Files
8-cut/core/db.py
T
Ethanfel 47f910644d feat: configurable clip duration, playback speed, Windows WId embedding
Add clip duration spinner (2–30s, default 8s) replacing all hardcoded
8.0 references. Store clip_duration in DB for accurate re-export span
calculations. Add x2/x4 playback speed toggle buttons. On Windows, mpv
renders directly into the widget's native window handle (WId embedding)
instead of slow FBO readback; crop overlays use a transparent child
widget. Fix _poll_render crash when player is None after closeEvent.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-28 15:18:37 +02:00

1121 lines
46 KiB
Python

import os
import sqlite3
import threading
from datetime import datetime, timezone
from pathlib import Path
from .paths import _log
class ProcessedDB:
_SCHEMA_VERSION = 4 # bump when schema changes
def __init__(self, db_path: str | None = None):
if db_path is None:
db_path = str(Path.home() / ".8cut.db")
self._path = db_path
self._lock = threading.Lock()
try:
self._con = sqlite3.connect(db_path, check_same_thread=False)
self._migrate()
self._enabled = True
_log(f"DB opened: {db_path}")
except Exception as e:
_log(f"DB unavailable: {e}")
self._con = None
self._enabled = False
def _migrate(self) -> None:
"""Create table if missing, then add any new columns for old DBs."""
cols = {
row[1]
for row in self._con.execute("PRAGMA table_info(processed)").fetchall()
}
if not cols:
# Fresh DB — create from scratch
self._con.execute(
"CREATE TABLE IF NOT EXISTS processed ("
" id INTEGER PRIMARY KEY AUTOINCREMENT,"
" filename TEXT NOT NULL,"
" start_time REAL NOT NULL,"
" output_path TEXT NOT NULL,"
" label TEXT NOT NULL DEFAULT '',"
" category TEXT NOT NULL DEFAULT '',"
" short_side INTEGER DEFAULT 512,"
" portrait_ratio TEXT NOT NULL DEFAULT '',"
" 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 '',"
" scan_export INTEGER NOT NULL DEFAULT 0,"
" processed_at TEXT NOT NULL"
")"
)
else:
# Add missing columns to legacy tables
new_cols = {
"label": "TEXT NOT NULL DEFAULT ''",
"category": "TEXT NOT NULL DEFAULT ''",
"short_side": "INTEGER DEFAULT 512",
"portrait_ratio": "TEXT NOT NULL DEFAULT ''",
"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 ''",
"scan_export": "INTEGER NOT NULL DEFAULT 0",
}
for col, typedef in new_cols.items():
if col not in cols:
self._con.execute(
f"ALTER TABLE processed ADD COLUMN {col} {typedef}"
)
self._con.execute(
"CREATE INDEX IF NOT EXISTS idx_filename ON processed(filename)"
)
self._con.execute(
"CREATE TABLE IF NOT EXISTS hidden_files ("
" filename TEXT NOT NULL,"
" profile TEXT NOT NULL DEFAULT 'default',"
" PRIMARY KEY (filename, profile)"
")"
)
self._con.execute(
"CREATE TABLE IF NOT EXISTS scan_results ("
" id INTEGER PRIMARY KEY AUTOINCREMENT,"
" filename TEXT NOT NULL,"
" profile TEXT NOT NULL DEFAULT 'default',"
" model TEXT NOT NULL,"
" start_time REAL NOT NULL,"
" end_time REAL NOT NULL,"
" score REAL NOT NULL,"
" disabled INTEGER NOT NULL DEFAULT 0,"
" orig_start_time REAL,"
" orig_end_time REAL,"
" scan_timestamp TEXT NOT NULL DEFAULT ''"
")"
)
# Migrate: add new columns to existing scan_results tables
sr_cols = {
row[1]
for row in self._con.execute("PRAGMA table_info(scan_results)").fetchall()
}
for col, typedef in [
("disabled", "INTEGER NOT NULL DEFAULT 0"),
("orig_start_time", "REAL"),
("orig_end_time", "REAL"),
("scan_timestamp", "TEXT NOT NULL DEFAULT ''"),
]:
if col not in sr_cols:
self._con.execute(
f"ALTER TABLE scan_results ADD COLUMN {col} {typedef}"
)
self._con.execute(
"CREATE INDEX IF NOT EXISTS idx_scan_file_profile_model"
" ON scan_results(filename, profile, model)"
)
self._con.execute(
"CREATE TABLE IF NOT EXISTS hard_negatives ("
" id INTEGER PRIMARY KEY AUTOINCREMENT,"
