perf: run waveform ffmpeg at low priority so it yields to mpv on load

The first load of a file decodes the whole audio track in a background
thread; nice'ing it (os.nice(15)) reduces disk/CPU contention with mpv
during the initial open. Result is cached, so subsequent loads are fast.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

8cut.sh

@@ -3,6 +3,7 @@
 SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
 ENV_NAME="8cut"
 CONDA_PREFIX_BASE="/media/p5/miniforge3"
+export LD_PRELOAD=/usr/lib/libstdc++.so.6
 
 # 1. Try .venv in project dir
 if [ -f "$SCRIPT_DIR/.venv/bin/activate" ]; then

core/audio_scan.py

@@ -67,7 +67,7 @@ _EMBED_MODELS = {
     "EAT":                 768,
     "EAT_LARGE":          1024,
 }
-_DEFAULT_EMBED_MODEL = "WAV2VEC2_BASE"
+_DEFAULT_EMBED_MODEL = "EAT_LARGE"
 
 _BEATS_CHECKPOINT = os.path.join(
     _DL_CACHE_DIR, "huggingface", "hub",
@@ -674,9 +674,11 @@ def restore_model_version(version_path: str, profile_name: str = "default",
 
 
 def list_trained_models(profile_name: str = "default") -> list[str]:
-    """Return embedding model names that have a trained .joblib for *profile_name*.
+    """Return embedding model keys that have a trained .joblib for *profile_name*.
 
-    Looks for files matching ``{profile}_{MODEL}.joblib`` in the models dir.
+    Looks for files matching ``{profile}_{KEY}.joblib`` in the models dir.
+    KEY is either a bare embed model name (e.g. ``EAT_LARGE``) or
+    ``{MODEL}_{name}`` for user-named variants.
     """
     prefix = f"{profile_name}_"
     suffix = ".joblib"
@@ -685,13 +687,17 @@ def list_trained_models(profile_name: str = "default") -> list[str]:
         return result
     for fname in os.listdir(_MODEL_DIR):
         if fname.startswith(prefix) and fname.endswith(suffix):
-            model_name = fname[len(prefix):-len(suffix)]
-            if model_name in _EMBED_MODELS:
-                result.append(model_name)
+            key = fname[len(prefix):-len(suffix)]
+            if key in _EMBED_MODELS:
+                result.append(key)
+            else:
+                for m in _EMBED_MODELS:
+                    if key.startswith(m + "_"):
+                        result.append(key)
+                        break
     # Also check legacy {profile}.joblib
     legacy = os.path.join(_MODEL_DIR, f"{profile_name}.joblib")
     if os.path.exists(legacy) and not result:
-        # Legacy model — we don't know the embed model, but it's usable
         result.append("")
     return sorted(result)
 

core/db.py

@@ -1,4 +1,5 @@
 import os
+import re
 import sqlite3
 import threading
 from datetime import datetime, timezone
@@ -7,6 +8,12 @@ from pathlib import Path
 from .paths import _log
 
 
+def _extract_m_number(output_path: str) -> int | None:
+    """Extract the manual export number from a path like clip_001_m3_0.mp4."""
+    m = re.search(r'_m(\d+)[_.]', os.path.basename(output_path))
+    return int(m.group(1)) if m else None
+
+
 class ProcessedDB:
     _SCHEMA_VERSION = 4  # bump when schema changes
 
