dtourolle
b26c66dcce
make_figures.py gains the DE-landscape, calibration, and per-film leave-one-out holdout figures used by the experiment log. regen_frame_examples.sh replays all nine films with the shipped learned-boundary flood config and draws GT-aware TP/FP/FN frames, so every annotated image in the docs is reproducible.
45 lines
2.4 KiB
Bash
Executable File
45 lines
2.4 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Regenerate annotated TP/FP/FN frame examples for ALL 9 films against the current
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# opencv5 pipeline (learned-boundary flood, shipped config). Replays each film with
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# --raw-out for bboxes, then dump_error_frames.py draws GT-aware boxes
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# (green TP / red FP / orange unknown / blue FN panel). Frames land in
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# experiments/dump_review/<slug>/ (regenerable; gitignored). Hand-pick the ones a
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# doc needs from there.
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set -uo pipefail
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REPO="/home/dtourolle/Development/scene-actor-extraction"; cd "$REPO"
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export MIOPEN_USER_DB_PATH="$HOME/.cache/miopen-sae"
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GAL=experiments/galleries/gallery_LVFace-B_Glint360K.h5
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LUT=experiments/file-lut.json
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CFG=(--prob-threshold 0.485 --ownership-logodds 1.72 --track-extinction-sec 31
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--track-alpha 0.435 --evidence-rho-max 0.204 --evidence-admit-below 0.784
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--match-prior 0.433 --expand-band-lo 0.804 --expand-band-hi 0.952
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--expand-gallery --presence-mode flood)
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mapfile -t ROWS < <(python3 -c '
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import json
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for f in json.load(open("experiments/manifests/films_LVFace_opencv5.json")):
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print(f["slug"]+"\t"+f["xray"])')
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SP=/tmp/claude-1000/-home-dtourolle-Development-scene-actor-extraction/c579f8cf-2974-4cbd-be88-afec68dbbf58/scratchpad
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for row in "${ROWS[@]}"; do
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slug="${row%%$'\t'*}"; xray="${row#*$'\t'}"
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movie="$(python3 -c "import json;print(json.load(open('$LUT'))['$slug'])")"
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echo "=== $slug ==="
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[ -f "experiments/dump_review/$slug/manifest.json" ] && { echo " exists, skip"; continue; }
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# replay the learned-boundary (LOO) dump so frames reflect true generalization
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dump="experiments/dumps/injected_loo/${slug}.h5"
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[ -f "$dump" ] || dump="experiments/dumps/LVFace-B_Glint360K_opencv5/dump_${slug}.h5"
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for try in 1 2 3; do
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timeout 280 python scripts/optimizer/replay.py --dump "$dump" --gallery "$GAL" \
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--out "$SP/${slug}_pred.json" --raw-out "$SP/${slug}_raw.jsonl" "${CFG[@]}" \
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>"$SP/${slug}_replay.log" 2>&1 && break
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echo " replay try $try failed, retrying"
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done
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[ -s "$SP/${slug}_raw.jsonl" ] || { echo " no raw output, skip"; continue; }
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python3 scripts/optimizer/dump_error_frames.py \
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--pred "$SP/${slug}_pred.json" --raw "$SP/${slug}_raw.jsonl" \
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--xray "$xray" --movie "$movie" --gallery "$GAL" \
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--out-dir "experiments/dump_review/$slug" --n-per-bucket 4 \
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>"$SP/${slug}_frames.log" 2>&1
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echo " $(grep -oE 'wrote [0-9]+ frames' "$SP/${slug}_frames.log" | tail -1)"
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done
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echo "=== DONE ==="
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