" filename TEXT NOT NULL,"
" profile TEXT NOT NULL DEFAULT 'default',"
" start_time REAL NOT NULL,"
" source_path TEXT NOT NULL DEFAULT '',"
" source_model TEXT NOT NULL DEFAULT ''"
")"
)
# Migrate: add source_model column to existing hard_negatives tables
hn_cols = {
row[1]
for row in self._con.execute("PRAGMA table_info(hard_negatives)").fetchall()
}
if "source_model" not in hn_cols:
self._con.execute(
"ALTER TABLE hard_negatives ADD COLUMN source_model TEXT NOT NULL DEFAULT ''"
)
self._con.execute(
"CREATE INDEX IF NOT EXISTS idx_hardneg_file_profile"
" ON hard_negatives(filename, profile)"
)
self._con.commit()
self._migrate_vid_folders()
def _migrate_vid_folders(self) -> None:
"""Migrate old clip_NNN group dirs → vid_NNN per-video folders.
Old layout: export_folder/clip_NNN/clip_NNN_sub.mp4
New layout: export_folder/vid_NNN/clip_NNN_sub.mp4
Rewrites output_path in DB and moves files on disk.
"""
# Check if any rows still use the old clip_NNN parent dir layout
row = self._con.execute(
"SELECT id FROM processed WHERE output_path LIKE '%/clip_%/%' LIMIT 1"
).fetchone()
if not row:
return
_log("Migrating old clip group dirs → vid folders …")
rows = self._con.execute(
"SELECT id, filename, profile, output_path FROM processed"
" ORDER BY profile, filename, output_path"
).fetchall()
# Assign vid_NNN per (profile, export_folder, filename)
vid_map: dict[tuple, str] = {}
vid_counters: dict[tuple, int] = {}
for rid, filename, profile, op in rows:
parent = os.path.dirname(op)
export_folder = os.path.dirname(parent)
key = (profile, export_folder, filename)
if key not in vid_map:
counter_key = (profile, export_folder)
n = vid_counters.get(counter_key, 1)
vid_map[key] = f"vid_{n:03d}"
vid_counters[counter_key] = n + 1
updates: list[tuple[str, int]] = []
moves: list[tuple[str, str]] = []
dirs_to_create: set[str] = set()
old_dirs: set[str] = set()
for rid, filename, profile, op in rows:
parent = os.path.dirname(op)
parent_name = os.path.basename(parent)
# Skip rows already using vid_NNN layout
if parent_name.startswith("vid_"):
continue
export_folder = os.path.dirname(parent)
key = (profile, export_folder, filename)
vid_name = vid_map[key]
new_path = os.path.join(export_folder, vid_name, os.path.basename(op))
updates.append((new_path, rid))
dirs_to_create.add(os.path.join(export_folder, vid_name))
old_dirs.add(parent)
if os.path.exists(op):
moves.append((op, new_path))
if not updates:
return
# Create vid directories
for d in sorted(dirs_to_create):
os.makedirs(d, exist_ok=True)
# Move files
import shutil
for old, new in moves:
if os.path.exists(old) and not os.path.exists(new):
shutil.move(old, new)
# Update DB
self._con.executemany(
"UPDATE processed SET output_path = ? WHERE id = ?", updates
)
self._con.commit()
# Remove empty old group directories
for d in sorted(old_dirs, reverse=True):
try:
if os.path.isdir(d) and not os.listdir(d):
os.rmdir(d)
except OSError:
pass
_log(f"Migrated {len(updates)} rows, moved {len(moves)} files to vid folders")
def add(self, filename: str, start_time: float, output_path: str,
label: str = "", category: str = "",
short_side: int | None = None, portrait_ratio: str = "",
crop_center: float = 0.5, fmt: str = "MP4",
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:
return
with self._lock:
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 (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
(filename, start_time, output_path, label, category,
short_side, portrait_ratio, crop_center, fmt,
clip_count, clip_duration, spread, profile, source_path,
1 if scan_export else 0,
datetime.now(timezone.utc).isoformat()),
)
self._con.commit()
def get_labels(self) -> list[str]:
"""Return distinct non-empty labels ordered by most recently used."""
