Merge pull request #34 from sudolulo/dev

release: v0.6.0 — revert SQLite tracker to JSON backend

CHANGELOG.md

@@ -7,42 +7,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
-## [0.6.1] - 2026-06-16
-
-### Fixed
-
-- **Corrupt or truncated full-res thumbnails now marked rejected**: `OSError` (truncated file) is caught alongside `PIL.UnidentifiedImageError` in the thumbnail path so persistently bad assets are tombstoned instead of retried forever. Full-res download failures (`USE_FULL_RESOLUTION=true`) remain transient — not marked rejected — so a Immich blip doesn't permanently blacklist valid assets.
-
-- **Quality replacement mode no longer flips mid-loop**: `person_has_fscores` was re-evaluated after each file deletion, which could switch the remaining replacements from Frigate-score mode to blur-score mode if the deleted file was the last scored one. The mode is now fixed for the duration of the upload loop.
-
-- **`reset_person` no longer removes shared asset IDs**: the flat `uploaded_asset_ids` list is now rebuilt from all remaining `by_person` entries rather than subtracting the reset person's IDs. Previously, resetting Alice could remove an asset ID that also appeared under Bob, making it re-eligible for upload.
-
-- **`_save` cache updated only after successful write**: the in-memory tracker cache is now updated after `os.replace` succeeds rather than before. A disk-full or permission error no longer leaves the cache permanently ahead of the on-disk file.
-
-- **Stale Frigate file cleanup batched**: the per-file `remove_frigate_file` loop is replaced with a single `remove_frigate_files_batch` call, reducing N tracker writes to 1 when stale mappings are cleaned up.
-
-- **`_migrate_entry` no longer mutates the cache through nested dict aliases**: all five nested dicts (`asset_ids`, `scores`, `frigate_scores`, `frigate_files`, `crop_dims`) are now individually copied so `.pop()` calls in write paths cannot reach the in-memory cache.
-
-- **`find_by_crop_dimension` and `_pick_mapped_file` now agree on duplicate asset→file handling**: both use first-seen-wins when the same `asset_id` maps to multiple Frigate filenames, preventing inconsistent replacement decisions.
-
-- **Non-atomic JSON write**: tracker files are written to a `.tmp` sibling then renamed with `os.replace` so a crash mid-write never leaves a truncated file.
-
-- **`get_person_summary` uses `_migrate_entry`**: replaced three ad-hoc `isinstance` guards with a single `_migrate_entry` call, making old-format (list) entries consistent with every other read path.
-
-- **Quality replacement floor check**: a candidate with a `None` blur score (PIL error during scoring) no longer blocks a freed slot — the `<=` floor comparison is only applied when a score is actually available.
-
-- **`executor.py` syntax error**: the `if img is None:` block in the full-res download path was comment-only and would have raised `IndentationError` on import. Added `pass`.
-
-- **Duplicate `if stale:` guard**: two consecutive identical guards around stale-cleanup and its log print were merged into one.
-
-- **`_flat_key` uses constant equality** instead of substring match, removing a latent routing bug for any filename that happens to contain "uploaded".
-
-- **`remove_frigate_file` no longer creates ghost entries**: returns early when the person is absent rather than writing an empty stub.
-
-- **`skip_ids` extracted to helper**: the identical set comprehension in `_handle_duplicate_people` that appeared in three branches is now a single `_smaller_duplicate_ids()` inner function.
-
-- **`blur_score_from_image` returns `None` on error** instead of `0.0`, so callers can distinguish a failed measurement from a legitimately near-zero Laplacian variance score.
-
 ## [0.6.0] - 2026-06-15
 
 ### Changed

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "winnow"
-version = "0.6.1"
+version = "0.6.0"
 description = "Selects diverse, high-quality photos from Immich as training data for Frigate face recognition."
 license = "AGPL-3.0-or-later"
 requires-python = ">=3.13"

winnow/cli.py

@@ -78,14 +78,6 @@ def _handle_duplicate_people(people: list[dict]) -> list[dict]:
     if not duplicates:
         return people
 
