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runEval.sh
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#!/bin/bash
#SBATCH --job-name=eval-classifier
#SBATCH -n 1
#SBATCH --time 0-00:10:00
#SBATCH --mem 30G
#SBATCH --mail-type=END,FAIL,TIME_LIMIT_90
#SBATCH -o log.%j
PYTHONPATH=pyutil: python \
classifierEval.py \
`#__________________________________________________`\
`# Path to model to be evaluated (supply on command line)`\
--classNN ${1} \
`#__________________________________________________`\
`# Path to raw validation input data`\
--validationData "PATH TO VALIDATION/TEST DATA" \
--normFactorVal1 1e-10 \
--pxRes 64 \
`#__________________________________________________`\
`# or alternatively to precomputed binary blob`\
`# (see pyutil/parseNNArgs.py for more details)`\
`#--loadValBlob "PATH TO VALIDATION/TEST NUMPY BLOB DATA" `\
`#__________________________________________________`\
`# How many images to classifier at once (depends on your GPU)`\
--miniBatchSize 64 \
`#__________________________________________________`\
`# Threshold for classification probability to compute confusion matrix`\
--threshold 0.5