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--- |
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tags: |
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- Tensorflow |
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license: apache-2.0 |
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datasets: |
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- Publaynet |
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--- |
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# Tensorpacks Cascade-RCNN with FPN and Group Normalization on ResNext32xd4-50 trained on Publaynet for Document Layout Analysis |
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The model and its training code has been mainly taken from: [Tensorpack](https://github.com/tensorpack/tensorpack/tree/master/examples/FasterRCNN) . |
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Please check: [Xu Zhong et. all. - PubLayNet: largest dataset ever for document layout analysis](https://arxiv.org/abs/1908.07836). |
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This model is different from the model used the paper. |
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The code has been adapted so that it can be used in a **deep**doctection pipeline. |
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## How this model can be used |
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This model can be used with the **deep**doctection in a full pipeline, along with table recognition and OCR. Check the general instruction following this [Get_started](https://github.com/deepdoctection/deepdoctection/blob/master/notebooks/Get_Started.ipynb) tutorial. |
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## How this model was trained. |
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To recreate the model run on the **deep**doctection framework, run: |
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```python |
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>>> import os |
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>>> from deep_doctection.datasets import DatasetRegistry |
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>>> from deep_doctection.eval import MetricRegistry |
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>>> from deep_doctection.utils import get_configs_dir_path |
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>>> from deep_doctection.train import train_faster_rcnn |
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publaynet = DatasetRegistry.get_dataset("publaynet") |
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path_config_yaml=os.path.join(get_configs_dir_path(),"tp/layout/conf_frcnn_layout.yaml") |
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path_weights = "" |
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dataset_train = publaynet |
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config_overwrite=["TRAIN.STEPS_PER_EPOCH=500","TRAIN.EVAL_PERIOD=200","TRAIN.STARTING_EPOCH=1", |
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"PREPROC.TRAIN_SHORT_EDGE_SIZE=[800,1200]","TRAIN.CHECKPOINT_PERIOD=50", |
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"BACKBONE.FREEZE_AT=0"] |
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build_train_config=["max_datapoints=335703"] |
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dataset_val = publaynet |
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build_val_config = ["max_datapoints=2000"] |
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coco_metric = MetricRegistry.get_metric("coco") |
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train_faster_rcnn(path_config_yaml=path_config_yaml, |
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dataset_train=dataset_train, |
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path_weights=path_weights, |
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config_overwrite=config_overwrite, |
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log_dir="/path/to/dir", |
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build_train_config=build_train_config, |
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dataset_val=dataset_val, |
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build_val_config=build_val_config, |
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metric=coco_metric, |
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pipeline_component_name="ImageLayoutService" |
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) |
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``` |
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## How to fine-tune this model |
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To fine tune this model, please check this [Fine-tune](https://github.com/deepdoctection/deepdoctection/blob/master/notebooks/Fine_Tune.ipynb) tutorial. |
