18.1+cu121 @/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/torchvision\ntorchvision arch flags 5.0, 6.0, 7.0, 7.5, 8.0, 8.6, 9.0\nfvcore 0.1.5.post20221221\niopath 0.1.9\ncv2 4.6.0\n------------------------------- ------------------------------------------------------------------------------------\nPyTorch built with:\n- GCC 9.3\n- C++ Version: 201703\n- Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications\n- Intel(R) MKL-DNN v3.3.6 (Git Hash 86e6af5974177e513fd3fee58425e1063e7f1361)\n- OpenMP 201511 (a.k.a. OpenMP 4.5)\n- LAPACK is enabled (usually provided by MKL)\n- NNPACK is enabled\n- CPU capability usage: AVX2\n- CUDA Runtime 12.1\n- NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-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\n- CuDNN 8.9\n- Built with CuDNN 8.9.2\n- Magma 2.6.1\n- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, 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=1, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,\n[09/26 09:45:35 detectron2]: Command line arguments: {'config_file': '/root/.pyenv/versions/3.10.15/lib/python3.10/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', '/src/models/Layout/model_final.pth']}\n[09/26 09:45:35 detectron2]: Contents of args.config_file=/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/magic_pdf/resources/model_config/layoutlmv3/layoutlmv3_base_inference.yaml:\nAUG:\nDETR: true\nCACHE_DIR: ~/cache/huggingface\nCUDNN_BENCHMARK: false\nDATALOADER:\nASPECT_RATIO_GROUPING: true\nFILTER_EMPTY_ANNOTATIONS: false\nNUM_WORKERS: 4\nREPEAT_THRESHOLD: 0.0\nSAMPLER_TRAIN: TrainingSampler\nDATASETS:\nPRECOMPUTED_PROPOSAL_TOPK_TEST: 1000\nPRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000\nPROPOSAL_FILES_TEST: []\nPROPOSAL_FILES_TRAIN: []\nTEST:\n- scihub_train\nTRAIN:\n- scihub_train\nGLOBAL:\nHACK: 1.0\nICDAR_DATA_DIR_TEST: ''\nICDAR_DATA_DIR_TRAIN: ''\nINPUT:\nCROP:\nENABLED: true\nSIZE:\n- 384\n- 600\nTYPE: absolute_range\nFORMAT: RGB\nMASK_FORMAT: polygon\nMAX_SIZE_TEST: 1333\nMAX_SIZE_TRAIN: 1333\nMIN_SIZE_TEST: 800\nMIN_SIZE_TRAIN:\n- 480\n- 512\n- 544\n- 576\n- 608\n- 640\n- 672\n- 704\n- 736\n- 768\n- 800\nMIN_SIZE_TRAIN_SAMPLING: choice\nRANDOM_FLIP: horizontal\nMODEL:\nANCHOR_GENERATOR:\nANGLES:\n- - -90\n- 0\n- 90\nASPECT_RATIOS:\n- - 0.5\n- 1.0\n- 2.0\nNAME: DefaultAnchorGenerator\nOFFSET: 0.0\nSIZES:\n- - 32\n- - 64\n- - 128\n- - 256\n- - 512\nBACKBONE:\nFREEZE_AT: 2\nNAME: build_vit_fpn_backbone\nCONFIG_PATH: ''\nDEVICE: cuda\nFPN:\nFUSE_TYPE: sum\nIN_FEATURES:\n- layer3\n- layer5\n- layer7\n- layer11\nNORM: ''\nOUT_CHANNELS: 256\nIMAGE_ONLY: true\nKEYPOINT_ON: false\nLOAD_PROPOSALS: false\nMASK_ON: true\nMETA_ARCHITECTURE: VLGeneralizedRCNN\nPANOPTIC_FPN:\nCOMBINE:\nENABLED: true\nINSTANCES_CONFIDENCE_THRESH: 0.5\nOVERLAP_THRESH: 0.5\nSTUFF_AREA_LIMIT: 4096\nINSTANCE_LOSS_WEIGHT: 1.0\nPIXEL_MEAN:\n- 127.5\n- 127.5\n- 127.5\nPIXEL_STD:\n- 127.5\n- 127.5\n- 127.5\nPROPOSAL_GENERATOR:\nMIN_SIZE: 0\nNAME: RPN\nRESNETS:\nDEFORM_MODULATED: false\nDEFORM_NUM_GROUPS: 