if not self._enabled:
return []
rows = self._con.execute(
"SELECT DISTINCT label FROM processed"
" WHERE label != '' ORDER BY processed_at DESC"
).fetchall()
# Deduplicate while preserving order (DISTINCT on processed_at DESC
# may return duplicates if the same label was used multiple times).
seen: set[str] = set()
result = []
for (lbl,) in rows:
if lbl not in seen:
seen.add(lbl)
result.append(lbl)
return result
def get_by_output_path(self, output_path: str) -> dict | None:
"""Return config dict for an output_path, or None."""
if not self._enabled:
return None
cur = self._con.cursor()
cur.row_factory = sqlite3.Row
row = cur.execute(
"SELECT label, category, short_side, portrait_ratio, crop_center, format,"
" 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, profile: str = "") -> None:
if not self._enabled:
return
with self._lock:
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:
return []
row = self._con.execute(
"SELECT filename, start_time, profile FROM processed WHERE output_path = ?",
(output_path,),
).fetchone()
if not row:
return []
filename, start_time, row_profile = row
p = profile or row_profile
rows = self._con.execute(
"SELECT output_path FROM processed"
" WHERE filename = ? AND start_time = ? AND profile = ? ORDER BY output_path",
(filename, start_time, p),
).fetchall()
return [r[0] for r in rows]
def delete_group(self, output_path: str, profile: str = "") -> list[str]:
"""Delete all rows sharing the same (filename, start_time, profile) as *output_path*.
Returns list of deleted output_paths."""
if not self._enabled:
return []
with self._lock:
row = self._con.execute(
"SELECT filename, start_time, profile FROM processed WHERE output_path = ?",
(output_path,),
).fetchone()
if not row:
return []
filename, start_time, row_profile = row
p = profile or row_profile
paths = [r[0] for r in self._con.execute(
"SELECT output_path FROM processed"
" WHERE filename = ? AND start_time = ? AND profile = ?",
(filename, start_time, p),
).fetchall()]
self._con.execute(
"DELETE FROM processed WHERE filename = ? AND start_time = ? AND profile = ?",
(filename, start_time, p),
)
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:
if t not in seen_times:
n += 1
seen_times[t] = (t, n, p)
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)."""
if not self._enabled:
return []
return self._get_markers_for(filename, profile)
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)."""
if not self._enabled:
return 0
row = self._con.execute(
"SELECT COUNT(*) FROM processed WHERE filename = ? AND profile = ?",
(filename, profile),
).fetchone()
return row[0] if row else 0
def get_profiles(self) -> list[str]:
"""Return distinct profile names across all tables, ordered alphabetically."""
if not self._enabled:
return []
rows = self._con.execute(
"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:
return []
rows = self._con.execute(
"SELECT DISTINCT output_path FROM processed WHERE profile = ?",
(profile,),
).fetchall()
return [r[0] for r in rows]
def get_max_counter(self, folder: str, name: str) -> int:
"""Return the highest counter N found in output_paths matching folder/name_NNN*.
Parses the counter from filenames (e.g. 'clip_035_0.mp4' → 35).
*folder* is typically the vid folder. Returns 0 if no matches exist.
