126 lines
4.3 KiB
Python
126 lines
4.3 KiB
Python
"""photo-pipeline: quality scan flow (v3) using CleanVision.
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Audits a folder for quality issues (blurry, dark, light, grayscale,
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low-information, odd aspect/size) and near/exact duplicates.
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Writes a per-image verdict: keep / review / delete-candidate, and moves
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files into the /mnt/data/{01_keep,02_review,03_delete} staging dirs.
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Nothing is deleted — 03_delete is a holding area for human confirmation.
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"""
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import shutil
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from pathlib import Path
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from prefect import flow, task
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STAGING = Path("/mnt/data")
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KEEP = STAGING / "01_keep"
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REVIEW = STAGING / "02_review"
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DELETE = STAGING / "03_delete"
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# Issue types that warrant deletion-candidate vs review
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HARD_ISSUES = {"dark", "light", "low_information", "blurry", "grayscale"}
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SOFT_ISSUES = {"odd_aspect_ratio", "odd_size"}
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@task
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def audit_folder(base_dir: str, issue_types: list[str] | None = None) -> dict:
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"""Run CleanVision audit on a folder. Returns issue summary + per-image issues."""
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from cleanvision import Imagelab
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imagelab = Imagelab(data_path=base_dir)
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if issue_types:
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imagelab.find_issues(issue_types=issue_types)
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else:
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imagelab.find_issues()
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summary = imagelab.issue_summary.to_dict("records")
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# imagelab.issues is ONE DataFrame: cols like dark_score/is_dark_issue
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df = imagelab.issues
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per_image = {}
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for idx, row in df.iterrows():
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name = idx
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for col in df.columns:
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if col.startswith("is_") and col.endswith("_issue") and row[col]:
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issue_type = col[len("is_"):-len("_issue")]
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per_image.setdefault(name, []).append(issue_type)
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return {"summary": summary, "per_image": per_image}
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@task
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def classify_and_sort(base_dir: str, per_image: dict, move: bool = True) -> dict:
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"""Classify each image and (optionally) move into staging dirs."""
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root = Path(base_dir)
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images = [p for p in root.rglob("*") if p.is_file()]
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counts = {"keep": 0, "review": 0, "delete_candidate": 0, "skipped": 0}
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decisions = {}
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for p in images:
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full = str(p)
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rel = str(p.relative_to(root))
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issues = set(per_image.get(full, []) or per_image.get(rel, []) or per_image.get(p.name, []))
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if not issues:
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decisions[rel] = "keep"
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counts["keep"] += 1
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if move:
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_move(p, KEEP, root)
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continue
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if issues & HARD_ISSUES:
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decisions[rel] = "delete_candidate"
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counts["delete_candidate"] += 1
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if move:
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_move(p, DELETE, root)
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else:
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decisions[rel] = "review"
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counts["review"] += 1
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if move:
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_move(p, REVIEW, root)
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return {"counts": counts, "decisions": decisions}
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def _move(p: Path, dest_root: Path, src_root: Path):
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"""Move p into dest_root, preserving relative structure under source name."""
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rel = p.relative_to(src_root)
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dest = dest_root / p.parent.name / p.name
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dest.parent.mkdir(parents=True, exist_ok=True)
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shutil.move(str(p), str(dest))
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@flow(name="photo-quality-scan")
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def quality_scan(base_dir: str, move: bool = False, notify: bool = True):
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"""Audit image quality with CleanVision; classify into keep/review/delete."""
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audit = audit_folder(base_dir)
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print(f"Issue summary: {audit['summary']}")
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result = classify_and_sort(base_dir, audit["per_image"], move=move)
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print(f"Verdicts: {result['counts']}")
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return {"audit": audit["summary"], **result}
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if notify:
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notify_result(result["counts"], audit["summary"], base_dir)
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if __name__ == "__main__":
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import sys
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d = sys.argv[1] if len(sys.argv) > 1 else "/tmp/cvtest"
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move = "--move" in sys.argv
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quality_scan(d, move=move)
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@task
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def notify_result(counts: dict, summary: list, base_dir: str):
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"""Send batch summary via Apprise."""
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import apprise_helper
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hard = counts.get("delete_candidate", 0)
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soft = counts.get("review", 0)
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keep = counts.get("keep", 0)
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flagged = [s for s in summary if s["num_images"] > 0]
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lines = "; ".join(f"{s[issue_type]}: {s[num_images]}" for s in flagged) or "none"
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body = (
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f"Scanned: {base_dir}\n"
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f"Keep: {keep} | Review: {soft} | Delete-candidates: {hard}\n"
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f"Issues: {lines}\n"
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f"Review: http://192.168.20.13:8092/review"
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)
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apprise_helper.notify("📸 photo-pipeline batch complete", body)
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return True
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