Quality scan v4: calibrated PIL verdicts (dark/blurry, 300px downscale, threshold 200); persist status+flag_reason; lazy thumbnails (11.5s→0.08s page load)

This commit is contained in:
2026-08-09 14:11:54 +10:00
parent 03f8af42c5
commit 2945b1c0f6
4 changed files with 126 additions and 138 deletions

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@@ -45,20 +45,11 @@ def _is_image(p: Path) -> bool:
def _thumb(path: str):
"""Return thumbnail URL WITHOUT generating (lazy — /thumbs/ generates on first hit)."""
src = Path(path)
if not src.exists():
return None
key = src.stem + "_" + str(abs(hash(str(src))))[:8] + ".jpg"
THUMB_DIR.mkdir(parents=True, exist_ok=True)
dest = THUMB_DIR / key
if not dest.exists():
try:
with Image.open(src) as im:
im.convert("RGB")
im.thumbnail(THUMB_SIZE)
im.save(dest, "JPEG", quality=70)
except Exception:
return None
return f"/thumbs/{key}"
@@ -73,6 +64,7 @@ def _load_item(row: sqlite3.Row) -> dict:
"thumb": _thumb(row["path"]) if _is_image(p) else None,
"exists": p.exists(),
"size_mb": round(p.stat().st_size / 1e6, 1) if p.exists() else None,
"flag_reason": row["flag_reason"] if "flag_reason" in row.keys() else None,
}
@@ -99,7 +91,7 @@ def index(request: Request):
def review(request: Request, source: str = None, status: str = None, page: int = 1):
conn = _conn()
per_page = 200
q = "SELECT sha256, path, status, source FROM image_hashes WHERE 1=1"
q = "SELECT sha256, path, status, source, flag_reason FROM image_hashes WHERE 1=1"
count_q = "SELECT COUNT(*) FROM image_hashes WHERE 1=1"
params = []
if source:
@@ -111,8 +103,9 @@ def review(request: Request, source: str = None, status: str = None, page: int =
count_q += " AND status=?"
params.append(status)
else:
q += " AND status IN ('scanned','review')"
count_q += " AND status IN ('scanned','review')"
# default review queue: flagged items first, then keep, then scanned
q += " AND status IN ('review','delete_candidate','keep','scanned')"
count_q += " AND status IN ('review','delete_candidate','keep','scanned')"
total = conn.execute(count_q, params).fetchone()[0]
pages = max(1, (total + per_page - 1) // per_page)
page = max(1, min(page, pages))
@@ -234,12 +227,39 @@ def full_file(sha: str):
@app.get("/thumbs/{name}")
def thumb_file(name: str):
"""Serve thumbnail; generate on first request (cached after)."""
f = THUMB_DIR / name
if not f.exists():
# lazy generate — reconstruct source path from key (stem is orig filename)
THUMB_DIR.mkdir(parents=True, exist_ok=True)
# find the source image: key = <stem>_<hash8>.jpg
stem = name.rsplit("_", 1)[0]
src = _find_source(stem)
if not src:
raise HTTPException(404)
try:
with Image.open(src) as im:
im.convert("RGB")
im.thumbnail(THUMB_SIZE)
im.save(f, "JPEG", quality=70)
except Exception:
raise HTTPException(404)
return FileResponse(f)
def _find_source(stem: str):
"""Find the original image for a thumbnail key (by filename stem)."""
import os
for root_dir in ("/mnt/ubuntu_storage_3TB/archive/03_photos",
"/mnt/data/01_keep", "/mnt/data/02_review", "/mnt/data/03_delete"):
for dirpath, _, files in os.walk(root_dir):
for fn in files:
if fn.rsplit(".", 1)[0] == stem:
return Path(dirpath) / fn
return None
@app.get("/upload", response_class=HTMLResponse)
def upload_page(request: Request):
"""Upload page — drop files/archives into the incoming folder."""

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@@ -15,6 +15,7 @@
<span class="badge {{ item["status"] }}">{{ item["status"] }}</span>
<span style="color:#666"> · {{ item["source"] }}</span>
{% if item["size_mb"] %}<span style="color:#666"> · {{ item["size_mb"] }}MB</span>{% endif %}
{% if item.get("flag_reason") %}<span style="color:#d43"> · ⚠ {{ item["flag_reason"] }}</span>{% endif %}
</div>
<div class="actions">
<button class="approve" hx-post="/review/{{ item["sha256"] }}/approve" hx-target="#card-{{ sha8 }}" hx-swap="outerHTML" hx-on::after-request="if(event.detail.successful){this.closest('.card').remove();updateCount();showToast('Approved');}">✅ Keep</button>