"""
if not self._enabled:
return 0
prefix = os.path.join(folder, name + "_")
rows = self._con.execute(
"SELECT DISTINCT output_path FROM processed"
" WHERE output_path LIKE ?",
(prefix + "%",),
).fetchall()
max_n = 0
name_prefix = name + "_"
for (op,) in rows:
stem = os.path.splitext(os.path.basename(op))[0]
# stem: "clip_035_0" or "clip_036_a1_0"
if not stem.startswith(name_prefix):
continue
rest = stem[len(name_prefix):] # "035_0" or "036_a1_0"
counter_str = rest.split("_")[0]
try:
max_n = max(max_n, int(counter_str))
except ValueError:
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*.
Returns the number of rows deleted.
"""
if not self._enabled:
return 0
cur = self._con.execute(
"DELETE FROM processed"
" WHERE filename = ? AND profile = ? AND scan_export = 1",
(filename, profile),
)
self._con.commit()
return cur.rowcount
def get_vid_folder(self, filename: str, profile: str,
export_folder: str) -> str:
"""Return the vid_NNN folder name for a source video.
Checks existing DB output_paths first; if the video already has a
vid_NNN folder, returns it. Otherwise assigns max(existing) + 1,
also checking disk for orphan vid folders.
"""
if not self._enabled:
return "vid_001"
# Use the most recent entry (ORDER BY rowid DESC) for determinism
# when a file has entries across multiple vid folders.
row = self._con.execute(
"SELECT output_path FROM processed"
" WHERE filename = ? AND profile = ?"
" ORDER BY rowid DESC LIMIT 1",
(filename, profile),
).fetchone()
if row:
parent = os.path.basename(os.path.dirname(row[0]))
if parent.startswith("vid_"):
return parent
# Collect max vid_NNN number from DB + disk (never reuse old numbers)
max_n = 0
rows = self._con.execute(
"SELECT DISTINCT output_path FROM processed WHERE profile = ?",
(profile,),
).fetchall()
for (op,) in rows:
p = os.path.basename(os.path.dirname(op))
if p.startswith("vid_"):
try:
max_n = max(max_n, int(p.split("_")[1]))
except (IndexError, ValueError):
pass
if os.path.isdir(export_folder):
for d in os.listdir(export_folder):
if d.startswith("vid_") and os.path.isdir(
os.path.join(export_folder, d)
):
try:
max_n = max(max_n, int(d.split("_")[1]))
except (IndexError, ValueError):
pass
return f"vid_{max_n + 1:03d}"
def get_export_folders(self, profile: str = "default",
include_scan_exports: bool = False) -> list[str]:
"""Return distinct export folder names found in output_paths for a profile.
Export paths follow the structure:
.../export_folder/vid_NNN/clip.mp4
The export folder is 2 levels up from the clip file.
Returns folder names sorted alphabetically (e.g. ["mp4_Intense", "mp4_Soft"]).
"""
if not self._enabled:
return []
if include_scan_exports:
rows = self._con.execute(
"SELECT DISTINCT output_path FROM processed WHERE profile = ?",
(profile,),
).fetchall()
else:
rows = self._con.execute(
"SELECT DISTINCT output_path FROM processed"
" WHERE profile = ? AND scan_export = 0",
(profile,),
).fetchall()
folder_names: set[str] = set()
for (op,) in rows:
grandparent = os.path.basename(os.path.dirname(os.path.dirname(op)))
if grandparent:
folder_names.add(grandparent)
return sorted(folder_names)
def get_training_data(self, profile: str, positive_folder: str,
negative_folder: str = "",
fallback_video_dir: str = "",
include_scan_exports: bool = False,
use_hard_negatives: bool = True,
) -> list[tuple[str, list[float], list[float], list[float]]]:
"""Build training video_infos from DB data.
Args:
profile: profile name
positive_folder: export folder name for positive class (e.g. "mp4_Intense")
negative_folder: export folder name for explicit negatives (optional)
fallback_video_dir: if source_path is empty, try filename in this dir
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.
