47 lines
1.9 KiB
Bash
Executable file
47 lines
1.9 KiB
Bash
Executable file
#!/usr/bin/env bash
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# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Get COCO 2017 data sets
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if [ -z $1 ]; then echo "Docker container name is missing" && exit 1; fi
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CONTAINER=$1
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COCO_DIR=${2:-"/data"}
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CHECKPOINT_DIR=${3:-"/checkpoints"}
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mkdir $COCO_DIR 2> /dev/null;
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chmod 777 $COCO_DIR
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cd $COCO_DIR
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curl -O http://images.cocodataset.org/zips/train2017.zip; unzip train2017.zip
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curl -O http://images.cocodataset.org/zips/val2017.zip; unzip val2017.zip
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curl -O http://images.cocodataset.org/annotations/annotations_trainval2017.zip; unzip annotations_trainval2017.zip
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# Download backbone checkpoint
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mkdir $CHECKPOINT_DIR 2> /dev/null;
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chmod 777 $CHECKPOINT_DIR
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cd $CHECKPOINT_DIR
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wget http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz
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tar -xzf resnet_v1_50_2016_08_28.tar.gz
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mkdir resnet_v1_50
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mv resnet_v1_50.ckpt resnet_v1_50/model.ckpt
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nvidia-docker run --rm -it -u 123 -v $COCO_DIR:/data $CONTAINER bash -c '
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cd /data
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# Create TFRecords
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python /workdir/models/research/object_detection/dataset_tools/create_coco_tf_record.py \
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--train_image_dir=`pwd`"/train2017" \
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--val_image_dir=`pwd`"/val2017" \
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--val_annotations_file=`pwd`"/annotations/instances_val2017.json" \
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--train_annotations_file=`pwd`"/annotations/instances_train2017.json" \
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--testdev_annotations_file=`pwd`"/annotations/instances_val2017.json" \
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--test_image_dir=`pwd`"/val2017" \
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--output_dir=`pwd`'
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