1\nDEFORM_ON_PER_STAGE:\n- false\n- false\n- false\n- false\nDEPTH: 50\nNORM: FrozenBN\nNUM_GROUPS: 1\nOUT_FEATURES:\n- res4\nRES2_OUT_CHANNELS: 256\nRES5_DILATION: 1\nSTEM_OUT_CHANNELS: 64\nSTRIDE_IN_1X1: true\nWIDTH_PER_GROUP: 64\nRETINANET:\nBBOX_REG_LOSS_TYPE: smooth_l1\nBBOX_REG_WEIGHTS:\n- 1.0\n- 1.0\n- 1.0\n- 1.0\nFOCAL_LOSS_ALPHA: 0.25\nFOCAL_LOSS_GAMMA: 2.0\nIN_FEATURES:\n- p3\n- p4\n- p5\n- p6\n- p7\nIOU_LABELS:\n- 0\n- -1\n- 1\nIOU_THRESHOLDS:\n- 0.4\n- 0.5\nNMS_THRESH_TEST: 0.5\nNORM: ''\nNUM_CLASSES: 10\nNUM_CONVS: 4\nPRIOR_PROB: 0.01\nSCORE_THRESH_TEST: 0.05\nSMOOTH_L1_LOSS_BETA: 0.1\nTOPK_CANDIDATES_TEST: 1000\nROI_BOX_CASCADE_HEAD:\nBBOX_REG_WEIGHTS:\n- - 10.0\n- 10.0\n- 5.0\n- 5.0\n- - 20.0\n- 20.0\n- 10.0\n- 10.0\n- - 30.0\n- 30.0\n- 15.0\n- 15.0\nIOUS:\n- 0.5\n- 0.6\n- 0.7\nROI_BOX_HEAD:\nBBOX_REG_LOSS_TYPE: smooth_l1\nBBOX_REG_LOSS_WEIGHT: 1.0\nBBOX_REG_WEIGHTS:\n- 10.0\n- 10.0\n- 5.0\n- 5.0\nCLS_AGNOSTIC_BBOX_REG: true\nCONV_DIM: 256\nFC_DIM: 1024\nNAME: FastRCNNConvFCHead\nNORM: ''\nNUM_CONV: 0\nNUM_FC: 2\nPOOLER_RESOLUTION: 7\nPOOLER_SAMPLING_RATIO: 0\nPOOLER_TYPE: ROIAlignV2\nSMOOTH_L1_BETA: 0.0\nTRAIN_ON_PRED_BOXES: false\nROI_HEADS:\nBATCH_SIZE_PER_IMAGE: 512\nIN_FEATURES:\n- p2\n- p3\n- p4\n- p5\nIOU_LABELS:\n- 0\n- 1\nIOU_THRESHOLDS:\n- 0.5\nNAME: CascadeROIHeads\nNMS_THRESH_TEST: 0.5\nNUM_CLASSES: 10\nPOSITIVE_FRACTION: 0.25\nPROPOSAL_APPEND_GT: true\nSCORE_THRESH_TEST: 0.05\nROI_KEYPOINT_HEAD:\nCONV_DIMS:\n- 512\n- 512\n- 512\n- 512\n- 512\n- 512\n- 512\n- 512\nLOSS_WEIGHT: 1.0\nMIN_KEYPOINTS_PER_IMAGE: 1\nNAME: KRCNNConvDeconvUpsampleHead\nNORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: true\nNUM_KEYPOINTS: 17\nPOOLER_RESOLUTION: 14\nPOOLER_SAMPLING_RATIO: 0\nPOOLER_TYPE: ROIAlignV2\nROI_MASK_HEAD:\nCLS_AGNOSTIC_MASK: false\nCONV_DIM: 256\nNAME: MaskRCNNConvUpsampleHead\nNORM: ''\nNUM_CONV: 4\nPOOLER_RESOLUTION: 14\nPOOLER_SAMPLING_RATIO: 0\nPOOLER_TYPE: ROIAlignV2\nRPN:\nBATCH_SIZE_PER_IMAGE: 256\nBBOX_REG_LOSS_TYPE: smooth_l1\nBBOX_REG_LOSS_WEIGHT: 1.0\nBBOX_REG_WEIGHTS:\n- 1.0\n- 1.0\n- 1.0\n- 1.0\nBOUNDARY_THRESH: -1\nCONV_DIMS:\n- -1\nHEAD_NAME: StandardRPNHead\nIN_FEATURES:\n- p2\n- p3\n- p4\n- p5\n- p6\nIOU_LABELS:\n- 0\n- -1\n- 1\nIOU_THRESHOLDS:\n- 0.3\n- 0.7\nLOSS_WEIGHT: 1.0\nNMS_THRESH: 0.7\nPOSITIVE_FRACTION: 0.5\nPOST_NMS_TOPK_TEST: 1000\nPOST_NMS_TOPK_TRAIN: 2000\nPRE_NMS_TOPK_TEST: 1000\nPRE_NMS_TOPK_TRAIN: 2000\nSMOOTH_L1_BETA: 0.0\nSEM_SEG_HEAD:\nCOMMON_STRIDE: 4\nCONVS_DIM: 128\nIGNORE_VALUE: 255\nIN_FEATURES:\n- p2\n- p3\n- p4\n- p5\nLOSS_WEIGHT: 1.0\nNAME: SemSegFPNHead\nNORM: GN\nNUM_CLASSES: 10\nVIT:\nDROP_PATH: 0.1\nIMG_SIZE:\n- 224\n- 224\nNAME: layoutlmv3_base\nOUT_FEATURES:\n- layer3\n- layer5\n- layer7\n- layer11\nPOS_TYPE: abs\nWEIGHTS:\nOUTPUT_DIR:\nSCIHUB_DATA_DIR_TRAIN: ~/publaynet/layout_scihub/train\nSEED: 42\nSOLVER:\nAMP:\nENABLED: true\nBACKBONE_MULTIPLIER: 1.0\nBASE_LR: 0.0002\nBIAS_LR_FACTOR: 1.0\nCHECKPOINT_PERIOD: 2000\nCLIP_GRADIENTS:\nCLIP_TYPE: full_model\nCLIP_VALUE: 1.0\nENABLED: true\nNORM_TYPE: 2.0\nGAMMA: 0.1\nGRADIENT_ACCUMULATION_STEPS: 1\nIMS_PER_BATCH: 32\nLR_SCHEDULER_NAME: WarmupCosineLR\nMAX_ITER: 20000\nMOMENTUM: 0.9\nNESTEROV: false\nOPTIMIZER: ADAMW\nREFERENCE_WORLD_SIZE: 0\nSTEPS:\n- 10000\nWARMUP_FACTOR: 0.01\nWARMUP_ITERS: 333\nWARMUP_METHOD: linear\nWEIGHT_DECAY: 0.05\nWEIGHT_DECAY_BIAS: null\nWEIGHT_DECAY_NORM: 0.0\nTEST:\nAUG:\nENABLED: false\nFLIP: true\nMAX_SIZE: 4000\nMIN_SIZES:\n- 400\n- 500\n- 600\n- 700\n- 800\n- 900\n- 1000\n- 1100\n- 1200\nDETECTIONS_PER_IMAGE: 100\nEVAL_PERIOD: 1000\nEXPECTED_RESULTS: []\nKEYPOINT_OKS_SIGMAS: []\nPRECISE_BN:\nENABLED: false\nNUM_ITER: 200\nVERSION: 2\nVIS_PERIOD: 0\n[09/26 09:45:37 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from /src/models/Layout/model_final.pth ...\n[09/26 09:45:37 fvcore.common.checkpoint]: [Checkpointer] Loading from /src/models/Layout/model_final.pth ...\ndownload https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar to /root/.paddleocr/whl/det/ch/ch_PP-OCRv4_det_infer/ch_PP-OCRv4_det_infer.tar\n 0%| | 0.00/4.89M [00:00<?, ?iB/s]\n 0%| | 3.07k/4.89M [00:00<05:36, 14.5kiB/s]\n 1%| | 35.8k/4.89M [00:00<00:58, 83.1kiB/s]\n 1%| | 52.2k/4.89M [00:00<00:47, 102kiB/s] \n 1%|▏ | 68.6k/4.89M [00:00<00:45, 107kiB/s]\n 2%|▏ | 85.0k/4.89M [00:00<00:52, 90.8kiB/s]\n 2%|▏ | 118k/4.89M [00:01<00:44, 108kiB/s] \n 3%|▎ | 134k/4.89M [00:01<00:55, 85.2kiB/s]\n 3%|▎ | 151k/4.89M [00:01<00:58, 81.1kiB/s]\n 3%|▎ | 167k/4.89M [00:01<01:01, 76.9kiB/s]\n 4%|▎ | 183k/4.89M [00:02<01:03, 74.1kiB/s]\n 4%|▍ | 200k/4.89M [00:02<01:03, 73.4kiB/s]\n 4%|▍ | 216k/4.89M [00:02<01:05, 71.7kiB/s]\n 5%|▍ | 232k/4.89M [00:02<01:02, 74.2kiB/s]\n 5%|▌ | 249k/4.89M [00:03<01:04, 72.2kiB/s]\n 5%|▌ | 265k/4.89M [00:03<01:01, 75.5kiB/s]\n 6%|▌ | 282k/4.89M [00:03<01:03, 73.0kiB/s]\n 6%|▌ | 298k/4.89M [00:03<01:03, 72.7kiB/s]\n 6%|▋ | 314k/4.89M [00:04<01:04, 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| 1.77M/2.19M [00:17<00:01, 294kiB/s]\n 82%|████████▏ | 1.81M/2.19M [00:17<00:01, 296kiB/s]\n 84%|████████▍ | 1.84M/2.19M [00:17<00:01, 294kiB/s]\n 85%|████████▌ | 1.87M/2.19M [00:17<00:01, 297kiB/s]\n 87%|████████▋ | 1.90M/2.19M [00:17<00:00, 295kiB/s]\n 88%|████████▊ | 1.94M/2.19M [00:17<00:00, 297kiB/s]\n 90%|████████▉ | 1.97M/2.19M [00:18<00:00, 303kiB/s]\n 91%|█████████▏| 2.00M/2.19M [00:18<00:00, 303kiB/s]\n 93%|█████████▎| 2.03M/2.19M [00:18<00:00, 299kiB/s]\n 94%|█████████▍| 2.07M/2.19M [00:18<00:00, 300kiB/s]\n 97%|█████████▋| 2.12M/2.19M [00:18<00:00, 319kiB/s]\n 99%|█████████▉| 2.17M/2.19M [00:18<00:00, 340kiB/s]\n100%|██████████| 2.19M/2.19M [00:18<00:00, 117kiB/s]\n2024-09-26 09:46:35.967 | INFO | magic_pdf.model.pdf_extract_kit:__init__:248 - DocAnalysis init done!