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eval_eschernet.sh
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eval_eschernet.sh
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#!/bin/bash
# bash script to evaluate the model
# TODO ################### Chose CaPE type ##########################
# 6DoF
cape_type="6DoF"
pretrained_model="kxic/eschernet-6dof"
## 4DoF
#cape_type="4DoF"
#pretrained_model="kxic/eschernet-4dof"
################### Chose CaPE type ##########################
# TODO ################### Chose data type ##########################
# demo
data_type="GSO25"
T_ins=(1 2 3 5 10)
data_dir="./demo/GSO30"
## GSO
#data_type="GSO25" # GSO25, GSO3D, GSO100, NeRF, RTMV
#T_ins=(1 2 3 5 10)
#data_dir="/home/xin/data/EscherNet/Data/GSO30/"
## RTMV
#data_type="RTMV"
#T_ins=(1 2 3 5 10)
#data_dir="/home/xin/data/RTMV/40_scenes/"
## NeRF
#data_type="NeRF"
#T_ins=(1 2 3 5 10 20 50 100)
#data_dir="/home/xin/data/nerf/nerf_synthetic"
## Real World Franka Recordings
#data_type="Franka"
#T_ins=(5)
#data_dir="/home/xin/data/EscherNet/Data/Franka16/"
## MVDream, 4 views to 100
#data_type='MVDream'
#T_ins=(4)
#data_dir="/home/xin/data/EscherNet/Data/MVDream/"
## Text2Img, 1 view to 100
#data_type='Text2Img'
#T_ins=(1)
#data_dir="/home/xin/data/EscherNet/Data/Text2Img/"
################### Chose data type ##########################
# run
for T_in in "${T_ins[@]}"; do
python eval_eschernet.py --pretrained_model_name_or_path "$pretrained_model" \
--data_dir "$data_dir" \
--data_type "$data_type" \
--cape_type "$cape_type" \
--T_in "$T_in"
done