"""
if not self._enabled:
return []
if include_scan_exports:
rows = self._con.execute(
"SELECT filename, start_time, output_path, source_path"
" FROM processed WHERE profile = ?",
(profile,),
).fetchall()
else:
rows = self._con.execute(
"SELECT filename, start_time, output_path, source_path"
" FROM processed WHERE profile = ? AND scan_export = 0",
(profile,),
).fetchall()
# Collect times by video, split by folder role
pos_by_video: dict[str, set[float]] = {}
neg_by_video: dict[str, set[float]] = {}
soft_by_video: dict[str, set[float]] = {}
source_by_filename: dict[str, str] = {}
for fn, st, op, sp in rows:
if sp:
source_by_filename[fn] = sp
grandparent = os.path.basename(os.path.dirname(os.path.dirname(op)))
if grandparent == positive_folder:
pos_by_video.setdefault(fn, set()).add(st)
elif negative_folder and grandparent == negative_folder:
neg_by_video.setdefault(fn, set()).add(st)
else:
soft_by_video.setdefault(fn, set()).add(st)
# Include hard negatives from scan feedback
if use_hard_negatives:
hard_rows = self._con.execute(
"SELECT filename, start_time, source_path FROM hard_negatives"
" WHERE profile = ?",
(profile,),
).fetchall()
for fn, st, sp in hard_rows:
neg_by_video.setdefault(fn, set()).add(st)
if sp:
source_by_filename.setdefault(fn, sp)
# Remove positive times from soft/neg to avoid conflicting labels
for fn in pos_by_video:
if fn in soft_by_video:
soft_by_video[fn] -= pos_by_video[fn]
if fn in neg_by_video:
neg_by_video[fn] -= pos_by_video[fn]
# Deduplicate nearby markers (spread clips from same position)
def _dedup_times(times: set[float], min_gap: float = 8.0) -> list[float]:
if not times:
return []
ordered = sorted(times)
result = [ordered[0]]
for t in ordered[1:]:
if t - result[-1] >= min_gap:
result.append(t)
return result
# 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):
if fallback_video_dir:
sp = os.path.join(fallback_video_dir, fn)
if not sp or not os.path.exists(sp):
continue
gt_pos = _dedup_times(pos_by_video.get(fn, set()))
gt_soft = _dedup_times(soft_by_video.get(fn, set()))
gt_neg = _dedup_times(neg_by_video.get(fn, set()))
result.append((sp, gt_pos, gt_soft, gt_neg))
return result
def get_training_stats(self, profile: str,
include_scan_exports: bool = False) -> dict[str, dict]:
"""Return per-subprofile stats for training readiness display.
Returns dict mapping subprofile_name → {
'videos': number of distinct source videos,
'clips': total clip count,
}
"""
if not self._enabled:
return {}
if include_scan_exports:
rows = self._con.execute(
"SELECT filename, output_path FROM processed WHERE profile = ?",
(profile,),
).fetchall()
else:
rows = self._con.execute(
"SELECT filename, output_path FROM processed"
" WHERE profile = ? AND scan_export = 0",
(profile,),
).fetchall()
folders = self.get_export_folders(profile, include_scan_exports=include_scan_exports)
stats: dict[str, dict] = {}
for folder_name in folders:
videos: set[str] = set()
clips = 0
for fn, op in rows:
grandparent = os.path.basename(os.path.dirname(os.path.dirname(op)))
if grandparent == folder_name:
videos.add(fn)
clips += 1
stats[folder_name] = {"videos": len(videos), "clips": clips}
return {k: v for k, v in stats.items() if v["clips"] > 0}
# ── Scan results ─────────────────────────────────────────────
def save_scan_results(self, filename: str, profile: str, model: str,
regions: list[tuple[float, float, float]],
max_versions: int = 5) -> None:
"""Save scan results as a new version for (filename, profile, model).
regions: list of (start_time, end_time, score).
Keeps up to max_versions; oldest are pruned automatically.