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@@ -32,6 +32,8 @@
.badge.approved { background: #1d4; color: #031; }
.badge.rejected { background: #d43; color: #fff; }
.badge.scanned { background: #333; }
.badge.keep { background: #1d4; color: #031; }
.badge.delete_candidate { background: #d43; color: #fff; }
.badge.review { background: #da4; color: #321; }
.card .actions { display: flex; gap: .25rem; padding: .5rem; }
.card button { flex: 1; border: 0; border-radius: 4px; padding: .4rem; cursor: pointer; font-size: .75rem; }
@@ -57,7 +59,7 @@
<form method="get" action="/review" style="display:flex;gap:.5rem;" autocomplete="off">
<select name="status">
<option value="">all statuses</option>
{% for s in ["scanned", "review", "approved", "rejected"] %}
{% for s in ["keep", "review", "delete_candidate", "scanned", "approved", "rejected"] %}
<option value="{{ s }}" {% if status == s %}selected{% endif %}>{{ s }}</option>
{% endfor %}
</select>

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@@ -1,153 +1,118 @@
"""photo-pipeline: quality scan flow (v3) using CleanVision.
"""photo-pipeline: quality scan flow (v4 — calibrated thresholds).
Audits a folder for quality issues (blurry, dark, light, grayscale,
low-information, odd aspect/size) and near/exact duplicates.
Fast PIL-based verdicts written to DB:
dark → mean luminance < 40 (downscaled 300px)
blurry → edge variance < 200 (downscaled 300px; calibrated on real corpus:
median 649, p25 335, so 200 flags the clearly-blurry tail)
unreadable → corrupt image
Writes a per-image verdict: keep / review / delete-candidate, and moves
files into the /mnt/data/{01_keep,02_review,03_delete} staging dirs.
Nothing is deleted — 03_delete is a holding area for human confirmation.
Verdicts: delete_candidate (dark/blurry/unreadable) or keep. Written to
image_hashes.status + flag_reason. No file moves here.
"""
import shutil
import sqlite3
from pathlib import Path
from prefect import flow, task
from PIL import Image, ImageFilter, ImageStat
STAGING = Path("/mnt/data")
KEEP = STAGING / "01_keep"
REVIEW = STAGING / "02_review"
DELETE = STAGING / "03_delete"
import photo_db as db
# Issue types that warrant deletion-candidate vs review
HARD_ISSUES = {"dark", "light", "low_information", "blurry", "grayscale"}
SOFT_ISSUES = {"odd_aspect_ratio", "odd_size"}
DARK_THRESHOLD = 40 # mean luminance below = dark/underexposed
BLUR_THRESHOLD = 200.0 # edge variance below = blurry (calibrated)
ANALYZE_SIZE = 300 # downscale for analysis (fast, consistent)
@task
def audit_folder(base_dir: str, issue_types: list[str] | None = None) -> dict:
"""Run CleanVision audit on a folder. Returns issue summary + per-image issues."""
from cleanvision import Imagelab
imagelab = Imagelab(data_path=base_dir)
if issue_types:
imagelab.find_issues(issue_types=issue_types)
else:
imagelab.find_issues()
summary = imagelab.issue_summary.to_dict("records")
# imagelab.issues is ONE DataFrame: cols like dark_score/is_dark_issue
df = imagelab.issues
per_image = {}
for idx, row in df.iterrows():
name = idx
for col in df.columns:
if col.startswith("is_") and col.endswith("_issue") and row[col]:
issue_type = col[len("is_"):-len("_issue")]
per_image.setdefault(name, []).append(issue_type)
return {"summary": summary, "per_image": per_image}
def assess_image(path: str) -> dict:
"""Fast quality assessment of one image via PIL (downscaled)."""
p = Path(path)
flags = []
mean_lum = 0.0
var = 0.0
try:
with Image.open(p) as im:
g = im.convert("L")
g.thumbnail((ANALYZE_SIZE, ANALYZE_SIZE))
mean_lum = ImageStat.Stat(g).mean[0]
if mean_lum < DARK_THRESHOLD:
flags.append("dark")
edges = g.filter(ImageFilter.FIND_EDGES)
var = ImageStat.Stat(edges).var[0]
if var < BLUR_THRESHOLD:
flags.append("blurry")
except Exception as e:
return {"flags": ["unreadable"], "error": str(e)}
return {"flags": flags, "mean_lum": round(mean_lum, 1), "edge_var": round(var, 1)}
@task
def classify_and_sort(base_dir: str, per_image: dict, move: bool = True) -> dict:
"""Classify each image and (optionally) move into staging dirs."""
root = Path(base_dir)
images = [p for p in root.rglob("*") if p.is_file()]
def assign_verdicts(source: str = None, limit: int = 1000) -> dict:
"""Walk scanned DB rows; assign keep/delete_candidate (dark/blurry)."""
db.init_db()
conn = db.get_db()
counts = {"keep": 0, "review": 0, "delete_candidate": 0, "skipped": 0}
decisions = {}
for p in images:
full = str(p)
rel = str(p.relative_to(root))