\n2024-09-26 09:46:35.968 | INFO | magic_pdf.model.doc_analyze_by_custom_model:custom_model_init:98 - model init cost: 87.97307825088501\n2024-09-26 09:46:39.620 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.91\n0: 1888x1504 14 embeddings, 237.6ms\nSpeed: 21.7ms preprocess, 237.6ms inference, 1.8ms postprocess per image at shape (1, 3, 1888, 1504)\n2024-09-26 09:46:41.567 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 14, mfr time: 0.72\n2024-09-26 09:47:03.059 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 21.48\n2024-09-26 09:47:04.696 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.64\n0: 1888x1344 12 embeddings, 217.7ms\nSpeed: 18.7ms preprocess, 217.7ms inference, 1.7ms postprocess per image at shape (1, 3, 1888, 1344)\n2024-09-26 09:47:05.967 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 12, mfr time: 0.85\n2024-09-26 09:47:28.866 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 22.88\n2024-09-26 09:47:30.793 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.93\n0: 1888x1376 1 embedding, 223.2ms\nSpeed: 24.1ms preprocess, 223.2ms inference, 1.8ms postprocess per image at shape (1, 3, 1888, 1376)\n2024-09-26 09:47:31.647 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 1, mfr time: 0.58\n2024-09-26 09:48:00.164 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 28.5\n2024-09-26 09:48:01.953 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.79\n0: 1888x1344 3 embeddings, 215.8ms\nSpeed: 20.7ms preprocess, 215.8ms inference, 1.4ms postprocess per image at shape (1, 3, 1888, 1344)\n2024-09-26 09:48:02.637 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 3, mfr time: 0.39\n2024-09-26 09:48:28.050 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 25.4\n2024-09-26 09:48:30.080 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 2.03\n0: 1888x1280 1 embedding, 204.6ms\nSpeed: 19.8ms preprocess, 204.6ms inference, 2.0ms postprocess per image at shape (1, 3, 1888, 1280)\n2024-09-26 09:48:30.646 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 1, mfr time: 0.32\n2024-09-26 09:49:09.381 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 38.72\n2024-09-26 09:49:11.338 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.96\n0: 1888x1408 2 embeddings, 235.1ms\nSpeed: 23.4ms preprocess, 235.1ms inference, 1.5ms postprocess per image at shape (1, 3, 1888, 1408)\n2024-09-26 09:49:12.379 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 2, mfr time: 0.74\n2024-09-26 09:49:46.451 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 34.06\n2024-09-26 09:49:46.452 | INFO | magic_pdf.model.doc_analyze_by_custom_model:doc_analyze:136 - doc analyze cost: 188.74599361419678\n2024-09-26 09:49:47.552 | INFO | magic_pdf.pipe.UNIPipe:pipe_mk_uni_format:48 - uni_pipe mk content list finished\n2024-09-26 09:49:47.567 | INFO | magic_pdf.pipe.UNIPipe:pipe_mk_markdown:53 - uni_pipe mk mm_markdown finished\nend",
"metrics": {
"predict_time": 283.02873374,
"total_time": 536.257257
},
"output": [
"https://replicate.delivery/czjl/N7aItThxCGpuLZoRRJh472aijOVSko10L6qfaL3A2rpdAXwJA/edupdf.md",
"https://replicate.delivery/czjl/qbgwHw8RbvrIG1OPfEKwjCJIH8NL2RsaGo0mNo649pkdAXwJA/edupdf.zip"
],
"started_at": "2024-09-26T09:45:04.856524Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/fzwr56bb5hrge0cj5pta96g7m4",
