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5767e72 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | #!/bin/bash
# Define the dimension list
dimensions=(
"subject_consistency"
"background_consistency"
"aesthetic_quality"
"imaging_quality"
"object_class"
"multiple_objects" "color"
"spatial_relationship"
"scene"
"temporal_style"
"overall_consistency"
"human_action"
"temporal_flickering"
"motion_smoothness"
"dynamic_degree"
"appearance_style")
# Corresponding folder names
folders=("subject_consistency" "scene" "overall_consistency" "overall_consistency" "object_class" "multiple_objects" "color" "spatial_relationship" "scene" "temporal_style" "overall_consistency" "human_action" "temporal_flickering" "subject_consistency" "subject_consistency" "appearance_style")
# Base path for videos
base_path='./sampled_videos/videocrafter-1' # TODO: change to local path
DEFAULT_GPUS=8
# get number of gpus
REAL_GPUS=$(nvidia-smi --query-gpu=name --format=csv,noheader | wc -l)
# min of REAL_GPUS and DEFAULT_GPUS
GPUS=$((REAL_GPUS < DEFAULT_GPUS ? REAL_GPUS : DEFAULT_GPUS))
echo "Using $GPUS GPUs"
# Loop over each dimension
for i in "${!dimensions[@]}"; do
# Get the dimension and corresponding folder
dimension=${dimensions[i]}
folder=${folders[i]}
# Construct the video path
videos_path="${base_path}/${folder}/1024x576"
echo "$dimension $videos_path"
# Run the evaluation script
torchrun --nproc_per_node=${GPUS} --standalone \
evaluate.py --videos_path $videos_path --dimension $dimension
done
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