@@ -46,6 +53,7 @@ class ProcessedDB:
                 "  crop_center     REAL    NOT NULL DEFAULT 0.5,"
                 "  format          TEXT    NOT NULL DEFAULT 'MP4',"
                 "  clip_count      INTEGER NOT NULL DEFAULT 3,"
+                "  clip_duration   REAL    NOT NULL DEFAULT 8.0,"
                 "  spread          REAL    NOT NULL DEFAULT 3.0,"
                 "  profile         TEXT    NOT NULL DEFAULT 'default',"
                 "  source_path     TEXT    NOT NULL DEFAULT '',"
@@ -63,6 +71,7 @@ class ProcessedDB:
                 "crop_center":    "REAL NOT NULL DEFAULT 0.5",
                 "format":         "TEXT NOT NULL DEFAULT 'MP4'",
                 "clip_count":     "INTEGER NOT NULL DEFAULT 3",
+                "clip_duration":  "REAL NOT NULL DEFAULT 8.0",
                 "spread":         "REAL NOT NULL DEFAULT 3.0",
                 "profile":        "TEXT NOT NULL DEFAULT 'default'",
                 "source_path":    "TEXT NOT NULL DEFAULT ''",
@@ -232,7 +241,8 @@ class ProcessedDB:
             label: str = "", category: str = "",
             short_side: int | None = None, portrait_ratio: str = "",
             crop_center: float = 0.5, fmt: str = "MP4",
-            clip_count: int = 3, spread: float = 3.0,
+            clip_count: int = 3, clip_duration: float = 8.0,
+            spread: float = 3.0,
             profile: str = "default", source_path: str = "",
             scan_export: bool = False) -> None:
         if not self._enabled:
@@ -242,16 +252,60 @@ class ProcessedDB:
                 "INSERT INTO processed"
                 " (filename, start_time, output_path, label, category,"
                 "  short_side, portrait_ratio, crop_center, format,"
-                "  clip_count, spread, profile, source_path, scan_export, processed_at)"
-                " VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
+                "  clip_count, clip_duration, spread, profile, source_path,"
+                "  scan_export, processed_at)"
+                " VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
                 (filename, start_time, output_path, label, category,
                  short_side, portrait_ratio, crop_center, fmt,
-                 clip_count, spread, profile, source_path,
+                 clip_count, clip_duration, spread, profile, source_path,
                  1 if scan_export else 0,
                  datetime.now(timezone.utc).isoformat()),
             )
             self._con.commit()
 
+    def update_source_paths(self, new_dir: str,
+                            playlist_paths: list[str] | None = None,
+                            profile: str = "") -> int:
+        """Re-resolve source_path for all rows whose current path is missing.
+
+        Checks *new_dir* and *playlist_paths* by filename match.
+        Returns the number of rows updated.
+        """
+        if not self._enabled:
+            return 0
+        lookup: dict[str, str] = {}
+        if playlist_paths:
+            for p in playlist_paths:
+                lookup[os.path.basename(p)] = p
+        if new_dir and os.path.isdir(new_dir):
+            for f in os.listdir(new_dir):
+                fp = os.path.join(new_dir, f)
+                if os.path.isfile(fp):
+                    lookup[f] = fp
+        if not lookup:
+            return 0
+        query = "SELECT DISTINCT filename, source_path FROM processed"
+        params: tuple = ()
+        if profile:
+            query += " WHERE profile = ?"
+            params = (profile,)
+        rows = self._con.execute(query, params).fetchall()
+        updated = 0
+        with self._lock:
+            for fn, sp in rows:
+                if sp and os.path.exists(sp):
+                    continue
+                new_path = lookup.get(fn)
+                if new_path and os.path.isfile(new_path):
+                    self._con.execute(
+                        "UPDATE processed SET source_path = ? WHERE filename = ?",
+                        (new_path, fn),
+                    )
+                    updated += 1
+            if updated:
+                self._con.commit()
+        return updated
+
     def get_labels(self) -> list[str]:
         """Return distinct non-empty labels ordered by most recently used."""
         if not self._enabled:
@@ -278,19 +332,37 @@ class ProcessedDB:
         cur.row_factory = sqlite3.Row
         row = cur.execute(
             "SELECT label, category, short_side, portrait_ratio, crop_center, format,"
-            " clip_count, spread"
+            " clip_count, clip_duration, spread"
             " FROM processed WHERE output_path = ?",
             (output_path,),
         ).fetchone()
         return dict(row) if row else None
 
