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refactor: merge dev → main — post-0.4.0 cleanup

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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
flan
2026-06-13 18:55:42 +00:00
co-authored by Claude Sonnet 4.6
parent 71df0e81de e67f2d9638
commit 91e0858aa6
3 changed files with 43 additions and 52 deletions
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winnow/executor.py
+8 -3
View File
@@ -395,6 +395,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
actually_uploaded: list[tuple[str, str | None]] = []
failed_deletes: set[str] = set()
min_quality_score_for_slot: float | None = None
person_has_fscores: bool = has_frigate_scores(name)
for fname in person_files:
fpath = os.path.join(person_dir, fname)
@@ -427,9 +428,9 @@ def upload_to_frigate(jobs: list[dict]) -> None:
# handles this conservatively by skipping that candidate until the next run.
pre_fscore: float | None = None
if Config.ENABLE_FRIGATE_SCORES and pre_run_count > 0:
if not at_cap or has_frigate_scores(name):
if not at_cap or person_has_fscores:
_result = recognize_face(fpath)
if _result is not None and _result[0] == name:
if _result is not None and (_result[0] or "").casefold() == name.casefold():
pre_fscore = _result[1]
# Ceiling check: skip if the existing training set already covers this
@@ -450,7 +451,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
progress.advance(upload_task)
continue
using_fscore = has_frigate_scores(name) and Config.ENABLE_FRIGATE_SCORES
using_fscore = person_has_fscores and Config.ENABLE_FRIGATE_SCORES
if using_fscore:
candidate_score = pre_fscore
if candidate_score is None:
@@ -476,6 +477,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
)
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 # clear any blur-mode slot floor — Frigate uses a different score metric
else:
@@ -507,6 +509,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
)
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 = score_map.get(fname)
else:
@@ -538,6 +541,8 @@ def upload_to_frigate(jobs: list[dict]) -> None:
crop_dims=dims_map.get(fname),
frigate_score=pre_fscore,
)
if pre_fscore is not None:
person_has_fscores = True
actually_uploaded.append((fname, asset_id))
break
winnow/frigate_api.py
+14 -18
View File
@@ -22,24 +22,6 @@ def _get_faces_data() -> dict | None:
return None
def get_frigate_face_counts() -> dict[str, int] | None:
"""Return {person_name: training_image_count} from Frigate's train directory.
Returns None if FRIGATE_URL is not set or the API is unreachable, so callers
can distinguish "API unavailable" from "person has 0 images."
"""
data = _get_faces_data()
if data is None:
return None
# Response: {person_name: [file, ...], "train": [...], ...}
# "train" is a flat pending list, not a person — skip it.
return {
name: len(files)
for name, files in data.items()
if name != "train" and isinstance(files, list)
}
def get_all_frigate_person_files() -> dict[str, list[str]] | None:
"""Return {person_name: [filename, ...]} for every person in Frigate.
@@ -49,6 +31,8 @@ def get_all_frigate_person_files() -> dict[str, list[str]] | None:
data = _get_faces_data()
if data is None:
return None
# Response: {person_name: [file, ...], "train": [...], ...}
# "train" is a flat pending list, not a person — skip it.
return {
name: files
for name, files in data.items()
@@ -56,6 +40,18 @@ def get_all_frigate_person_files() -> dict[str, list[str]] | None:
}
def get_frigate_face_counts() -> dict[str, int] | None:
"""Return {person_name: training_image_count} from Frigate's train directory.
Returns None if FRIGATE_URL is not set or the API is unreachable, so callers
can distinguish "API unavailable" from "person has 0 images."
"""
all_files = get_all_frigate_person_files()
if all_files is None:
return None
return {name: len(files) for name, files in all_files.items()}
def get_frigate_person_files(person_name: str) -> list[str] | None:
"""Return the list of training filenames for a person in Frigate.
winnow/upload_tracker.py
+21 -31
View File
@@ -167,7 +167,9 @@ def remove_frigate_file(person_name: str, frigate_filename: str) -> None:
data = _load(UPLOAD_TRACKER_FILE)
by_person = data.get("by_person", {})
entry = _migrate_entry(by_person.get(person_name, {}))
entry["frigate_files"].pop(frigate_filename, None)
asset_id = entry["frigate_files"].pop(frigate_filename, 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 Frigate file mapping {frigate_filename} ({person_name})")
@@ -204,6 +206,22 @@ def has_frigate_scores(person_name: str) -> bool:
return any(asset_id in frigate_scores for asset_id in frigate_files.values())
def _pick_mapped_file(
person_name: str, score_key: str, *, highest: bool, exclude: set[str] | None = None
) -> tuple[str, str, float] | None:
data = _load(UPLOAD_TRACKER_FILE)
entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
scores = entry.get(score_key, {})
candidates = [
(ff, asset_id, scores[asset_id])
for ff, asset_id in entry.get("frigate_files", {}).items()
if (exclude is None or ff not in exclude) and asset_id in scores
]
if not candidates:
return None
return max(candidates, key=lambda x: x[2]) if highest else min(candidates, key=lambda x: x[2])
def get_lowest_quality_mapped_file(
person_name: str, exclude: set[str] | None = None
) -> tuple[str, str, float] | None:
@@ -213,21 +231,7 @@ def get_lowest_quality_mapped_file(
Used for quality replacement when no Frigate scores are available.
Pass `exclude` to skip files that failed to delete this run.
"""
data = _load(UPLOAD_TRACKER_FILE)
entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
frigate_files = entry.get("frigate_files", {})
blur_scores = entry.get("scores", {})
candidates = [
(ff, asset_id, blur_scores[asset_id])
for ff, asset_id in frigate_files.items()
if (exclude is None or ff not in exclude)
and asset_id in blur_scores
]
if not candidates:
return None
return min(candidates, key=lambda x: x[2])
return _pick_mapped_file(person_name, "scores", highest=False, exclude=exclude)
def get_most_redundant_mapped_file(
@@ -240,21 +244,7 @@ def get_most_redundant_mapped_file(
= the most redundant file and therefore the best replacement target.
Pass `exclude` to skip files that failed to delete this run.
"""
data = _load(UPLOAD_TRACKER_FILE)
entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
frigate_files = entry.get("frigate_files", {})
frigate_scores = entry.get("frigate_scores", {})
candidates = [
(ff, asset_id, frigate_scores[asset_id])
for ff, asset_id in frigate_files.items()
if (exclude is None or ff not in exclude)
and asset_id in frigate_scores
]
if not candidates:
return None
return max(candidates, key=lambda x: x[2])
return _pick_mapped_file(person_name, "frigate_scores", highest=True, exclude=exclude)
def get_frigate_filename_for_asset(person_name: str, asset_id: str) -> str | None: