#!/bin/bash
# Generic chain driver for the video target preprocessing pipeline.
#
# Usage:
#   WORK=/path/to/workdir SKIP_PATTERN='ct_src_(0001[015]|005[0-9]|006[0-9])\.mp4' \
#     bash run_video_pipeline.sh > /opt/face-sets/work/logs/<name>.log 2>&1
#
# Required env vars:
#   WORK         per-batch workdir (will hold scenes/, queue.json, results.jsonl, plan.json, review/)
#
# Optional env vars:
#   INPUT_DIR    default /mnt/x/src/vd
#   OUTPUT_DIR   default /mnt/x/src/vd/ct
#   FILTER_FROM  basename floor; only files with name >= this go in (e.g. ct_src_00050.mp4)
#   SKIP_PATTERN regex of basenames to exclude (Python `re` syntax). Applied AFTER FILTER_FROM.
#   MAX_DUR      score --max-dur (default 120)
#   IDENTITY     "yes" to enable identity tagging; default "no"
#   SIDECAR      "yes" to emit <uuid>.json provenance sidecars; default "no"

set -e

: ${WORK:?WORK env var must point at a workdir}
: ${INPUT_DIR:=/mnt/x/src/vd}
: ${OUTPUT_DIR:=/mnt/x/src/vd/ct}
: ${MAX_DUR:=120}
: ${IDENTITY:=no}
: ${SIDECAR:=no}

mkdir -p "$WORK" "$WORK/scenes"

PY_WSL=/home/peter/face_sort_env/bin/python
PY_WIN="/mnt/c/face_embed_venv/Scripts/python.exe"
PIPELINE=/opt/face-sets/work/video_target_pipeline.py
WORKER=/opt/face-sets/work/video_face_worker.py
INVENTORY_FULL=/opt/face-sets/work/video_preprocess/inventory_full.json

ts() { date +"%Y-%m-%d %H:%M:%S"; }
log() { echo "[$(ts)] [$PHASE] $*"; }

PHASE="setup"
log "STARTED — host=$(hostname) pid=$$ work=$WORK"
log "config: input=$INPUT_DIR output=$OUTPUT_DIR filter_from=${FILTER_FROM:-<none>} skip_pattern=${SKIP_PATTERN:-<none>} max_dur=$MAX_DUR identity=$IDENTITY sidecar=$SIDECAR"

PHASE="inventory"
log "building subset inventory"
T0=$(date +%s)
# rebuild full inventory if missing
if [ ! -f "$INVENTORY_FULL" ]; then
    log "(no full inventory cached — running fresh scan)"
    $PY_WSL $PIPELINE scan --input "$INPUT_DIR" --output-dir "$OUTPUT_DIR" --out "$INVENTORY_FULL"
fi
$PY_WSL <<EOF
import json, re
from pathlib import Path
inv = json.load(open('$INVENTORY_FULL'))
subset = list(inv['videos'])
filter_from = '${FILTER_FROM}'
skip_pat = '${SKIP_PATTERN}'
if filter_from:
    subset = [v for v in subset if Path(v['path']).name >= filter_from]
if skip_pat:
    pat = re.compile(skip_pat)
    subset = [v for v in subset if not pat.search(Path(v['path']).name)]
subset.sort(key=lambda v: v['path'])
inv['videos'] = subset
json.dump(inv, open('$WORK/inventory.json','w'), indent=2)
total_dur = sum(v.get('duration_s', 0) for v in inv['videos'] if 'error' not in v)
print(f'  {len(inv["videos"])} videos, total {total_dur/3600:.2f}h input')
EOF
log "done in $(($(date +%s)-T0))s"

PHASE="scenes"
log "PySceneDetect AdaptiveDetector across all videos (cached entries skipped)"
T0=$(date +%s)
$PY_WSL $PIPELINE scenes --inventory "$WORK/inventory.json" --out-dir "$WORK/scenes"
log "done in $(($(date +%s)-T0))s"

PHASE="stage"
log "building frame queue @ 2 fps within scenes"
T0=$(date +%s)
$PY_WSL $PIPELINE stage --inventory "$WORK/inventory.json" --scenes-dir "$WORK/scenes" --out "$WORK/queue.json"
log "done in $(($(date +%s)-T0))s"

PHASE="worker"
log "Windows DML face detect+embed (resumable; the slow one)"
T0=$(date +%s)
$PY_WIN $WORKER "$WORK/queue.json" "$WORK/results.json"
log "done in $(($(date +%s)-T0))s"

PHASE="merge"
log "ingesting worker output (jsonl)"
T0=$(date +%s)
$PY_WSL $PIPELINE merge --results "$WORK/results.json" --out "$WORK/frames.json"
log "done in $(($(date +%s)-T0))s"

PHASE="track"
log "stitching detections into tracks"
T0=$(date +%s)
$PY_WSL $PIPELINE track --frames "$WORK/frames.json" --scenes-dir "$WORK/scenes" \
  --inventory "$WORK/inventory.json" --out "$WORK/tracks.json"
log "done in $(($(date +%s)-T0))s"

PHASE="score"
log "scoring with relaxed gates + max-dur=$MAX_DUR identity=$IDENTITY"
T0=$(date +%s)
ID_FLAG=""
if [ "$IDENTITY" != "yes" ]; then ID_FLAG="--no-identity"; fi
$PY_WSL $PIPELINE score --tracks "$WORK/tracks.json" --inventory "$WORK/inventory.json" \
  --out "$WORK/plan.json" --max-dur "$MAX_DUR" $ID_FLAG
log "done in $(($(date +%s)-T0))s"

PHASE="cut"
log "ffmpeg stream-copy into per-source subfolders (no --clean)"
T0=$(date +%s)
SIDECAR_FLAG=""
if [ "$SIDECAR" = "yes" ]; then SIDECAR_FLAG="--write-sidecar"; fi
$PY_WSL $PIPELINE cut --plan "$WORK/plan.json" --output-dir "$OUTPUT_DIR" $SIDECAR_FLAG
log "done in $(($(date +%s)-T0))s"

PHASE="report"
log "rendering HTML"
T0=$(date +%s)
$PY_WSL $PIPELINE report --plan "$WORK/plan.json" --output-dir "$OUTPUT_DIR" --out "$WORK/review"
log "done in $(($(date +%s)-T0))s"

PHASE="done"
log "PIPELINE COMPLETE — review at file://$WORK/review/index.html"