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automated update: 2026-06-10 22:25:47

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2026-06-10 22:25:47 -04:00
parent 78ce09adaa
commit b9b734507b
13 changed files with 243 additions and 79 deletions
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if_curator/cli.py
+55 -37
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@@ -14,7 +14,7 @@ from rich.table import Table
from .config import Config, ConfigManager
from .diversity import select_diverse_assets
from .embeddings import is_embedding_available
from .embeddings import is_embedding_available, load_embedding_model
from .image_processing import process_face_mode, process_full_mode, process_object_mode
from .immich_api import fetch_all_assets, fetch_full_image, filter_recent_assets, get_people
from .logging import console, setup_logging
@@ -146,6 +146,7 @@ def interactive_configure(people: list[dict]) -> list[dict]:
return jobs
def auto_configure(people: list[dict]) -> list[dict]:
"""Non-interactive: configure jobs for all named people automatically."""
valid_people = sorted([p for p in people if p.get("name")], key=lambda x: x["name"])
@@ -164,6 +165,13 @@ def auto_configure(people: list[dict]) -> list[dict]:
if skip:
valid_people = [p for p in valid_people if p["name"] not in skip]
# Filter by minimum face count (Issue #6: previously unimplemented)
min_face_count = Config.MIN_FACE_COUNT
if min_face_count > 0:
valid_people = [p for p in valid_people if p.get("assetCount", 0) >= min_face_count]
if valid_people:
rprint(f" Filtered to {len(valid_people)} people with ≥{min_face_count} assets (MIN_FACE_COUNT={min_face_count})")
jobs = []
for person in valid_people:
name = person["name"]
@@ -239,6 +247,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
rprint(f" People: [bold]{len(jobs)}[/bold], Total images: [bold]{total_files}[/bold]")
uploaded, failed = 0, 0
max_retries = 2
with Progress(
SpinnerColumn(),
@@ -276,45 +285,54 @@ def upload_to_frigate(jobs: list[dict]) -> None:
for fname in person_files:
fpath = os.path.join(person_dir, fname)
try:
with open(fpath, "rb") as f:
resp = requests.post(
f"{frigate_url}/api/faces/train/{encoded_name}/classify",
files={"file": (fname, f, "image/jpeg")},
timeout=30,
success = False
for attempt in range(1, max_retries + 1):
try:
with open(fpath, "rb") as f:
resp = requests.post(
f"{frigate_url}/api/faces/train/{encoded_name}/classify",
files={"file": (fname, f, "image/jpeg")},
timeout=30,
)
if resp.status_code == 200:
uploaded += 1
person_uploaded += 1
success = True
break
else:
if attempt < max_retries:
logger.warning(f"Upload attempt {attempt}/{max_retries} for {fname}: HTTP {resp.status_code}, retrying...")
continue
failed += 1
person_failed += 1
progress.console.print(
f" [red]✗ {fname}: HTTP {resp.status_code} (after {max_retries} attempts)[/red]"
)
try:
error_detail = resp.json().get("message", resp.text[:100])
progress.console.print(f" [dim]{error_detail}[/dim]")
except Exception:
progress.console.print(f" [dim]{resp.text[:100]}[/dim]")
except (requests.exceptions.ConnectionError, requests.exceptions.Timeout) as exc:
if attempt < max_retries:
logger.warning(f"Upload attempt {attempt}/{max_retries} for {fname}: {type(exc).__name__}, retrying...")
continue
failed += 1
person_failed += 1
label = "Connection refused" if isinstance(exc, requests.exceptions.ConnectionError) else "Request timed out (30s)"
progress.console.print(
f" [red]✗ {fname}: {label} (after {max_retries} attempts)[/red]"
)
if resp.status_code == 200:
uploaded += 1
person_uploaded += 1
else:
except Exception as e:
if attempt < max_retries:
logger.warning(f"Upload attempt {attempt}/{max_retries} for {fname}: {type(e).__name__}, retrying...")
continue
failed += 1
person_failed += 1
progress.console.print(
f" [red]✗ {fname}: HTTP {resp.status_code}[/red]"
f" [red]✗ {fname}: {type(e).__name__} - {e} (after {max_retries} attempts)[/red]"
)
try:
error_detail = resp.json().get("message", resp.text[:100])
progress.console.print(f" [dim]{error_detail}[/dim]")
except Exception:
progress.console.print(f" [dim]{resp.text[:100]}[/dim]")
except requests.exceptions.ConnectionError:
failed += 1
person_failed += 1
progress.console.print(
f" [red]✗ {fname}: Connection refused[/red]"
)
except requests.exceptions.Timeout:
failed += 1
person_failed += 1
progress.console.print(
f" [red]✗ {fname}: Request timed out (30s)[/red]"
)
except Exception as e:
failed += 1
person_failed += 1
progress.console.print(
f" [red]✗ {fname}: {type(e).__name__} - {e}[/red]"
)
progress.advance(upload_task)
@@ -349,8 +367,8 @@ def _perform_selection(assets: list, limit: int | str, name: str, selection_mode
model_display = "InsightFace (face embeddings)" if entity_type == "face" else "SigLIP (visual embeddings)"
rprint(f"\n[cyan]Using {model_display} for diversity analysis...[/cyan]")
# Pre-load model to avoid interference with progress bar
is_embedding_available(entity_type)
# Pre-load model explicitly (separate from availability check)
load_embedding_model(entity_type)
with Progress(
SpinnerColumn(),