-    def _smaller_duplicate_ids(groups: dict) -> set[str]:
-        """IDs of all but the largest person in each duplicate group."""
-        return {
-            p["id"]
-            for ps in groups.values()
-            for p in sorted(ps, key=lambda x: x.get("assetCount", 0), reverse=True)[1:]
-        }
-
     if not Config.MERGE_DUPLICATE_PEOPLE:
         rprint("\n[bold yellow]⚠  Duplicate person names detected in Immich:[/bold yellow]")
         for name, ps in sorted(duplicates.items()):
@@ -107,7 +99,12 @@ def _handle_duplicate_people(people: list[dict]) -> list[dict]:
         )
         # Return deduplicated list — keep only the largest per name so that
         # downstream job creation never runs two jobs for the same Frigate folder.
-        return [p for p in people if p["id"] not in _smaller_duplicate_ids(duplicates)]
+        skip_ids = {
+            p["id"]
+            for ps in duplicates.values()
+            for p in sorted(ps, key=lambda x: x.get("assetCount", 0), reverse=True)[1:]
+        }
+        return [p for p in people if p["id"] not in skip_ids]
 
     # Auto-merge: survivor = largest asset count, rest merge into it inside Immich
     merged_any = False
@@ -133,7 +130,11 @@ def _handle_duplicate_people(people: list[dict]) -> list[dict]:
         # IDs still exist in Immich and would produce two jobs for the same folder.
         # IDs from groups that merged successfully are already gone from Immich, so
         # this filter is a no-op for them.
-        skip_ids = _smaller_duplicate_ids(duplicates)
+        skip_ids = {
+            p["id"]
+            for ps in duplicates.values()
+            for p in sorted(ps, key=lambda x: x.get("assetCount", 0), reverse=True)[1:]
+        }
         return [p for p in fresh if p.get("id") not in skip_ids]
 
     # All merges failed — fall back to local deduplication (keep largest per name) so
@@ -142,7 +143,12 @@ def _handle_duplicate_people(people: list[dict]) -> list[dict]:
         "  [yellow]All merges failed — applying local deduplication"
         " to avoid overwriting output.[/yellow]"
     )
-    return [p for p in people if p["id"] not in _smaller_duplicate_ids(duplicates)]
+    skip_ids = {
+        p["id"]
+        for ps in duplicates.values()
+        for p in sorted(ps, key=lambda x: x.get("assetCount", 0), reverse=True)[1:]
+    }
+    return [p for p in people if p["id"] not in skip_ids]
 
 
 _UNSUPPORTED_VARS = [

winnow/executor.py

@@ -35,7 +35,6 @@ from .upload_tracker import (
     mark_rejected,
     mark_uploaded,
     remove_frigate_file,
-    remove_frigate_files_batch,
 )
 
 logger = logging.getLogger(__name__)
@@ -152,9 +151,9 @@ def execute_jobs(jobs: list[dict]) -> None:
                         if use_full_res:
                             img = fetch_full_image(asset["id"])
                             if img is None:
-                                # Full-res download failed — could be a transient network
+                                # Both original and preview fallback failed — mark rejected
-                                # error, so don't mark rejected; it will be retried next run.
+                                # so this asset isn't retried on every future run.
-                                pass
+                                mark_rejected(asset["id"], person_name=name)
                         else:
                             resp = requests.get(
                                 f"{Config.IMMICH_URL}/api/assets/{asset['id']}/thumbnail?size=preview&format=JPEG",
@@ -164,11 +163,11 @@ def execute_jobs(jobs: list[dict]) -> None:
                             if resp.ok:
                                 try:
                                     img = Image.open(BytesIO(resp.content))
-                                except (PIL.UnidentifiedImageError, OSError):
+                                except PIL.UnidentifiedImageError:
-                                    # Pillow cannot identify the format or the content is
+                                    # Pillow cannot identify the format — genuinely corrupt
-                                    # truncated. The download already succeeded (resp.ok),
+                                    # Immich thumbnail. Mark rejected so this asset isn't
-                                    # so this is a data problem, not a transient network
+                                    # retried indefinitely. OSError/truncation errors are
-                                    # error — mark rejected so it isn't retried forever.
+                                    # transient and intentionally not caught here.
                                     logger.warning("Invalid image data for asset %s — marking rejected", asset["id"])
                                     mark_rejected(asset["id"], person_name=name)
                                     img = None
@@ -346,8 +345,9 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                 # (manually deleted, or cleaned up outside winnow). This corrects the
                 # effective_count so those slots are available for new uploads.
                 stale = get_tracked_frigate_filenames(name) - known_frigate_files_at_start
+                for stale_fn in stale:
+                    remove_frigate_file(name, stale_fn)
                 if stale:
-                    remove_frigate_files_batch(name, list(stale))
                     progress.console.print(
                         f"  [dim]{name}: cleared {len(stale)} stale mapping(s)"
                         " (file(s) no longer in Frigate)[/dim]"
@@ -372,9 +372,10 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                 # freed slot isn't filled with something worse than what we removed.
                 if min_quality_score_for_slot is not None:
                     file_score = score_map.get(fname)
-                    if file_score is not None and file_score <= min_quality_score_for_slot:
+                    if file_score is None or file_score <= min_quality_score_for_slot:
+                        score_str = f"{file_score:.3f}" if file_score is not None else "N/A"
                         progress.console.print(
-                            f"    [dim]⏭  {fname}: score {file_score:.3f} ≤ freed slot floor"
+                            f"    [dim]⏭  {fname}: score {score_str} ≤ freed slot floor"
                             f" {min_quality_score_for_slot:.3f}, skipping[/dim]"
                         )
                         progress.advance(upload_task)
@@ -445,13 +446,11 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                         get_target = get_most_redundant_mapped_file
                         score_label, better_note = "frigate", " (more novel)"
                         no_score_msg = "Frigate recognize unavailable, skipping replacement"
-                        is_better_than = lambda c, t: c < t
                     else:
                         candidate_score = score_map.get(fname)
                         get_target = get_lowest_quality_mapped_file
                         score_label, better_note = "blur", ""
                         no_score_msg = "no quality score, skipping replacement"
-                        is_better_than = lambda c, t: c > t
 
                     if candidate_score is None:
                         progress.console.print(f"    [dim]⏭  {fname}: {no_score_msg}[/dim]")
@@ -459,25 +458,28 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                         continue
 
                     target = get_target(name, exclude=failed_deletes)
-                    not_better = target is None or not is_better_than(candidate_score, target[2])
+                    not_better = target is None or (
+                        candidate_score >= target[2] if using_fscore else candidate_score <= target[2]
+                    )
                     if not_better:
                         target_str = f"{target[2]:.3f}" if target is not None else "N/A"
-                        cmp_op = "<" if using_fscore else ">"
+                        op = "<" if using_fscore else ">"
                         progress.console.print(
                             f"    [dim]⏭  {fname}: {score_label} {candidate_score:.3f}"
-                            f" not {cmp_op} {target_str}, skipping[/dim]"
+                            f" not {op} {target_str}, skipping[/dim]"
                         )
                         progress.advance(upload_task)
                         continue
 
                     target_frigate_file, _target_asset_id, target_score = target
-                    cmp_op = "<" if using_fscore else ">"
+                    op = "<" if using_fscore else ">"
                     progress.console.print(
-                        f"    🔄 {fname}: {score_label} {candidate_score:.3f} {cmp_op} {target_score:.3f},"
+                        f"    🔄 {fname}: {score_label} {candidate_score:.3f} {op} {target_score:.3f},"
                         f" replacing {target_frigate_file}{better_note}"
                     )
                     if delete_frigate_person_files(name, [target_frigate_file]):
                         remove_frigate_file(name, target_frigate_file)
+                        person_has_fscores = has_frigate_scores(name)
                         effective_count -= 1
                         min_quality_score_for_slot = None if using_fscore else target_score
                     else:

winnow/quality.py

@@ -139,15 +139,14 @@ def assess_quality(
     return QualityResult(passed=len(reasons) == 0, reasons=reasons, blur_score=blur_score)
 
 
-def blur_score_from_image(img: Image.Image, max_dim: int = 1440) -> float | None:
+def blur_score_from_image(img: Image.Image, max_dim: int = 1440) -> float:
     """Compute Laplacian-variance blur score, capped at max_dim px to normalise scale.
 
     Caps resolution so full-res and thumbnail scores are comparable — Laplacian
     variance grows with pixel count, making uncapped full-res scores much larger
     than thumbnail scores for the same perceived sharpness.
 
