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valid_age_gender.sh
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valid_age_gender.sh
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#!/usr/bin/env bash
# inference utk
python3 eval_pretrained.py \
--dataset_images data/utk/images \
--dataset_annotations data/utk/annotation \
--dataset_name utk \
--batch-size 512 \
--checkpoint pretrained/model_imdb_cross_person_4.24_99.46.pth.tar \
--split valid \
--half \
--with-persons \
--device "cuda:0"
# inference fairface
python3 eval_pretrained.py \
--dataset_images data/FairFace/fairface-img-margin125-trainval \
--dataset_annotations data/FairFace/annotations \
--dataset_name fairface \
--batch-size 512 \
--checkpoint pretrained/model_imdb_cross_person_4.24_99.46.pth.tar \
--split val \
--half \
--with-persons \
--device "cuda:0"
# inference adience
python3 eval_pretrained.py \
--dataset_images data/adience/faces \
--dataset_annotations data/adience/annotations \
--dataset_name adience \
--batch-size 512 \
--checkpoint pretrained/model_imdb_cross_person_4.24_99.46.pth.tar \
--split adience \
--half \
--with-persons \
--device "cuda:0"
# inference agedb
python3 eval_pretrained.py \
--dataset_images data/agedb/AgeDB \
--dataset_annotations data/agedb/annotation \
--dataset_name agedb \
--batch-size 512 \
--checkpoint pretrained/model_imdb_cross_person_4.24_99.46.pth.tar \
--split 0,1,2,3,4,5,6,7,8,9 \
--half \
--device "cuda:0"