"cancel": "https://api.replicate.com/v1/predictions/fzwr56bb5hrge0cj5pta96g7m4/cancel"
},
"version": "8760c9da25e67ab85d40c0efb56dbc75e2d0553de0f665cd7c8af7c58d6b48a9"
}Generated in
start
/tmp/tmpkkr03214sw1.pdf
2024-09-26 09:45:07.994 | INFO | magic_pdf.libs.pdf_check:detect_invalid_chars:57 - cid_count: 0, text_len: 6, cid_chars_radio: 0.0
2024-09-26 09:45:07.994 | 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: True, by_invalid_chars: True
2024-09-26 09:45:15.442 | INFO | magic_pdf.model.pdf_extract_kit:__init__:180 - DocAnalysis init, this may take some times. apply_layout: True, apply_formula: True, apply_ocr: True, apply_table: False
2024-09-26 09:45:15.442 | INFO | magic_pdf.model.pdf_extract_kit:__init__:188 - using device: cuda
2024-09-26 09:45:15.442 | INFO | magic_pdf.model.pdf_extract_kit:__init__:190 - using models_dir: /src/models
CustomVisionEncoderDecoderModel init
CustomMBartForCausalLM init
CustomMBartDecoder init
[09/26 09:45:34 detectron2]: Rank of current process: 0. World size: 1
[09/26 09:45:35 detectron2]: Environment info:
------------------------------- ------------------------------------------------------------------------------------
sys.platform linux
Python 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0]
numpy 1.26.4
detectron2 0.6 @/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/detectron2
Compiler GCC 11.4
CUDA compiler not available
DETECTRON2_ENV_MODULE <not set>
PyTorch 2.3.1+cu121 @/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/torch
PyTorch debug build False
torch._C._GLIBCXX_USE_CXX11_ABI False
GPU available Yes
GPU 0 Tesla T4 (arch=7.5)
Driver version 535.104.12
CUDA_HOME /usr/local/cuda
Pillow 10.4.0
torchvision 0.18.1+cu121 @/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/torchvision
torchvision arch flags 5.0, 6.0, 7.0, 7.5, 8.0, 8.6, 9.0
fvcore 0.1.5.post20221221
iopath 0.1.9
cv2 4.6.0
------------------------------- ------------------------------------------------------------------------------------
PyTorch built with:
- GCC 9.3
- C++ Version: 201703
- Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v3.3.6 (Git Hash 86e6af5974177e513fd3fee58425e1063e7f1361)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 12.1
- NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-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
- CuDNN 8.9
- Built with CuDNN 8.9.2
- Magma 2.6.1
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, 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=1, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,
[09/26 09:45:35 detectron2]: Command line arguments: {'config_file': '/root/.pyenv/versions/3.10.15/lib/python3.10/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', '/src/models/Layout/model_final.pth']}
[09/26 09:45:35 detectron2]: Contents of args.config_file=/root/.pyenv/versions/3.10.15/lib/python3.10/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
[09/26 09:45:37 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from /src/models/Layout/model_final.pth ...