-    Returns None on error so callers can distinguish a failed measurement from a
+    Returns 0.0 on any error so callers can treat the result as lowest quality.
-    legitimately low (near-zero) score.
     """
     try:
         score_img = img.convert("RGB") if img.mode != "RGB" else img
@@ -157,5 +156,5 @@ def blur_score_from_image(img: Image.Image, max_dim: int = 1440) -> float | None
         return float(assess_quality(score_img).blur_score)
     except Exception as exc:
         logger.debug("blur_score_from_image failed: %s", exc)
-        return None
+        return 0.0
 

winnow/upload_tracker.py

@@ -71,20 +71,14 @@ def _load(filename: str) -> dict:
 
 def _save(filename: str, data: dict) -> None:
     path = _tracker_path(filename)
+    _cache[str(path)] = data  # keep cache consistent with what we write
     path.parent.mkdir(parents=True, exist_ok=True)
-    tmp = path.with_suffix(".tmp")
+    with open(path, "w") as f:
-    try:
-        with open(tmp, "w") as f:
         json.dump(data, f, indent=2)
-        os.replace(tmp, path)
-        _cache[str(path)] = data  # update only after the file is safely on disk
-    except Exception:
-        tmp.unlink(missing_ok=True)
-        raise
 
 
 def _flat_key(filename: str) -> str:
-    return "uploaded_asset_ids" if filename == UPLOAD_TRACKER_FILE else "rejected_asset_ids"
+    return "uploaded_asset_ids" if "uploaded" in filename else "rejected_asset_ids"
 
 
 def _load_flat(filename: str) -> set[str]:
@@ -102,14 +96,12 @@ def _migrate_entry(entry: list | dict) -> dict:
     """Ensure by_person entry is in the current dict format."""
     if isinstance(entry, list):
         return {"asset_ids": sorted(entry), "scores": {}, "frigate_scores": {}, "frigate_files": {}, "crop_dims": {}}
-    # Copy top-level and all nested dicts so callers' mutations never reach the cache.
+    entry.setdefault("asset_ids", [])
-    result = dict(entry)
+    entry.setdefault("scores", {})
-    result["asset_ids"] = list(result.get("asset_ids", []))
+    entry.setdefault("frigate_scores", {})
-    result["scores"] = dict(result.get("scores", {}))
+    entry.setdefault("frigate_files", {})
-    result["frigate_scores"] = dict(result.get("frigate_scores", {}))
+    entry.setdefault("crop_dims", {})
-    result["frigate_files"] = dict(result.get("frigate_files", {}))
+    return entry
-    result["crop_dims"] = dict(result.get("crop_dims", {}))
-    return result
 
 
 def _mark(
@@ -168,10 +160,15 @@ def mark_rejected(asset_id: str, person_name: str | None = None) -> None:
 
 
 
-
 def record_frigate_file(person_name: str, frigate_filename: str, asset_id: str) -> None:
-    """Record a single Frigate filename → asset_id mapping."""
+    """Record the mapping from a Frigate training filename to an Immich asset ID."""
-    record_frigate_files_batch(person_name, {frigate_filename: asset_id})
+    data = _load(UPLOAD_TRACKER_FILE)
+    by_person = data.setdefault("by_person", {})
+    entry = _migrate_entry(by_person.get(person_name, {}))
+    entry["frigate_files"][frigate_filename] = asset_id
+    by_person[person_name] = entry
+    _save(UPLOAD_TRACKER_FILE, data)
+    logger.debug(f"Mapped Frigate file {frigate_filename} → {asset_id} ({person_name})")
 
 
 def record_frigate_files_batch(person_name: str, mappings: dict[str, str]) -> None:
@@ -193,24 +190,15 @@ def remove_frigate_file(person_name: str, frigate_filename: str) -> None:
     Does NOT unmark the source asset_id — the deletion was deliberate and
     we don't want to re-upload the inferior image on the next run.
     """
-    remove_frigate_files_batch(person_name, [frigate_filename])
-
-
-def remove_frigate_files_batch(person_name: str, frigate_filenames: list[str]) -> None:
-    """Remove multiple Frigate filenames in a single load/save."""
     data = _load(UPLOAD_TRACKER_FILE)
     by_person = data.get("by_person", {})
-    raw = by_person.get(person_name)
+    entry = _migrate_entry(by_person.get(person_name, {}))
-    if raw is None:
+    asset_id = entry["frigate_files"].pop(frigate_filename, None)
-        return
-    entry = _migrate_entry(raw)
-    for fn in frigate_filenames:
-        asset_id = entry["frigate_files"].pop(fn, None)
     if asset_id:
         entry["frigate_scores"].pop(asset_id, None)
     by_person[person_name] = entry
     _save(UPLOAD_TRACKER_FILE, data)
-    logger.debug(f"Removed {len(frigate_filenames)} Frigate file mapping(s) for {person_name}")
+    logger.debug(f"Removed Frigate file mapping {frigate_filename} ({person_name})")
 
