wehub-resource-sync
45 lines
1.8 KiB
Bash
Executable File
45 lines
1.8 KiB
Bash
Executable File
export IMAGENET_HOME=/media/Data/imagenet_data
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# Setup folders
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mkdir -p $IMAGENET_HOME/validation
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mkdir -p $IMAGENET_HOME/train
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# ###### Modification 1: set .tar files path to $IMAGENET_HOME #############
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# Extract validation and training
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tar xf $IMAGENET_HOME/ILSVRC2012_img_val.tar -C $IMAGENET_HOME/validation
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tar xf $IMAGENET_HOME/ILSVRC2012_img_train.tar -C $IMAGENET_HOME/train
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# ##########################################################################
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# Extract and then delete individual training tar files This can be pasted
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# directly into a bash command-line or create a file and execute.
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cd $IMAGENET_HOME/train
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for f in *.tar; do
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d=`basename $f .tar`
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mkdir $d
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tar xf $f -C $d
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done
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cd $IMAGENET_HOME # Move back to the base folder
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# [Optional] Delete tar files if desired as they are not needed
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rm $IMAGENET_HOME/train/*.tar
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# ###### Modification 2: Updated deprecated link #############
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# Download labels file.
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wget -O $IMAGENET_HOME/synset_labels.txt \
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https://raw.githubusercontent.com/tensorflow/models/master/research/slim/datasets/imagenet_2012_validation_synset_labels.txt
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# ############################################################
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# Process the files. Remember to get the script from github first. The TFRecords
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# will end up in the --local_scratch_dir. To upload to gcs with this method
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# leave off `nogcs_upload` and provide gcs flags for project and output_path.
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python imagenet_to_gcs.py \
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--raw_data_dir=$IMAGENET_HOME \
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--local_scratch_dir=$IMAGENET_HOME/tf_records \
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--nogcs_upload
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# ######## Modification 3: move train and validation files to root dir #######################
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mv $IMAGENET_HOME/tf_records/train* $IMAGENET_HOME/tf_records
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mv $IMAGENET_HOME/tf_records/validation* $IMAGENET_HOME/tf_records
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# ############################################################################################
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