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imagerepo/app/utils/image_importer.py
T
bvandeusen ce560d09a1 feat(integrity): structural verification + supersede-on-replace pipeline
Adds per-image integrity tracking so corrupt files are detected, excluded
from random/showcase/ML/suggestion paths, and recoverable by dropping a
fresh copy in /import — closing the gap that surfaced as the WD14
'6 bytes not processed' OSError.

Schema (migration l26042501)
- image_record.integrity_status: unknown | ok | truncated | unreadable | missing
- image_record.integrity_checked_at: timestamptz
- partial index on status <> 'ok' for cheap report/filter queries

Verifier
- app/services/integrity.py: verify_path() dispatches by extension
- PIL two-stage (verify + load with LOAD_TRUNCATED_IMAGES disabled)
- ffprobe for video, zipfile.testzip for archives
- Truncation-vs-unreadable distinction via PIL message hints

Pipeline
- verify_media_integrity Celery task: per-image, idempotent
- verify_unverified_images sweep: only_unknown by default, skips
  paths in active import tasks
- Hooked into the end of import_media_file (new + archive paths) and
  the supersede branch
- supersede_image() resets status to 'unknown' so the post-supersede
  verify writes a fresh truth
- Supersede-on-replace: a fresh /import/<artist>/<filename> matching
  a flagged-corrupt record routes through _supersede_existing,
  preserving tags/series/embeddings

Exclusions
- /, /api/random-images, tag_and_embed, ml.backfill enqueue, and
  get_suggestions all filter integrity_status IN ('ok', 'unknown') so
  flagged rows don't poison the gallery, ML, or suggestion math.
  'unknown' is treated as healthy so post-migration data stays visible
  until the sweep runs.

UI / report
- Settings -> Maintenance: 'Verify unknown' + 'Force re-verify all'
- GET /api/integrity/failed (paginated list of flagged rows)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-26 00:16:06 -04:00

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# app/utils/image_importer.py
from __future__ import annotations
from datetime import datetime
from pathlib import Path
import hashlib
import json
import logging
import mimetypes
import os
import re
import shutil
import subprocess
import tempfile
import uuid
log = logging.getLogger(__name__)
from PIL import Image, ImageOps
import exifread
import imagehash
from app import db
from app.models import ImageRecord, Tag, ArchiveRecord
FFMPEG_THUMB_TIMEOUT = int(os.environ.get("THUMBS_FFMPEG_TIMEOUT", "60")) # seconds
FFMPEG_TRANSCODE_TIMEOUT = int(os.environ.get("FFMPEG_TRANSCODE_TIMEOUT", "600")) # 10 min default
Image.MAX_IMAGE_PIXELS = int(os.environ.get("PIL_MAX_IMAGE_PIXELS", "178956970"))
ARCHIVE_NUM_WIDTH = int(os.environ.get("ARCHIVE_NUM_WIDTH", "4"))
# =============================================================================
# Configuration & Constants
# =============================================================================
THUMB_SIZE = (400, 400)
# Media and archive extensions we handle
IMAGE_EXTS = (".jpg", ".jpeg", ".jfif", ".png", ".gif", ".bmp", ".tiff", ".webp")
VIDEO_EXTS = (".mp4", ".mov", ".avi", ".mkv", ".webm", ".m4v", ".wmv", ".flv")
VIDEO_EXTS_NEED_TRANSCODE = (".mov", ".avi", ".mkv", ".webm", ".m4v", ".wmv", ".flv") # Non-MP4 formats
ALLOWED_MEDIA_EXTS = IMAGE_EXTS + VIDEO_EXTS
ALLOWED_ARCHIVE_EXTS = (
".zip", ".rar", ".cbr", ".7z",
".tar", ".tar.gz", ".tgz", ".tar.bz2", ".tbz2", ".tar.xz", ".txz"
)
# Import filter settings (loaded from file or env)
IMPORT_SETTINGS_PATH = "/import/settings.json"
def load_import_settings() -> dict:
"""
Load import filter settings from database, with file and environment fallbacks.
Priority: DB settings > file settings > environment variables
"""
# Start with environment defaults
defaults = {
"min_width": int(os.environ.get("IMPORT_MIN_WIDTH", "0")),
"min_height": int(os.environ.get("IMPORT_MIN_HEIGHT", "0")),
"skip_transparent": os.environ.get("IMPORT_SKIP_TRANSPARENT", "false").lower() == "true",
"transparency_threshold": float(os.environ.get("IMPORT_TRANSPARENCY_THRESHOLD", "0.9")),
"skip_single_color": os.environ.get("IMPORT_SKIP_SINGLE_COLOR", "true").lower() == "true",
"single_color_threshold": float(os.environ.get("IMPORT_SINGLE_COLOR_THRESHOLD", "0.95")),
"single_color_tolerance": int(os.environ.get("IMPORT_SINGLE_COLOR_TOLERANCE", "30")),
"phash_threshold": int(os.environ.get("IMPORT_PHASH_THRESHOLD", "10")), # Default for 256-bit
"supersede_smaller": os.environ.get("IMPORT_SUPERSEDE_SMALLER", "true").lower() == "true",
}
# Try to load from file (legacy support)
try:
if os.path.exists(IMPORT_SETTINGS_PATH):
with open(IMPORT_SETTINGS_PATH, "r") as f:
file_settings = json.load(f)
defaults.update(file_settings)
except Exception as e:
print(f"[WARN] Failed to load import settings from file: {e}")
# Try to load from database (preferred)
try:
from app.utils.version_migration import get_import_settings
db_settings = get_import_settings()
# Only override if DB has non-default values
for key, value in db_settings.items():
if value is not None:
defaults[key] = value
except Exception as e:
print(f"[WARN] Failed to load import settings from DB: {e}")
return defaults
def is_mostly_transparent(file_path: str, threshold: float = 0.9) -> bool:
"""
Check if an image is mostly transparent (> threshold % of pixels are transparent).
Returns False for images without alpha channel.
Args:
file_path: Path to the image file
threshold: Percentage of pixels that must be transparent (0.0-1.0, default 0.9 = 90%)
Returns:
True if the image has > threshold% transparent pixels
"""
try:
with Image.open(file_path) as img:
original_mode = img.mode
# Handle different image modes that may have transparency
if original_mode == "RGBA":
# Already has alpha channel
pass
elif original_mode == "LA":
# Grayscale with alpha
img = img.convert("RGBA")
elif original_mode == "P":
# Palette mode - check for transparency
if "transparency" in img.info:
img = img.convert("RGBA")
else:
return False
elif original_mode == "PA":
# Palette with alpha
img = img.convert("RGBA")
else:
# RGB, L, etc. - no alpha channel
return False
# Get alpha channel
bands = img.split()
if len(bands) < 4:
return False
alpha = bands[3] # Alpha is the 4th channel (index 3)
alpha_data = alpha.getdata()
total_pixels = alpha.size[0] * alpha.size[1]
if total_pixels == 0:
return False
# Count pixels where alpha < 128 (more than 50% transparent)
transparent_count = sum(1 for p in alpha_data if p < 128)
transparency_ratio = transparent_count / total_pixels
return transparency_ratio > threshold
except Exception as e:
print(f"[WARN] Failed to check transparency for {file_path}: {e}")
return False
def is_mostly_single_color(file_path: str, threshold: float = 0.95, tolerance: int = 30) -> bool:
"""
Check if an image is mostly a single color (> threshold % of pixels are similar).
Uses color distance tolerance to group similar colors.
