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rename datasets.md
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@ -15,11 +15,7 @@ RUN apt-get update && apt-get install -y git ninja-build libglib2.0-0 libsm6 lib
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RUN conda clean --all
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RUN conda clean --all
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RUN pip install mmcv-full==1.2.6+torch1.5.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
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RUN pip install mmcv-full==1.2.6+torch1.5.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
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RUN git clone https://github.com/open-mmlab/mmdetection.git /mmdet
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RUN pip install mmdet==2.9.0
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WORKDIR /mmdet
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RUN git checkout -b v2.9.0 v2.9.0
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RUN pip install -r requirements.txt
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RUN pip install .
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RUN git clone https://github.com/open-mmlab/mmocr.git /mmocr
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RUN git clone https://github.com/open-mmlab/mmocr.git /mmocr
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WORKDIR /mmocr
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WORKDIR /mmocr
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@ -37,7 +37,7 @@ It will save both the prediction results and visualized images to `${RESULTS_DIR
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### Test a Dataset
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### Test a Dataset
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MMOCR implements **distributed** testing with `MMDistributedDataParallel`. (Please refer to [datasets.md](datasets.md) to prepare your datasets)
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MMOCR implements **distributed** testing with `MMDistributedDataParallel`. (Please refer to [dataset.md](dataset.md) to prepare your datasets)
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#### Test with Single/Multiple GPUs
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#### Test with Single/Multiple GPUs
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@ -78,7 +78,7 @@ You can check [slurm_test.sh](https://github.com/open-mmlab/mmocr/blob/master/to
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## Train a Model
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## Train a Model
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MMOCR implements **distributed** training with `MMDistributedDataParallel`. (Please refer to [datasets.md](datasets.md) to prepare your datasets)
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MMOCR implements **distributed** training with `MMDistributedDataParallel`. (Please refer to [dataset.md](dataset.md) to prepare your datasets)
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All outputs (log files and checkpoints) will be saved to a working directory specified by `work_dir` in the config file.
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All outputs (log files and checkpoints) will be saved to a working directory specified by `work_dir` in the config file.
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@ -23,7 +23,7 @@ Welcome to MMOCR's documentation!
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:maxdepth: 2
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:maxdepth: 2
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:caption: Datasets
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:caption: Datasets
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datasets.md
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dataset.md
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.. toctree::
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.. toctree::
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:maxdepth: 2
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:maxdepth: 2
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@ -129,7 +129,7 @@ docker run --gpus all --shm-size=8g -it -v {DATA_DIR}:/mmocr/data mmocr
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## Prepare Datasets
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## Prepare Datasets
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It is recommended to symlink the dataset root to `mmocr/data`. Please refer to [datasets.md](datasets.md) to prepare your datasets.
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It is recommended to symlink the dataset root to `mmocr/data`. Please refer to [dataset.md](dataset.md) to prepare your datasets.
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If your folder structure is different, you may need to change the corresponding paths in config files.
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If your folder structure is different, you may need to change the corresponding paths in config files.
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The `mmocr` folder is organized as follows:
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The `mmocr` folder is organized as follows:
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@ -85,7 +85,7 @@ modelzoo = f"""
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* Number of papers: {len(allpapers)}
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* Number of papers: {len(allpapers)}
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{countstr}
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{countstr}
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For supported datasets, see [datasets overview](datasets.md).
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For supported datasets, see [datasets overview](dataset.md).
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{msglist}
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{msglist}
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"""
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"""
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