 
 def get_tracked_frigate_file_count(person_name: str) -> int:
@@ -250,12 +238,11 @@ def _pick_mapped_file(
     data = _load(UPLOAD_TRACKER_FILE)
     entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
     scores = entry.get(score_key, {})
-    seen_assets: set[str] = set()
+    candidates = [
-    candidates = []
+        (ff, asset_id, scores[asset_id])
-    for ff, asset_id in entry.get("frigate_files", {}).items():
+        for ff, asset_id in entry.get("frigate_files", {}).items()
-        if (exclude is None or ff not in exclude) and asset_id in scores and asset_id not in seen_assets:
+        if (exclude is None or ff not in exclude) and asset_id in scores
-            seen_assets.add(asset_id)
+    ]
-            candidates.append((ff, asset_id, scores[asset_id]))
     if not candidates:
         return None
     return max(candidates, key=lambda x: x[2]) if highest else min(candidates, key=lambda x: x[2])
@@ -298,9 +285,7 @@ def find_by_crop_dimension(size: int) -> list[dict]:
         entry = _migrate_entry(raw_entry)
         scores = entry.get("scores", {})
         frigate_files = entry.get("frigate_files", {})
-        asset_to_frigate: dict[str, str] = {}
+        asset_to_frigate = {v: k for k, v in frigate_files.items()}
-        for fn, aid in frigate_files.items():
-            asset_to_frigate.setdefault(aid, fn)  # first-seen wins; plain inversion silently drops duplicates
         frigate_scores = entry.get("frigate_scores", {})
         for asset_id, dims in entry.get("crop_dims", {}).items():
             w, h = dims[0], dims[1]
@@ -353,12 +338,9 @@ def reset_person(person_name: str) -> None:
         by_person = data.get("by_person", {})
         tracker_entry = by_person.pop(person_name, None)
         if tracker_entry is not None:
-            # Rebuild from remaining entries rather than subtracting, so IDs that
+            person_ids = set(_get_ids(tracker_entry))
-            # appear under another person aren't incorrectly removed from the flat list.
+            flat = set(data.get(flat_key, [])) - person_ids
-            remaining_ids: set[str] = set()
+            data[flat_key] = sorted(flat)
-            for other_entry in by_person.values():
-                remaining_ids.update(_get_ids(other_entry))
-            data[flat_key] = sorted(remaining_ids)
             data["by_person"] = by_person
             _save(filename, data)
             changed = True
@@ -375,14 +357,14 @@ def get_person_summary() -> dict[str, dict]:
     names = set(uploaded_data) | set(rejected_data)
     result = {}
     for name in sorted(names):
-        u_entry = _migrate_entry(uploaded_data.get(name, {}))
+        u_entry = uploaded_data.get(name, {})
-        r_entry = _migrate_entry(rejected_data.get(name, {}))
+        r_entry = rejected_data.get(name, {})
         result[name] = {
-            "uploaded": len(u_entry["asset_ids"]),
+            "uploaded": len(_get_ids(u_entry)),
-            "rejected": len(r_entry["asset_ids"]),
+            "rejected": len(_get_ids(r_entry)),
-            "frigate_count": u_entry.get("frigate_count"),
+            "frigate_count": u_entry.get("frigate_count") if isinstance(u_entry, dict) else None,
-            "scores": u_entry["scores"],
+            "scores": u_entry.get("scores", {}) if isinstance(u_entry, dict) else {},
-            "frigate_files": u_entry["frigate_files"],
+            "frigate_files": u_entry.get("frigate_files", {}) if isinstance(u_entry, dict) else {},
         }
     return result