Args:
file_path: Path to the image file
threshold: Percentage of pixels that must be similar (0.0-1.0, default 0.95 = 95%)
tolerance: Maximum color distance to be considered "same" color (0-255 per channel, default 30)
Returns:
True if the image is mostly a single solid color
"""
try:
with Image.open(file_path) as img:
# Convert to RGB for consistent color comparison
if img.mode in ("RGBA", "LA"):
# For images with alpha, only consider non-transparent pixels
img_rgba = img.convert("RGBA") if img.mode != "RGBA" else img
pixels = list(img_rgba.getdata())
# Filter out mostly transparent pixels (alpha < 128)
opaque_pixels = [(r, g, b) for r, g, b, a in pixels if a >= 128]
if len(opaque_pixels) == 0:
return True # Fully transparent = effectively single color
pixels = opaque_pixels
elif img.mode == "P":
img = img.convert("RGB")
pixels = list(img.getdata())
elif img.mode == "L":
# Grayscale - convert to RGB tuples
pixels = [(p, p, p) for p in img.getdata()]
else:
if img.mode != "RGB":
img = img.convert("RGB")
pixels = list(img.getdata())
if len(pixels) == 0:
return True
# Sample pixels for performance on large images
total_pixels = len(pixels)
if total_pixels > 10000:
# Sample evenly distributed pixels
step = total_pixels // 10000
pixels = pixels[::step]
# Find the dominant color (most common pixel or average of sampled area)
# Use the pixel at center as reference
center_idx = len(pixels) // 2
ref_color = pixels[center_idx]
# Count pixels within tolerance of reference color
similar_count = 0
for pixel in pixels:
if isinstance(pixel, int):
pixel = (pixel, pixel, pixel)
# Calculate color distance (simple RGB distance)
dist = abs(pixel[0] - ref_color[0]) + abs(pixel[1] - ref_color[1]) + abs(pixel[2] - ref_color[2])
if dist <= tolerance * 3: # tolerance per channel * 3 channels
similar_count += 1
similarity_ratio = similar_count / len(pixels)
return similarity_ratio > threshold
except Exception as e:
print(f"[WARN] Failed to check single color for {file_path}: {e}")
return False
def supersede_image(old_record: "ImageRecord", new_filepath: str, new_thumb_path: str,
new_hash: str, new_phash, new_metadata: dict, new_filename: str) -> "ImageRecord":
"""
Replace a smaller image with a larger version, preserving tags and metadata.
Args:
old_record: The existing ImageRecord to supersede
new_filepath: Path to the new larger image file
new_thumb_path: Path to the new thumbnail
new_hash: SHA256 hash of the new file
new_phash: Perceptual hash of the new image
new_metadata: Metadata dict for the new image
new_filename: Original filename of the new image
Returns:
The updated ImageRecord
"""
# Store old file paths for cleanup
old_filepath = old_record.filepath
old_thumb_path = old_record.thumb_path
print(f"[SUPERSEDE] Replacing {old_record.filename} ({old_record.width}x{old_record.height}) "
f"with {new_filename} ({new_metadata['width']}x{new_metadata['height']})")
# Update record with new file info
old_record.filename = new_filename
old_record.filepath = new_filepath
old_record.thumb_path = new_thumb_path
old_record.hash = new_hash
old_record.perceptual_hash = str(new_phash) if new_phash else None
old_record.file_size = new_metadata["file_size"]
old_record.width = new_metadata["width"]
old_record.height = new_metadata["height"]
old_record.format = new_metadata["format"]
# The bytes on disk just changed — the prior verification result is no
# longer authoritative. Reset to 'unknown' so the post-supersede verify
# hook (or the next sweep) re-records the truth.
old_record.integrity_status = 'unknown'
old_record.integrity_checked_at = None
# Keep the earlier taken_at date (prefer original date)
if new_metadata.get("taken_at") and old_record.taken_at:
if new_metadata["taken_at"] < old_record.taken_at:
old_record.taken_at = new_metadata["taken_at"]
elif new_metadata.get("taken_at") and not old_record.taken_at:
old_record.taken_at = new_metadata["taken_at"]
# Don't update imported_at - keep original import time
# Delete old files
try:
if old_filepath and os.path.exists(old_filepath):
os.remove(old_filepath)
print(f"[SUPERSEDE] Deleted old file: {old_filepath}")
except Exception as e:
print(f"[WARN] Failed to delete old file {old_filepath}: {e}")
try:
if old_thumb_path and os.path.exists(old_thumb_path):
os.remove(old_thumb_path)
print(f"[SUPERSEDE] Deleted old thumbnail: {old_thumb_path}")
except Exception as e:
print(f"[WARN] Failed to delete old thumbnail {old_thumb_path}: {e}")
return old_record
# Regex for multi-part detection
RAR_PART_RE = re.compile(r"\.part(\d+)\.rar$", re.IGNORECASE)
SEVENZ_PART_RE = re.compile(r"\.7z\.(\d{3})$", re.IGNORECASE)
OLD_RAR_VOL_RE = re.compile(r"\.r\d{2}$", re.IGNORECASE) # .r00, .r01, ...
