| #!/bin/bash |
| set -e |
| source /root/miniconda3/etc/profile.d/conda.sh |
|
|
| ROOT=/root/autodl-tmp/SplatAtlas |
| ITER=30000 |
|
|
| |
| declare -A ENV_MAP |
| declare -A CODE_MAP |
|
|
| ENV_MAP[lod_gs]="/root/autodl-tmp/envs/lod_gs" |
| CODE_MAP[lod_gs]="/root/autodl-tmp/LOD_GS" |
|
|
| ENV_MAP[coadaptgs]="/root/autodl-tmp/envs/co_adaptation_3dgs" |
| CODE_MAP[coadaptgs]="/root/autodl-tmp/CoAdaptGS" |
|
|
| get_source_res() { |
| case "$1" in |
| auditorium|ballroom|barn|caterpillar|courtroom|lighthouse|museum|palace|playground|temple|train|truck) |
| echo "/root/autodl-tmp/dataset/tnt/$1 2" ;; |
| bicycle|flowers|garden|stump|treehill) |
| echo "/root/autodl-tmp/dataset/360/$1 4" ;; |
| bonsai|counter|kitchen|room) |
| echo "/root/autodl-tmp/dataset/360/$1 2" ;; |
| Chair|Drums|Ficus|Hotdog|Lego|Materials|Mic|Ship) |
| echo "/root/autodl-tmp/dataset/Synthetic_NeRF_Verified/Synthetic_NeRF/$1 1" ;; |
| DrJohnson|Playroom) |
| echo "/root/autodl-tmp/dataset/deepblending_clean/$1 1" ;; |
| *) |
| echo ""; return 1 ;; |
| esac |
| } |
|
|
| MISSING=( |
| "coadaptgs auditorium" |
| "coadaptgs ballroom" |
| "coadaptgs barn" |
| "coadaptgs caterpillar" |
| "coadaptgs courtroom" |
| "coadaptgs lighthouse" |
| "coadaptgs museum" |
| "coadaptgs palace" |
| "coadaptgs playground" |
| "coadaptgs temple" |
| "coadaptgs train" |
| "coadaptgs truck" |
| "coadaptgs bicycle" |
| "coadaptgs bonsai" |
| "coadaptgs counter" |
| "coadaptgs flowers" |
| "coadaptgs garden" |
| "coadaptgs kitchen" |
| "coadaptgs room" |
| "coadaptgs stump" |
| "coadaptgs treehill" |
| "coadaptgs DrJohnson" |
| "coadaptgs Playroom" |
| "lod_gs Chair" |
| "lod_gs Drums" |
| "lod_gs Ficus" |
| "lod_gs Hotdog" |
| "lod_gs Lego" |
| "lod_gs Materials" |
| "lod_gs Mic" |
| "lod_gs Ship" |
| ) |
|
|
| run_step() { |
| local name="$1" |
| local cmd="$2" |
| echo " [Step] $name ..." |
| if eval "$cmd"; then |
| echo " [OK]" |
| return 0 |
| else |
| echo " [FAIL]" |
| return 1 |
| fi |
| } |
|
|
| for entry in "${MISSING[@]}"; do |
| read -r method scene <<< "$entry" |
| env_path="${ENV_MAP[$method]}" |
| code_root="${CODE_MAP[$method]}" |
| if [ -z "$env_path" ] || [ -z "$code_root" ]; then |
| echo "Unknown method or code root for $method"; continue |
| fi |
|
|
| read -r source_path resolution < <(get_source_res "$scene") |
| if [ -z "$source_path" ]; then |
| echo "Skipping $method/$scene: unknown dataset"; continue |
| fi |
|
|
| model_path="$ROOT/outputs/${method}_${scene}" |
| ply_path="$model_path/point_cloud/iteration_${ITER}/point_cloud.ply" |
| if [ ! -f "$ply_path" ]; then |
| echo "Skipping $method/$scene: PLY not found"; continue |
| fi |
|
|
| render_dir="$model_path/renders_test_${ITER}" |
| gt_dir="$model_path/gt_test_${ITER}" |
| render_flag="$model_path/render_complete_${ITER}.flag" |
|
|
| png_count=$(find "$render_dir" -maxdepth 1 -name "*.png" 2>/dev/null | wc -l) |
| if [ "$png_count" -eq 0 ]; then |
| echo "=== $method / $scene (res=$resolution) - RENDER ===" |
| rm -rf "$render_dir" "$gt_dir" |
| else |
| echo "=== $method / $scene - renders exist ($png_count pngs) ===" |
| fi |
|
|
| conda activate "$env_path" |
|
|
| |
| export PYTHONPATH="${code_root}:${ROOT}:${PYTHONPATH:+:$PYTHONPATH}" |
|
|
| if [ "$png_count" -eq 0 ]; then |
| run_step "Render" " |
| python $ROOT/scripts/main_render.py \ |
| --method $method \ |
| --source_path $source_path \ |
| --model_path $model_path \ |
| --iteration $ITER \ |
| --resolution $resolution |
| " || continue |
| fi |
|
|
| metrics_json="$model_path/metrics_test_iter${ITER}.json" |
| if [ ! -f "$metrics_json" ]; then |
| run_step "Eval" " |
| python $ROOT/ufd_evalkit/run_eval.py \ |
| --method $method \ |
| --scene $scene \ |
| --render_dir $render_dir \ |
| --gt_dir $gt_dir \ |
| --ply_path $ply_path \ |
| --output_json $metrics_json \ |
| --colmap_dir $source_path |
| " || continue |
| else |
| echo " [Metrics json already exists]" |
| fi |
|
|
| conda deactivate |
| done |
|
|
| echo "All done. Now re-run fix_phase5a_table.py to update the CSV." |
|
|