-    def delete_by_output_path(self, output_path: str) -> None:
+    def delete_by_output_path(self, output_path: str, profile: str = "") -> None:
         if not self._enabled:
             return
         with self._lock:
-            self._con.execute("DELETE FROM processed WHERE output_path = ?", (output_path,))
+            if profile:
+                self._con.execute(
+                    "DELETE FROM processed WHERE output_path = ? AND profile = ?",
+                    (output_path, profile),
+                )
+            else:
+                self._con.execute(
+                    "DELETE FROM processed WHERE output_path = ?", (output_path,),
+                )
             self._con.commit()
 
+    def is_path_used_by_other_profiles(self, output_path: str, profile: str) -> bool:
+        """Return True if *output_path* is referenced by any profile other than *profile*."""
+        if not self._enabled:
+            return False
+        row = self._con.execute(
+            "SELECT 1 FROM processed WHERE output_path = ? AND profile != ? LIMIT 1",
+            (output_path, profile),
+        ).fetchone()
+        return row is not None
+
     def get_group(self, output_path: str, profile: str = "") -> list[str]:
         """Return all output_paths sharing the same (filename, start_time, profile) as *output_path*."""
         if not self._enabled:
@@ -336,29 +408,120 @@ class ProcessedDB:
             self._con.commit()
             return paths
 
-    def _get_markers_for(self, match: str, profile: str = "default") -> list[tuple[float, int, str]]:
-        rows = self._con.execute(
-            "SELECT start_time, output_path FROM processed"
-            " WHERE filename = ? AND profile = ? AND scan_export = 0"
-            " ORDER BY start_time",
-            (match, profile),
-        ).fetchall()
-        # Deduplicate by start_time — batch exports share the same cursor.
-        seen_times: dict[float, tuple[float, int, str]] = {}
-        n = 0
-        for t, p in rows:
+    def _get_markers_for(self, match: str, profile: str = "default",
+                         export_folder: str = "") -> list[tuple[float, int, str, float]]:
+        if export_folder:
+            rows = self._con.execute(
+                "SELECT start_time, output_path, clip_duration, clip_count, spread"
+                " FROM processed"
+                " WHERE filename = ? AND profile = ? AND scan_export = 0"
+                "   AND output_path LIKE ?"
+                " ORDER BY start_time",
+                (match, profile, export_folder.rstrip("/") + "/%"),
+            ).fetchall()
+        else:
+            rows = self._con.execute(
+                "SELECT start_time, output_path, clip_duration, clip_count, spread"
+                " FROM processed"
+                " WHERE filename = ? AND profile = ? AND scan_export = 0"
+                " ORDER BY start_time",
+                (match, profile),
+            ).fetchall()
+        seen_times: dict[float, tuple[float, int, str, float]] = {}
+        seq = 0
+        for t, p, dur, cnt, spr in rows:
             if t not in seen_times:
-                n += 1
-                seen_times[t] = (t, n, p)
+                seq += 1
+                num = _extract_m_number(p) or seq
+                span = (dur or 8.0) + ((cnt or 1) - 1) * (spr or 3.0)
+                seen_times[t] = (t, num, p, span)
         return list(seen_times.values())
 