# Environment configuration (optional)
ENV_TMPDIR = "ARCHIVE_TMPDIR" # where to extract archives (default: system tmp)
ENV_MINFREE = "ARCHIVE_MIN_FREE_GB" # min free GB required to start extraction (float; 0 = disabled)
# =============================================================================
# Utilities: Temp space management & free-space guard
# =============================================================================
def get_tmp_base() -> Path:
"""Return the base temp directory for archive extraction."""
return Path(os.environ.get(ENV_TMPDIR, tempfile.gettempdir())).resolve()
def cleanup_stale_tempdirs(prefix: str = "extract_") -> None:
"""Delete any leftover extraction directories from previous crashes."""
base = get_tmp_base()
base.mkdir(parents=True, exist_ok=True)
for entry in base.glob(f"{prefix}*"):
if entry.is_dir():
try:
shutil.rmtree(entry, ignore_errors=True)
except Exception:
pass
def ensure_free_space_or_raise(path: Path, min_free_gb: float) -> None:
"""Raise if there is not enough free space at path."""
if min_free_gb <= 0:
return
total, used, free = shutil.disk_usage(str(path))
free_gb = free / (1024 ** 3)
if free_gb < min_free_gb:
raise RuntimeError(
f"Insufficient free space at {path}: {free_gb:.1f} GB free "
f"(required >= {min_free_gb:.1f} GB)."
)
# =============================================================================
# Utilities: External extractors with resilient fallback
# =============================================================================
class ExtractError(Exception):
"""Raised when archive extraction fails with all strategies."""
def _run_cmd(cmd: list[str]) -> tuple[int, str, str]:
p = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
return p.returncode, p.stdout, p.stderr
def _count_extracted_files(out_dir: str) -> int:
"""Count all files (recursively) in the output directory."""
count = 0
for root, dirs, files in os.walk(out_dir):
count += len(files)
return count
def extract_with_unar(archive_path: str, out_dir: str) -> None:
os.makedirs(out_dir, exist_ok=True)
rc, out, err = _run_cmd(["unar", "-o", out_dir, archive_path])
if rc != 0:
# Check if files were actually extracted (partial success)
# unar may return non-zero even when most files extracted successfully
extracted_files = _count_extracted_files(out_dir)
if extracted_files > 0:
# Partial extraction - log warning but continue
log.warning(f"unar partial extraction (rc={rc}): {extracted_files} files extracted from {archive_path}")
return
raise ExtractError(f"unar failed (rc={rc})\nSTDOUT:\n{out}\nSTDERR:\n{err}")
def extract_with_7z(archive_path: str, out_dir: str) -> None:
os.makedirs(out_dir, exist_ok=True)
rc, out, err = _run_cmd(["7z", "x", "-y", f"-o{out_dir}", archive_path])
if rc != 0:
# Check if files were actually extracted (partial success)
extracted_files = _count_extracted_files(out_dir)
if extracted_files > 0:
# Partial extraction - log warning but continue
log.warning(f"7z partial extraction (rc={rc}): {extracted_files} files extracted from {archive_path}")
return
raise ExtractError(f"7z failed (rc={rc})\nSTDOUT:\n{out}\nSTDERR:\n{err}")
def looks_password_protected_with_lsar(archive_path: str) -> bool:
"""Best-effort pre-check for 'Encrypted/Password' in lsar output."""
try:
rc, out, err = _run_cmd(["lsar", archive_path])
txt = (out + "\n" + err).lower()
return ("encrypted" in txt) or ("password" in txt)
except Exception:
return False
def extract_archive_resilient(archive_path: str, out_dir: str) -> None:
"""
Prefer unar for RAR/CBR (RAR5-friendly); fallback to 7z.