"""
if not self._enabled:
return
ts = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
with self._lock:
self._con.executemany(
"INSERT INTO scan_results"
" (filename, profile, model, start_time, end_time, score,"
" orig_start_time, orig_end_time, scan_timestamp)"
" VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)",
[(filename, profile, model, s, e, sc, s, e, ts)
for s, e, sc in regions],
)
# Prune old versions beyond max_versions
versions = self._con.execute(
"SELECT DISTINCT scan_timestamp FROM scan_results"
" WHERE filename = ? AND profile = ? AND model = ?"
" ORDER BY scan_timestamp DESC",
(filename, profile, model),
).fetchall()
if len(versions) > max_versions:
old_ts = [v[0] for v in versions[max_versions:]]
self._con.execute(
"DELETE FROM scan_results"
" WHERE filename = ? AND profile = ? AND model = ?"
f" AND scan_timestamp IN ({','.join('?' * len(old_ts))})",
(filename, profile, model, *old_ts),
)
self._con.commit()
def get_scan_versions(self, filename: str, profile: str, model: str
) -> list[dict]:
"""Return list of scan versions for (filename, profile, model).
Returns [{timestamp, count, max_score}, ...] ordered newest first.
"""
if not self._enabled:
return []
rows = self._con.execute(
"SELECT scan_timestamp, COUNT(*), MAX(score)"
" FROM scan_results"
" WHERE filename = ? AND profile = ? AND model = ?"
" AND scan_timestamp != ''"
" GROUP BY scan_timestamp"
" ORDER BY scan_timestamp DESC",
(filename, profile, model),
).fetchall()
return [{"timestamp": ts, "count": cnt, "max_score": sc}
for ts, cnt, sc in rows]
def get_scan_results(self, filename: str, profile: str,
scan_timestamp: str | None = None
) -> dict[str, list[tuple[int, float, float, float, bool, float, float]]]:
"""Return scan results grouped by model.
If scan_timestamp is given, returns only that version's rows.
Otherwise returns the latest version per model.
Returns {model: [(row_id, start, end, score, disabled, orig_start, orig_end), ...]}
sorted by start_time.
"""
if not self._enabled:
return {}
if scan_timestamp:
rows = self._con.execute(
"SELECT id, model, start_time, end_time, score, disabled,"
" orig_start_time, orig_end_time"
" FROM scan_results"
" WHERE filename = ? AND profile = ? AND scan_timestamp = ?"
" ORDER BY model, start_time",
(filename, profile, scan_timestamp),
).fetchall()
else:
# For each model, get rows from the latest timestamp only
rows = self._con.execute(
"SELECT r.id, r.model, r.start_time, r.end_time, r.score,"
" r.disabled, r.orig_start_time, r.orig_end_time"
" FROM scan_results r"
" INNER JOIN ("
" SELECT model, MAX(scan_timestamp) AS latest"
" FROM scan_results"
" WHERE filename = ? AND profile = ?"
" GROUP BY model"
" ) m ON r.model = m.model AND r.scan_timestamp = m.latest"
" WHERE r.filename = ? AND r.profile = ?"
" ORDER BY r.model, r.start_time",
(filename, profile, filename, profile),
).fetchall()
result: dict[str, list[tuple[int, float, float, float, bool, float, float]]] = {}
for row_id, model, s, e, sc, dis, os_, oe in rows:
# Fall back to current bounds for legacy rows without orig
result.setdefault(model, []).append(
(row_id, s, e, sc, bool(dis), os_ if os_ is not None else s,
oe if oe is not None else e))
return result
def delete_scan_result(self, row_id: int) -> None:
"""Delete a single scan result row."""
if not self._enabled:
return
with self._lock:
self._con.execute("DELETE FROM scan_results WHERE id = ?", (row_id,))
self._con.commit()
def toggle_scan_result_disabled(self, row_id: int, disabled: bool) -> None:
"""Set disabled flag on a scan result row."""
if not self._enabled:
return
with self._lock:
self._con.execute(
"UPDATE scan_results SET disabled = ? WHERE id = ?",
(1 if disabled else 0, row_id),
)
self._con.commit()
def update_scan_result_times(self, row_id: int,
start: float, end: float) -> None:
"""Update start/end times of a scan result row (resize)."""
