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feat: disable videos per-subcategory, named models, multi-category training, playlist separators

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- Train dialog: multi-select positive subcategories via checkbox list, optional model name suffix ({profile}_{model}_{name}.joblib)
- list_trained_models recognizes named model variants
- Disable a video per-subcategory: moves its clips to a sibling {subcat}_disabled folder, rewrites DB output_path, migrates dataset.json, marks the name red
- Disabled clips excluded from training, stats, timeline, and playlist counts
- Playlist per-video count reflects only visible, non-disabled subcategories
- Persist subcategory show/hide visibility per profile across restarts
- Add/remove playlist separator rows (right-click) to mark batches, persisted per profile

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Ethanfel
2026-06-05 12:45:03 +02:00
parent 56218c18f4
commit 299779cf29
3 changed files with 376 additions and 79 deletions
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core/audio_scan.py
+12 -6
View File
@@ -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
+110 -5
View File
@@ -483,6 +483,8 @@ class ProcessedDB:
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
@@ -531,6 +533,105 @@ 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 relocate_video_clips(self, filename: str, profile: str,
src_folder_name: str,
dst_folder_name: str) -> int:
"""Move *filename*'s clips from one export folder to a sibling folder.
Matches rows whose grandparent dir basename == *src_folder_name*,
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
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}: "
f"{src_folder_name} -> {dst_folder_name}")
return len(updates)
def get_profiles(self) -> list[str]:
"""Return distinct profile names across all tables, ordered alphabetically."""
if not self._enabled:
@@ -788,11 +889,12 @@ 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,
@@ -803,7 +905,7 @@ 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
@@ -812,10 +914,11 @@ class ProcessedDB:
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"
@@ -839,7 +942,9 @@ 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)