For other formats, try 7z first then unar.
Surfaces stderr so logs show CRC/password/permissions issues.
"""
lower = archive_path.lower()
errors = []
# Optional password hint to skip early
if lower.endswith((".rar", ".cbr")) and looks_password_protected_with_lsar(archive_path):
raise ExtractError("Archive appears password-protected; skipping (no password provided).")
if lower.endswith((".rar", ".cbr")):
order = (extract_with_unar, extract_with_7z)
else:
order = (extract_with_7z, extract_with_unar)
for fn in order:
try:
fn(archive_path, out_dir)
return
except ExtractError as e:
errors.append(str(e))
raise ExtractError("Both extractors failed:\n" + "\n---\n".join(errors))
# =============================================================================
# Content-addressed storage helpers
# =============================================================================
def build_hashed_dest_path(target_dir: str, original_name: str, content_hash: str) -> str:
"""
Always produce a content-addressed destination:
<target>/<name_without_ext>__<hash[:10]><ext>
If that path already exists, append a numeric suffix.
"""
base, ext = os.path.splitext(original_name)
candidate = os.path.join(target_dir, f"{base}__{content_hash[:10]}{ext}")
if not os.path.exists(candidate):
return candidate
# Rare: collision (e.g., concurrent import) → add counter
i = 2
while True:
candidate = os.path.join(target_dir, f"{base}__{content_hash[:10]}_{i}{ext}")
if not os.path.exists(candidate):
return candidate
i += 1
# =============================================================================
# Helpers: Thumbnails, metadata, hashing, similarity
# =============================================================================
def generate_thumbnail(
image_path,
size=(400, 400),
overwrite=False,
prefer_jpeg=False, # False = auto-pick PNG for alpha images; True = always JPEG
jpeg_bg=(0, 0, 0), # background used when flattening to JPEG
):
"""
Save thumbnails mirrored under /images/thumbs/<...>.
If prefer_jpeg is False (default), transparent images save as PNG, others as JPEG.
If prefer_jpeg is True, all thumbs are JPEG with transparency flattened to `jpeg_bg`.
For images with extreme aspect ratios (very tall like comic strips, or very wide),
crops to the center region before thumbnailing to produce better quality previews.
Returns the absolute path to the thumbnail.
"""
images_root = Path("/images").resolve()
image_path = Path(image_path).resolve()
try:
rel_path = image_path.relative_to(images_root)
except ValueError:
raise ValueError(f"{image_path} is not under {images_root}")
# Base path under /images/thumbs with same subfolders/filename (we may change the suffix)
thumb_base = (images_root / "thumbs" / rel_path).with_suffix("") # drop original suffix for control
# Decide output extension/format
with Image.open(image_path) as img:
img = ImageOps.exif_transpose(img) # honor camera rotation
# Handle extreme aspect ratios by cropping to a more balanced region
# This prevents very tall/wide images from becoming tiny slivers
w, h = img.size
aspect_ratio = w / h if h > 0 else 1
# If aspect ratio is extreme (< 0.5 means very tall, > 2.0 means very wide)
# crop to a more balanced region before thumbnailing
if aspect_ratio < 0.5:
# Very tall image (like comic strip) - crop from top portion
# Take a region that's closer to square, from the top
crop_height = min(h, w * 2) # At most 2:1 tall
img = img.crop((0, 0, w, crop_height))
elif aspect_ratio > 2.0:
# Very wide image - crop from center
crop_width = min(w, h * 2) # At most 2:1 wide
left = (w - crop_width) // 2
img = img.crop((left, 0, left + crop_width, h))
# Use LANCZOS resampling for high-quality downscaling
img.thumbnail(size, Image.Resampling.LANCZOS)
has_alpha = _has_alpha(img)
if prefer_jpeg:
# Force JPEG for consistency
out_path = thumb_base.with_suffix(".jpg")
out_path.parent.mkdir(parents=True, exist_ok=True)
if not overwrite and out_path.exists():
return str(out_path)
img_rgb = _flatten_to_rgb(img, bg=jpeg_bg)
img_rgb.save(out_path, format="JPEG", quality=85, optimize=True, progressive=True)
return str(out_path)
else:
# Auto-pick: PNG for alpha, JPEG otherwise
if has_alpha:
out_path = thumb_base.with_suffix(".png")
out_path.parent.mkdir(parents=True, exist_ok=True)
if not overwrite and out_path.exists():
return str(out_path)
# Keep transparency if present
# Convert palette to RGBA for reliable PNG writing
if img.mode == "P":
img = img.convert("RGBA")
img.save(out_path, format="PNG", optimize=True)
return str(out_path)
else:
out_path = thumb_base.with_suffix(".jpg")
out_path.parent.mkdir(parents=True, exist_ok=True)
if not overwrite and out_path.exists():
return str(out_path)
if img.mode != "RGB":
img = img.convert("RGB")
img.save(out_path, format="JPEG", quality=85, optimize=True, progressive=True)
return str(out_path)
def generate_video_thumbnail(video_path: str, output_path: str, time_position: str = "00:00:01") -> str | None:
"""
Extract a single JPG frame from a video using ffmpeg and write it to output_path.
Returns output_path on success, or None on failure.
"""
try:
os.makedirs(os.path.dirname(output_path), exist_ok=True)
cmd = [
"ffmpeg", "-y",
"-ss", time_position,
"-i", str(video_path),
"-vframes", "1",
"-vf", f"scale={THUMB_SIZE[0]}:-1",
str(output_path),
]
subprocess.run(cmd, check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=FFMPEG_THUMB_TIMEOUT)
return output_path
except subprocess.CalledProcessError as e:
print(f"[WARN] Failed to extract video thumbnail for {video_path}: {e}")
return None
def generate_video_thumbnail_mirrored(video_path: str, time_position: str = "00:00:01") -> str | None:
"""
Mirror the stored (hashed) video path under /images/thumbs/... and save as .jpg.
"""
images_root = Path("/images").resolve()
video_path_p = Path(video_path).resolve()
rel_path = video_path_p.relative_to(images_root) # raises if not under /images
thumb_path = (images_root / "thumbs" / rel_path).with_suffix(".jpg")
return generate_video_thumbnail(str(video_path_p), str(thumb_path), time_position=time_position)
def _probe_video_duration(video_path: str) -> float | None:
"""Return duration in seconds via ffprobe, or None on failure."""
try:
result = subprocess.run(
[
"ffprobe", "-v", "error",
"-show_entries", "format=duration",
"-of", "default=noprint_wrappers=1:nokey=1",
str(video_path),
],
capture_output=True, text=True, timeout=30, check=True,
)
return float(result.stdout.strip())
except (subprocess.CalledProcessError, subprocess.TimeoutExpired, ValueError):
return None
def extract_video_frames(video_path: str, count: int = 10) -> list[str]:
"""Extract `count` evenly-spaced JPEG frames from a video into tempfiles.
Frames are sampled between 10% and 90% of the video's duration so title
cards and black-fade endings don't dominate the sample. Returns a list of
absolute paths; the caller is responsible for deleting the containing
temp directory when done. Returns [] if duration probe fails or no frames
could be extracted.