if not self._enabled:
return
with self._lock:
self._con.execute(
"UPDATE scan_results SET start_time = ?, end_time = ? WHERE id = ?",
(start, end, row_id),
)
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:
return []
rows = self._con.execute(
"SELECT DISTINCT model FROM scan_results"
" WHERE filename = ? AND profile = ? ORDER BY model",
(filename, profile),
).fetchall()
return [r[0] for r in rows]
def get_scanned_filenames(self, profile: str, model: str) -> set[str]:
"""Return filenames that already have scan results for this model."""
if not self._enabled:
return set()
rows = self._con.execute(
"SELECT DISTINCT filename FROM scan_results"
" WHERE profile = ? AND model = ?",
(profile, model),
).fetchall()
return {r[0] for r in rows}
def add_hard_negatives(self, filename: str, profile: str,
times: list[float], source_path: str = "",
source_model: str = "") -> None:
"""Save timestamps as hard-negative training examples."""
if not self._enabled or not times:
return
with self._lock:
for t in times:
self._con.execute(
"INSERT INTO hard_negatives"
" (filename, profile, start_time, source_path, source_model)"
" VALUES (?, ?, ?, ?, ?)",
(filename, profile, t, source_path, source_model),
)
self._con.commit()
def get_hard_negative_times(self, filename: str, profile: str) -> set[float]:
"""Return start_times marked as hard negatives for this file."""
if not self._enabled:
return set()
rows = self._con.execute(
"SELECT start_time FROM hard_negatives"
" WHERE filename = ? AND profile = ?",
(filename, profile),
).fetchall()
return {r[0] for r in rows}
def get_hard_negatives(self, profile: str) -> list[dict]:
"""Return all hard negatives for a profile with full details."""
if not self._enabled:
return []
rows = self._con.execute(
"SELECT id, filename, start_time, source_path, source_model"
" FROM hard_negatives WHERE profile = ?"
" ORDER BY filename, start_time",
(profile,),
).fetchall()
return [{"id": r[0], "filename": r[1], "start_time": r[2],
"source_path": r[3], "source_model": r[4]} for r in rows]
def delete_hard_negatives_by_ids(self, ids: list[int]) -> None:
"""Delete hard negatives by row IDs."""
if not self._enabled or not ids:
return
with self._lock:
self._con.execute(
f"DELETE FROM hard_negatives WHERE id IN ({','.join('?' * len(ids))})",
ids,
)
self._con.commit()
def remove_hard_negatives(self, filename: str, profile: str,
times: list[float]) -> None:
"""Remove specific hard-negative timestamps."""
if not self._enabled or not times:
return
with self._lock:
for t in times:
self._con.execute(
"DELETE FROM hard_negatives"
" WHERE filename = ? AND profile = ? AND start_time = ?",
(filename, profile, t),
)
self._con.commit()
def get_training_filenames(self, profile: str) -> set[str]:
"""Return filenames used in training (have exported clips)."""
if not self._enabled:
return set()
rows = self._con.execute(
"SELECT DISTINCT filename FROM processed WHERE profile = ?",
(profile,),
).fetchall()
return {r[0] for r in rows}
# ── Hidden files ───────────────────────────────────────────
def hide_file(self, filename: str, profile: str = "default") -> None:
if not self._enabled:
return
with self._lock:
self._con.execute(
"INSERT OR IGNORE INTO hidden_files (filename, profile) VALUES (?, ?)",
(filename, profile),
)
self._con.commit()
def unhide_file(self, filename: str, profile: str = "default") -> None:
if not self._enabled:
return
with self._lock:
self._con.execute(
"DELETE FROM hidden_files WHERE filename = ? AND profile = ?",
(filename, profile),
)
self._con.commit()
def get_hidden_files(self, profile: str = "default") -> set[str]:
if not self._enabled:
return set()
rows = self._con.execute(
"SELECT filename FROM hidden_files WHERE profile = ?", (profile,)
).fetchall()
return {r[0] for r in rows}