[09/26 09:45:37 fvcore.common.checkpoint]: [Checkpointer] Loading from /src/models/Layout/model_final.pth ...
download https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_infer.tar to /root/.paddleocr/whl/det/ch/ch_PP-OCRv4_det_infer/ch_PP-OCRv4_det_infer.tar
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download https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_rec_infer.tar to /root/.paddleocr/whl/rec/ch/ch_PP-OCRv4_rec_infer/ch_PP-OCRv4_rec_infer.tar
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download https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar to /root/.paddleocr/whl/cls/ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.tar
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2024-09-26 09:46:35.967 | INFO | magic_pdf.model.pdf_extract_kit:__init__:248 - DocAnalysis init done!
2024-09-26 09:46:35.968 | INFO | magic_pdf.model.doc_analyze_by_custom_model:custom_model_init:98 - model init cost: 87.97307825088501
2024-09-26 09:46:39.620 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.91
0: 1888x1504 14 embeddings, 237.6ms
Speed: 21.7ms preprocess, 237.6ms inference, 1.8ms postprocess per image at shape (1, 3, 1888, 1504)
2024-09-26 09:46:41.567 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 14, mfr time: 0.72
2024-09-26 09:47:03.059 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 21.48
2024-09-26 09:47:04.696 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.64
0: 1888x1344 12 embeddings, 217.7ms
Speed: 18.7ms preprocess, 217.7ms inference, 1.7ms postprocess per image at shape (1, 3, 1888, 1344)
2024-09-26 09:47:05.967 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 12, mfr time: 0.85
2024-09-26 09:47:28.866 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 22.88
2024-09-26 09:47:30.793 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.93
0: 1888x1376 1 embedding, 223.2ms
Speed: 24.1ms preprocess, 223.2ms inference, 1.8ms postprocess per image at shape (1, 3, 1888, 1376)
2024-09-26 09:47:31.647 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 1, mfr time: 0.58
2024-09-26 09:48:00.164 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 28.5
2024-09-26 09:48:01.953 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.79
0: 1888x1344 3 embeddings, 215.8ms
Speed: 20.7ms preprocess, 215.8ms inference, 1.4ms postprocess per image at shape (1, 3, 1888, 1344)
2024-09-26 09:48:02.637 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 3, mfr time: 0.39
2024-09-26 09:48:28.050 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 25.4
2024-09-26 09:48:30.080 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 2.03
0: 1888x1280 1 embedding, 204.6ms
Speed: 19.8ms preprocess, 204.6ms inference, 2.0ms postprocess per image at shape (1, 3, 1888, 1280)
2024-09-26 09:48:30.646 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 1, mfr time: 0.32
2024-09-26 09:49:09.381 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 38.72
2024-09-26 09:49:11.338 | INFO | magic_pdf.model.pdf_extract_kit:__call__:259 - layout detection cost: 1.96
0: 1888x1408 2 embeddings, 235.1ms
Speed: 23.4ms preprocess, 235.1ms inference, 1.5ms postprocess per image at shape (1, 3, 1888, 1408)
2024-09-26 09:49:12.379 | INFO | magic_pdf.model.pdf_extract_kit:__call__:289 - formula nums: 2, mfr time: 0.74
2024-09-26 09:49:46.451 | INFO | magic_pdf.model.pdf_extract_kit:__call__:372 - ocr cost: 34.06
2024-09-26 09:49:46.452 | INFO | magic_pdf.model.doc_analyze_by_custom_model:doc_analyze:136 - doc analyze cost: 188.74599361419678
2024-09-26 09:49:47.552 | INFO | magic_pdf.pipe.UNIPipe:pipe_mk_uni_format:48 - uni_pipe mk content list finished
2024-09-26 09:49:47.567 | INFO | magic_pdf.pipe.UNIPipe:pipe_mk_markdown:53 - uni_pipe mk mm_markdown finished
end