-    def get_markers(self, filename: str, profile: str = "default") -> list[tuple[float, int, str]]:
-        """Return [(start_time, marker_number, output_path), ...] for exact
-        filename match, sorted by start_time. Empty list if no match.
-        Excludes scan exports (shown via scan panel instead)."""
+    def get_markers(self, filename: str, profile: str = "default",
+                    export_folder: str = "") -> list[tuple[float, int, str, float]]:
+        """Return [(start_time, marker_number, output_path, clip_span), ...]
+        for exact filename match, sorted by start_time. Empty list if no match.
+        Excludes scan exports (shown via scan panel instead).
+        If export_folder is set, only markers in that folder are returned."""
         if not self._enabled:
             return []
-        return self._get_markers_for(filename, profile)
+        return self._get_markers_for(filename, profile, export_folder)
+
+    def get_other_folder_markers(self, filename: str, profile: str = "default",
+                                export_folder: str = ""
+                                ) -> dict[str, list[tuple[float, int, str, float]]]:
+        """Return {folder_name: [(start_time, num, path, span), ...]} for
+        markers NOT in export_folder, grouped by their base export folder."""
+        if not self._enabled or not export_folder:
+            return {}
+        rows = self._con.execute(
+            "SELECT start_time, output_path, clip_duration, clip_count, spread"
+            " FROM processed"
+            " WHERE filename = ? AND profile = ? AND scan_export = 0"
+            "   AND output_path NOT LIKE ?"
+            " ORDER BY start_time",
+            (filename, profile, export_folder.rstrip("/") + "/%"),
+        ).fetchall()
+        by_folder: dict[str, list] = {}
+        for t, p, dur, cnt, spr in rows:
+            parts = p.split("/")
+            for i, part in enumerate(parts):
+                if part.startswith("vid_"):
+                    folder = "/".join(parts[:i])
+                    break
+            else:
+                folder = os.path.dirname(os.path.dirname(p))
+            by_folder.setdefault(folder, []).append((t, p, dur, cnt, spr))
+        result: dict[str, list[tuple[float, int, str, float]]] = {}
+        for folder, folder_rows in by_folder.items():
+            seen: dict[float, tuple[float, int, str, float]] = {}
+            seq = 0
+            for t, p, dur, cnt, spr in folder_rows:
+                if t not in seen:
+                    seq += 1
+                    num = _extract_m_number(p) or seq
+                    span = (dur or 8.0) + ((cnt or 1) - 1) * (spr or 3.0)
+                    seen[t] = (t, num, p, span)
+            name = os.path.basename(folder)
+            if name.endswith("_disabled"):
+                continue  # disabled clips are excluded from the timeline
+            result[name] = list(seen.values())
+        return result
+
+    def get_manual_export_groups(self, filename: str, profile: str = "default"
+                                ) -> list[dict]:
+        """Return manual (non-scan) export groups for *filename*.
+
+        Each group dict has:
+          start_time, paths (list[str] sorted), clip_count, clip_duration,
+          spread, short_side, portrait_ratio, crop_center, format, label,
+          category
+        """
+        if not self._enabled:
+            return []
+        rows = self._con.execute(
+            "SELECT start_time, output_path, clip_count, clip_duration, spread,"
+            " short_side, portrait_ratio, crop_center, format, label, category"
+            " FROM processed"
+            " WHERE filename = ? AND profile = ? AND scan_export = 0"
+            " ORDER BY start_time, output_path",
+            (filename, profile),
+        ).fetchall()
+        groups: dict[float, dict] = {}
+        for r in rows:
+            t = r[0]
+            if t not in groups:
+                groups[t] = {
+                    "start_time": t,
+                    "paths": [],
+                    "clip_count": r[2], "clip_duration": r[3],
+                    "spread": r[4],
+                    "short_side": r[5], "portrait_ratio": r[6],
+                    "crop_center": r[7], "format": r[8],
+                    "label": r[9], "category": r[10],
+                }
+            groups[t]["paths"].append(r[1])
+        return list(groups.values())
 
     def get_clip_count(self, filename: str, profile: str = "default") -> int:
         """Return total number of exported clips (including scan exports)."""
@@ -370,15 +533,235 @@ class ProcessedDB:
         ).fetchone()
         return row[0] if row else 0
 