"""
duration = _probe_video_duration(video_path)
if duration is None or duration <= 0:
return []
if count <= 1:
fractions = [0.5]
else:
fractions = [0.1 + 0.8 * (i / (count - 1)) for i in range(count)]
tmpdir = tempfile.mkdtemp(prefix="vframes_")
frame_paths: list[str] = []
for i, frac in enumerate(fractions):
t = duration * frac
out = os.path.join(tmpdir, f"frame_{i:02d}.jpg")
try:
subprocess.run(
[
"ffmpeg", "-y",
"-ss", f"{t:.3f}",
"-i", str(video_path),
"-vframes", "1",
out,
],
check=True,
stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL,
timeout=FFMPEG_THUMB_TIMEOUT,
)
if os.path.exists(out) and os.path.getsize(out) > 0:
frame_paths.append(out)
except (subprocess.CalledProcessError, subprocess.TimeoutExpired):
continue
if not frame_paths:
try:
os.rmdir(tmpdir)
except OSError:
pass
return frame_paths
def transcode_video_to_mp4(input_path: str, output_path: str = None) -> str | None:
"""
Transcode a video to H.264 MP4 for universal browser playback.
Args:
input_path: Path to source video file
output_path: Optional destination path. If None, replaces extension with .mp4
in a temp location.
Returns:
Path to transcoded MP4 file on success, None on failure.
"""
input_p = Path(input_path)
# Determine output path
if output_path is None:
# Create temp file with .mp4 extension
output_path = str(input_p.with_suffix(".mp4"))
if output_path == input_path:
# Already .mp4, use temp suffix
output_path = str(input_p.with_suffix(".transcoded.mp4"))
try:
os.makedirs(os.path.dirname(output_path), exist_ok=True)
# FFmpeg command for H.264/AAC transcoding with good browser compatibility
# -movflags +faststart: Enables progressive playback (moov atom at start)
# -preset medium: Balance between speed and compression
# -crf 23: Good quality (lower = better, 18-28 typical range)
# -c:v libx264: H.264 video codec
# -c:a aac: AAC audio codec
# -pix_fmt yuv420p: Pixel format for maximum compatibility
cmd = [
"ffmpeg", "-y",
"-i", str(input_path),
"-c:v", "libx264",
"-preset", "medium",
"-crf", "23",
"-pix_fmt", "yuv420p",
"-c:a", "aac",
"-b:a", "128k",
"-movflags", "+faststart",
str(output_path),
]
print(f"[INFO] Transcoding video: {input_path} -> {output_path}")
result = subprocess.run(
cmd,
check=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
timeout=FFMPEG_TRANSCODE_TIMEOUT
)
print(f"[INFO] Transcoding complete: {output_path}")
return output_path
except subprocess.TimeoutExpired:
print(f"[WARN] Video transcode timed out after {FFMPEG_TRANSCODE_TIMEOUT}s: {input_path}")
# Clean up partial output
if os.path.exists(output_path):
os.remove(output_path)
return None
except subprocess.CalledProcessError as e:
print(f"[WARN] Failed to transcode video {input_path}: {e}")
if e.stderr:
print(f"[WARN] FFmpeg stderr: {e.stderr.decode('utf-8', errors='ignore')[:500]}")
# Clean up partial output
if os.path.exists(output_path):
os.remove(output_path)
return None
except Exception as e:
print(f"[WARN] Unexpected error transcoding video {input_path}: {e}")
if os.path.exists(output_path):
os.remove(output_path)
return None
def needs_transcode(file_path: str) -> bool:
"""Check if a video file needs transcoding to MP4."""
ext = Path(file_path).suffix.lower()
return ext in VIDEO_EXTS_NEED_TRANSCODE
def calculate_hash(file_path: str) -> str:
hash_func = hashlib.sha256()
with open(file_path, "rb") as f:
for chunk in iter(lambda: f.read(1024 * 1024), b""): # 1MB chunks work well for big files
hash_func.update(chunk)
return hash_func.hexdigest()
def calculate_perceptual_hash(file_path: str, hash_size: int = 16):
"""
Calculate a perceptual hash for an image.
Args:
file_path: Path to the image file
hash_size: Size of the hash grid (default 16 for 256-bit hash)
hash_size=8 gives 64-bit, hash_size=16 gives 256-bit
Returns:
ImageHash object or None if hashing fails (e.g., for videos)
"""
try:
with Image.open(file_path) as img:
return imagehash.phash(img, hash_size=hash_size)
except Exception:
# videos or unreadable images land here (phash not applicable)
return None
def find_similar_image(phash, width: int, height: int, existing_phashes, threshold: int = 10):
"""
Find visually similar images and determine relationship.