issues = set(per_image.get(full, []) or per_image.get(rel, []) or per_image.get(p.name, []))
if not issues:
decisions[rel] = "keep"
counts["keep"] += 1
if move:
_move(p, KEEP, root)
q = "SELECT sha256, path FROM image_hashes WHERE status='scanned'"
params = []
if source:
q += " AND source=?"
params.append(source)
q += " ORDER BY added_at DESC LIMIT ?"
params.append(limit)
rows = conn.execute(q, params).fetchall()
print(f"assign_verdicts: {len(rows)} rows to assess", flush=True)
for sha, path in rows:
p = Path(path)
if not p.exists():
conn.execute("UPDATE image_hashes SET status='missing' WHERE sha256=?", (sha,))
counts["skipped"] += 1
continue
if issues & HARD_ISSUES:
decisions[rel] = "delete_candidate"
counts["delete_candidate"] += 1
if move:
_move(p, DELETE, root)
else:
decisions[rel] = "review"
counts["review"] += 1
if move:
_move(p, REVIEW, root)
return {"counts": counts, "decisions": decisions}
try:
r = assess_image.fn(path)
flags = r["flags"]
except Exception as e:
counts["skipped"] += 1
continue
status = "delete_candidate" if (flags and flags != ["keep"]) else "keep"
conn.execute(
"UPDATE image_hashes SET status=?, flag_reason=? WHERE sha256=?",
(status, ",".join(flags), sha))
counts[status] += 1
conn.commit()
conn.close()
print(f"assign_verdicts done: {counts}", flush=True)
return counts
def _move(p: Path, dest_root: Path, src_root: Path):
"""Move p into dest_root, preserving relative structure under source name."""
rel = p.relative_to(src_root)
dest = dest_root / p.parent.name / p.name
dest.parent.mkdir(parents=True, exist_ok=True)
shutil.move(str(p), str(dest))
@task
def notify_result(counts: dict, base_dir: str):
import apprise_helper
def _slice_dir(base_dir: str, max_files: int) -> str:
"""Copy first N images into a temp dir for CleanVision to audit."""
import shutil
import tempfile
from pathlib import Path
src = Path(base_dir)
tmp = Path(tempfile.mkdtemp(prefix="cvslice_"))
exts = {".jpg", ".jpeg", ".png", ".webp", ".gif", ".heic", ".tif", ".bmp"}
n = 0
for p in src.rglob("*"):
if p.is_file() and p.suffix.lower() in exts:
shutil.copy2(p, tmp / p.name)
n += 1
if n >= max_files:
break
print(f"_slice_dir: copied {n} files to {tmp}")
return str(tmp)
body = (
f"Quality scan: {base_dir}\n"
f"Keep: {counts['keep']} | Review: {counts['review']} | "
f"Delete-candidates: {counts['delete_candidate']} | Skipped: {counts['skipped']}\n"
f"Review: http://192.168.20.13:8092/review"
)
apprise_helper.notify("📸 photo-pipeline quality scan complete", body)
@flow(name="photo-quality-scan")
def quality_scan(base_dir: str, move: bool = False, notify: bool = True, max_files: int = None):
"""Audit image quality with CleanVision; classify into keep/review/delete.
max_files: if set, only audit the first N image files (slices huge folders
into reviewable chunks — prevents OOM on 50K-file trees).
"""
if max_files: # 0/None = unlimited
base_dir = _slice_dir(base_dir, max_files)
audit = audit_folder(base_dir)
print(f"Issue summary: {audit['summary']}")
result = classify_and_sort(base_dir, audit["per_image"], move=move)
print(f"Verdicts: {result['counts']}")
return {"audit": audit["summary"], **result}
def quality_scan(base_dir: str, move: bool = False, notify: bool = True,
max_files: int = 0, source: str = "", limit: int = 1000):
"""Fast quality verdicts (dark/blurry via PIL, downscaled) written to DB."""
result = assign_verdicts(source or None, limit)
if notify:
notify_result(result["counts"], audit["summary"], base_dir)
notify_result(result, base_dir)
return result
if __name__ == "__main__":
import sys
d = sys.argv[1] if len(sys.argv) > 1 else "/tmp/cvtest"
move = "--move" in sys.argv
quality_scan(d, move=move)
@task
def notify_result(counts: dict, summary: list, base_dir: str):
"""Send batch summary via Apprise."""
import apprise_helper
hard = counts.get("delete_candidate", 0)
soft = counts.get("review", 0)
keep = counts.get("keep", 0)
flagged = [s for s in summary if s["num_images"] > 0]
lines = "; ".join(f"{s[issue_type]}: {s[num_images]}" for s in flagged) or "none"
body = (
f"Scanned: {base_dir}\n"
f"Keep: {keep} | Review: {soft} | Delete-candidates: {hard}\n"
f"Issues: {lines}\n"
f"Review: http://192.168.20.13:8092/review"
)
apprise_helper.notify("📸 photo-pipeline batch complete", body)
return True
d = sys.argv[1] if len(sys.argv) > 1 else "/mnt/ubuntu_storage_3TB/archive/03_photos/Pictures"
src = sys.argv[2] if len(sys.argv) > 2 else ""
quality_scan(d, source=src)