+    def get_clip_counts_by_folder(self, filename: str,
+                                  profile: str = "default") -> dict[str, int]:
+        """Return per-export-folder clip counts for a single video.
+
+        Folder name is the grandparent dir of each clip's output_path
+        (e.g. ``mp4_doggy_clap``).
+        """
+        if not self._enabled:
+            return {}
+        rows = self._con.execute(
+            "SELECT output_path FROM processed WHERE filename = ? AND profile = ?",
+            (filename, profile),
+        ).fetchall()
+        counts: dict[str, int] = {}
+        for (op,) in rows:
+            folder = os.path.basename(os.path.dirname(os.path.dirname(op)))
+            counts[folder] = counts.get(folder, 0) + 1
+        return counts
+
+    def get_all_folder_counts(self, profile: str = "default") -> dict[str, int]:
+        """Return clip counts per export folder across all videos in *profile*.
+
+        Includes ``_disabled`` folders so callers can offer enable/disable.
+        """
+        if not self._enabled:
+            return {}
+        rows = self._con.execute(
+            "SELECT output_path FROM processed WHERE profile = ?",
+            (profile,),
+        ).fetchall()
+        counts: dict[str, int] = {}
+        for (op,) in rows:
+            folder = os.path.basename(os.path.dirname(os.path.dirname(op)))
+            counts[folder] = counts.get(folder, 0) + 1
+        return counts
+
+    def relocate_video_clips(self, filename: "str | None", profile: str,
+                             src_folder_name: str,
+                             dst_folder_name: str) -> int:
+        """Move clips from one export folder to a sibling folder.
+
+        Matches rows whose grandparent dir basename == *src_folder_name*
+        (restricted to *filename* when given, else every video in *profile*),
+        then moves each clip (and any ``.wav`` sidecar) on disk into a sibling
+        folder named *dst_folder_name*, migrates its dataset.json annotation,
+        and rewrites output_path in the DB.  Returns the number of clips moved.
+        """
+        if not self._enabled:
+            return 0
+        import shutil
+        from .annotations import remove_clip_annotation, upsert_clip_annotation
+
+        if filename is None:
+            rows = self._con.execute(
+                "SELECT id, output_path, label FROM processed WHERE profile = ?",
+                (profile,),
+            ).fetchall()
+        else:
+            rows = self._con.execute(
+                "SELECT id, output_path, label FROM processed"
+                " WHERE filename = ? AND profile = ?",
+                (filename, profile),
+            ).fetchall()
+
+        moves: list[tuple[str, str]] = []        # (old_path, new_path)
+        updates: list[tuple[str, int]] = []       # (new_path, id)
+        ann: list[tuple[str, str, str, str, str]] = []  # old_fold,new_fold,old,new,label
+        new_dirs: set[str] = set()
+        old_vid_dirs: set[str] = set()
+
+        for rid, op, label in rows:
+            vid_dir = os.path.dirname(op)
+            export_folder = os.path.dirname(vid_dir)
+            if os.path.basename(export_folder) != src_folder_name:
+                continue
+            new_export_folder = os.path.join(
+                os.path.dirname(export_folder), dst_folder_name)
+            new_vid_dir = os.path.join(new_export_folder, os.path.basename(vid_dir))
+            new_op = os.path.join(new_vid_dir, os.path.basename(op))
+            updates.append((new_op, rid))
+            new_dirs.add(new_vid_dir)
+            old_vid_dirs.add(vid_dir)
+            if os.path.exists(op):
+                moves.append((op, new_op))
+            ann.append((export_folder, new_export_folder, op, new_op, label or ""))
+
+        if not updates:
+            return 0
+
+        with self._lock:
+            for d in sorted(new_dirs):
+                os.makedirs(d, exist_ok=True)
+            for old, new in moves:
+                if os.path.exists(old) and not os.path.exists(new):
+                    shutil.move(old, new)
+                wav_old, wav_new = old + ".wav", new + ".wav"
+                if os.path.exists(wav_old) and not os.path.exists(wav_new):
+                    shutil.move(wav_old, wav_new)
+            self._con.executemany(
+                "UPDATE processed SET output_path = ? WHERE id = ?", updates)
+            self._con.commit()
+
+        # Migrate dataset.json entries (best-effort, outside the DB lock).
+        for old_fold, new_fold, old_op, new_op, label in ann:
+            remove_clip_annotation(old_fold, old_op)
+            if label:
+                upsert_clip_annotation(new_fold, new_op, label)
+
+        # Remove now-empty old vid dirs and their export folder if empty.
+        for d in sorted(old_vid_dirs):
+            try:
+                if os.path.isdir(d) and not os.listdir(d):
+                    os.rmdir(d)
+                parent = os.path.dirname(d)
+                if os.path.isdir(parent) and not os.listdir(parent):
+                    os.rmdir(parent)
+            except OSError:
+                pass
+
+        _log(f"Relocated {len(updates)} clip(s) of {filename or 'all videos'}: "
+             f"{src_folder_name} -> {dst_folder_name}")
+        return len(updates)
+
     def get_profiles(self) -> list[str]:
-        """Return distinct profile names, ordered alphabetically."""
+        """Return distinct profile names across all tables, ordered alphabetically."""
         if not self._enabled:
             return []
         rows = self._con.execute(
-            "SELECT DISTINCT profile FROM processed ORDER BY profile"
+            "SELECT DISTINCT profile FROM processed"
+            " UNION SELECT DISTINCT profile FROM scan_results"
+            " UNION SELECT DISTINCT profile FROM hard_negatives"
+            " ORDER BY profile"
         ).fetchall()
         return [r[0] for r in rows]
 
+    def duplicate_profile(self, src: str, dst: str) -> int:
+        """Copy all profile data from *src* to *dst*.
+
+        Copies processed (exports), scan_results, hard_negatives, and
+        hidden_files.  Returns total number of rows copied.
+        """
+        if not self._enabled or src == dst:
+            return 0
+        total = 0
+        with self._lock:
+            # processed (exports)
+            rows = self._con.execute(
+                "SELECT filename, start_time, output_path, label, category,"
+                " short_side, portrait_ratio, crop_center, format,"
+                " clip_count, clip_duration, spread, source_path, scan_export,"
+                " processed_at"
+                " FROM processed WHERE profile = ?", (src,),
+            ).fetchall()
+            for r in rows:
+                self._con.execute(
+                    "INSERT INTO processed"
+                    " (filename, start_time, output_path, label, category,"
+                    "  short_side, portrait_ratio, crop_center, format,"
+                    "  clip_count, clip_duration, spread, profile,"
+                    "  source_path, scan_export, processed_at)"
+                    " VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)",
+                    (*r[:12], dst, *r[12:]),
+                )
+            total += len(rows)
+            # scan_results
+            rows = self._con.execute(
+                "SELECT filename, model, start_time, end_time, score,"
+                " disabled, orig_start_time, orig_end_time, scan_timestamp"
+                " FROM scan_results WHERE profile = ?", (src,),
+            ).fetchall()
+            for r in rows:
+                self._con.execute(
+                    "INSERT INTO scan_results"
+                    " (filename, profile, model, start_time, end_time, score,"
+                    "  disabled, orig_start_time, orig_end_time, scan_timestamp)"
+                    " VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
+                    (r[0], dst, r[1], r[2], r[3], r[4], r[5], r[6], r[7], r[8]),
+                )
+            total += len(rows)
+            # hard_negatives
+            rows = self._con.execute(
+                "SELECT filename, start_time, source_path, source_model"
+                " FROM hard_negatives WHERE profile = ?", (src,),
+            ).fetchall()
+            for r in rows:
+                self._con.execute(
+                    "INSERT INTO hard_negatives"
+                    " (filename, profile, start_time, source_path, source_model)"
+                    " VALUES (?, ?, ?, ?, ?)",
+                    (r[0], dst, r[1], r[2], r[3]),
+                )
+            total += len(rows)
+            # hidden_files
+            rows = self._con.execute(
+                "SELECT filename FROM hidden_files WHERE profile = ?", (src,),
+            ).fetchall()
+            for r in rows:
+                self._con.execute(
+                    "INSERT OR IGNORE INTO hidden_files (filename, profile)"
+                    " VALUES (?, ?)",
+                    (r[0], dst),
+                )
+            total += len(rows)
+            self._con.commit()
+        return total
+
+    def count_profile_rows(self, profile: str) -> int:
+        """Return total number of rows across all tables for *profile*."""
+        if not self._enabled:
+            return 0
+        n = 0
+        for table in ("processed", "scan_results", "hard_negatives", "hidden_files"):
+            row = self._con.execute(
+                f"SELECT COUNT(*) FROM {table} WHERE profile = ?", (profile,),
+            ).fetchone()
+            n += row[0] if row else 0
+        return n
+
+    def delete_profile(self, profile: str) -> None:
+        """Delete all rows for *profile* from every table."""
+        if not self._enabled:
+            return
+        with self._lock:
+            for table in ("processed", "scan_results", "hard_negatives", "hidden_files"):
+                self._con.execute(
+                    f"DELETE FROM {table} WHERE profile = ?", (profile,),
+                )
+            self._con.commit()
+
     def get_all_export_paths(self, profile: str = "default") -> list[str]:
         """Return all unique output_path values for a given profile."""
         if not self._enabled:
@@ -418,6 +801,32 @@ class ProcessedDB:
                 pass
         return max_n
 
+    def get_scan_export_rep_paths_in_range(self, filename: str, profile: str,
+                                           start: float, end: float) -> list[str]:
+        """Return one representative output_path per distinct scan-export
+        start_time inside [start, end] for (filename, profile)."""
+        if not self._enabled:
+            return []
+        rows = self._con.execute(
+            "SELECT output_path FROM processed"
+            " WHERE filename = ? AND profile = ? AND scan_export = 1"
+            " AND start_time BETWEEN ? AND ?"
+            " GROUP BY start_time",
+            (filename, profile, start, end),
+        ).fetchall()
+        return [r[0] for r in rows]
+
+    def get_scan_export_times(self, filename: str, profile: str) -> list[float]:
+        """Return start_times of scan_export=1 rows for this file/profile."""
+        if not self._enabled:
+            return []
+        rows = self._con.execute(
+            "SELECT start_time FROM processed"
+            " WHERE filename = ? AND profile = ? AND scan_export = 1",
+            (filename, profile),
+        ).fetchall()
+        return [r[0] for r in rows]
+
     def delete_scan_exports(self, filename: str, profile: str) -> int:
         """Delete all scan_export entries for *filename* in *profile*.
 
@@ -504,13 +913,15 @@ class ProcessedDB:
         folder_names: set[str] = set()
         for (op,) in rows:
             grandparent = os.path.basename(os.path.dirname(os.path.dirname(op)))
-            if grandparent:
+            if grandparent and not grandparent.endswith("_disabled"):
                 folder_names.add(grandparent)
         return sorted(folder_names)
 
-    def get_training_data(self, profile: str, positive_folder: str,
+    def get_training_data(self, profile: str,
+                          positive_folder: "str | list[str]",
                           negative_folder: str = "",
                           fallback_video_dir: str = "",
+                          playlist_paths: list[str] | None = None,
                           include_scan_exports: bool = False,
                           use_hard_negatives: bool = True,
                           ) -> list[tuple[str, list[float], list[float], list[float]]]:
@@ -518,18 +929,20 @@ class ProcessedDB:
 
         Args:
             profile: profile name
-            positive_folder: export folder name for positive class (e.g. "mp4_Intense")
+            positive_folder: export folder name(s) for positive class
             negative_folder: export folder name for explicit negatives (optional)
             fallback_video_dir: if source_path is empty, try filename in this dir
+            playlist_paths: loaded playlist paths to resolve filenames
             include_scan_exports: if True, include auto-exported scan clips
             use_hard_negatives: if False, skip hard negatives from scan feedback
 
         Returns:
             list of (source_video_path, positive_times, soft_times, negative_times)
-            per video.  Soft times = clips from any other non-negative folder.
+            per video.  Soft times = clips from any other non-positive/non-negative folder.
         """
         if not self._enabled:
             return []
+        pos_folders = {positive_folder} if isinstance(positive_folder, str) else set(positive_folder)
         if include_scan_exports:
             rows = self._con.execute(
                 "SELECT filename, start_time, output_path, source_path"
@@ -553,7 +966,9 @@ class ProcessedDB:
             if sp:
                 source_by_filename[fn] = sp
             grandparent = os.path.basename(os.path.dirname(os.path.dirname(op)))
-            if grandparent == positive_folder:
+            if grandparent.endswith("_disabled"):
+                continue  # disabled clips are excluded from training entirely
+            if grandparent in pos_folders:
                 pos_by_video.setdefault(fn, set()).add(st)
             elif negative_folder and grandparent == negative_folder:
                 neg_by_video.setdefault(fn, set()).add(st)
@@ -590,11 +1005,19 @@ class ProcessedDB:
                     result.append(t)
             return result
 
+        # Build filename→path lookup from playlist
+        playlist_lookup: dict[str, str] = {}
+        if playlist_paths:
+            for p in playlist_paths:
+                playlist_lookup[os.path.basename(p)] = p
+
         # Include videos that have positives OR explicit negatives
         all_videos = set(pos_by_video) | set(neg_by_video)
         result = []
         for fn in all_videos:
             sp = source_by_filename.get(fn, "")
+            if not sp or not os.path.exists(sp):
+                sp = playlist_lookup.get(fn, "")
             if not sp or not os.path.exists(sp):
                 if fallback_video_dir:
                     sp = os.path.join(fallback_video_dir, fn)
@@ -777,6 +1200,41 @@ class ProcessedDB:
             )
             self._con.commit()
 
+    def insert_scan_result(self, filename: str, profile: str, model: str,
+                           start: float, end: float, score: float,
+                           disabled: bool, orig_start: float, orig_end: float,
+                           scan_timestamp: str = "") -> int:
+        """Insert a single scan result row; returns its new id."""
+        if not self._enabled:
+            return -1
+        with self._lock:
+            cur = self._con.execute(
+                "INSERT INTO scan_results"
+                " (filename, profile, model, start_time, end_time, score,"
+                "  disabled, orig_start_time, orig_end_time, scan_timestamp)"
+                " VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
+                (filename, profile, model, start, end, score,
+                 1 if disabled else 0, orig_start, orig_end, scan_timestamp),
+            )
+            self._con.commit()
+            return int(cur.lastrowid or -1)
+
+    def update_scan_result_full(self, row_id: int, start: float, end: float,
+                                score: float, orig_start: float,
+                                orig_end: float) -> None:
+        """Update bounds, score and orig_* fields — used after merging rows."""
+        if not self._enabled:
+            return
+        with self._lock:
+            self._con.execute(
+                "UPDATE scan_results"
+                " SET start_time = ?, end_time = ?, score = ?,"
+                "     orig_start_time = ?, orig_end_time = ?"
+                " WHERE id = ?",
+                (start, end, score, orig_start, orig_end, row_id),
+            )
+            self._con.commit()
+
     def get_scan_models(self, filename: str, profile: str) -> list[str]:
         """Return model names that have scan results for this file."""
         if not self._enabled:

core/ffmpeg.py

@@ -78,6 +78,7 @@ def build_ffmpeg_command(
     crop_center: float = 0.5,
     image_sequence: bool = False,
     encoder: str = "libx264",
+    duration: float = 8.0,
 ) -> list[str]:
     # -ss before -i: fast input-seeking. Safe here because we always re-encode,
     # so there is no keyframe-alignment issue from pre-input seek.
@@ -96,7 +97,7 @@ def build_ffmpeg_command(
         "-threads", "0",
         "-ss", str(start),
         "-i", input_path,
-        "-t", "8",
+        "-t", str(duration),
     ]
 
     filters: list[str] = []
@@ -141,14 +142,15 @@ def build_ffmpeg_command(
     return cmd
 
 
-def build_audio_extract_command(input_path: str, start: float, sequence_dir: str) -> list[str]:
+def build_audio_extract_command(input_path: str, start: float, sequence_dir: str,
+                                duration: float = 8.0) -> list[str]:
     """Return an ffmpeg command that extracts audio to <sequence_dir>.wav."""
     audio_path = sequence_dir + ".wav"
     return [
         _bin("ffmpeg"), "-y",
         "-ss", str(start),
         "-i", input_path,
-        "-t", "8",
+        "-t", str(duration),
         "-vn",
         "-c:a", "pcm_s16le",
         audio_path,