Args:
phash: Perceptual hash of the new image
width: Width of the new image
height: Height of the new image
existing_phashes: List of (phash, width, height, image_id) tuples for existing images
threshold: Maximum Hamming distance to consider images similar
Default is 10 for 256-bit hashes (was 2 for 64-bit)
Returns:
tuple: (relationship, image_id) where relationship is one of:
- None: No similar image found
- "larger_exists": A larger or equal similar image exists (skip new image)
- "smaller_exists": A smaller similar image exists (supersede it)
image_id is the ID of the matching image, or None
"""
for existing_phash, ew, eh, image_id in existing_phashes:
try:
distance = phash - existing_phash
if distance <= threshold:
# Similar image found - check size relationship
if ew >= width and eh >= height:
# Existing is larger or equal - skip new image
return ("larger_exists", image_id)
elif width > ew or height > eh:
# New image is larger - supersede the existing one
return ("smaller_exists", image_id)
except Exception as e:
print(f"[WARN] Failed pHash comparison: {e}")
return (None, None)
def is_similar_image(phash, width: int, height: int, existing_phashes, threshold: int = 10) -> bool:
"""
Check if an image is visually similar to any existing larger image.
Legacy wrapper for find_similar_image - returns True only if a larger version exists.
"""
relationship, _ = find_similar_image(phash, width, height, existing_phashes, threshold)
return relationship == "larger_exists"
def extract_metadata(file_path: str) -> dict:
metadata = {
"file_size": None,
"width": None,
"height": None,
"format": None,
"camera_model": None,
"taken_at": None
}
metadata["file_size"] = os.path.getsize(file_path)
ext = os.path.splitext(file_path)[1].lower()
# Get file modification time as fallback for taken_at
try:
file_mtime = datetime.fromtimestamp(os.path.getmtime(file_path))
except Exception:
file_mtime = None
# Video: use ffprobe
if ext in (".mp4", ".mov"):
try:
cmd = [
"ffprobe", "-v", "error",
"-select_streams", "v:0",
"-show_entries", "stream=width,height",
"-of", "json", file_path
]
result = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True, check=False)
data = json.loads(result.stdout or "{}")
stream = data.get("streams", [{}])[0]
metadata["width"] = stream.get("width")
metadata["height"] = stream.get("height")
metadata["format"] = ext.lstrip(".")
# Use file mtime for videos since they don't have EXIF
metadata["taken_at"] = file_mtime
except Exception as e:
print(f"[WARN] Failed to extract video metadata: {file_path} {e}")
return metadata
# Image: PIL + EXIF (best-effort)
try:
with Image.open(file_path) as img:
metadata["width"], metadata["height"] = img.size
metadata["format"] = (img.format or "").lower()
except Exception as e:
mime_type, _ = mimetypes.guess_type(file_path)
print(f"[WARN] Failed to read image metadata: {file_path} ({e}) ext={ext} mime={mime_type}")
try:
with open(file_path, "rb") as f:
tags = exifread.process_file(f, stop_tag="UNDEF", details=False)
if "EXIF DateTimeOriginal" in tags:
metadata["taken_at"] = datetime.strptime(str(tags["EXIF DateTimeOriginal"]), "%Y:%m:%d %H:%M:%S")
if "Image Model" in tags:
metadata["camera_model"] = str(tags["Image Model"])
except Exception:
pass
# Fallback to file modification time if no EXIF date
if metadata["taken_at"] is None:
metadata["taken_at"] = file_mtime
return metadata
def _has_alpha(img: Image.Image) -> bool:
"""Return True if the image has any transparency channel."""
if img.mode in ("RGBA", "LA"):
return True
if img.mode == "P" and "transparency" in img.info:
return True
return False
def _flatten_to_rgb(img: Image.Image, bg=(0, 0, 0)) -> Image.Image:
"""
Flatten an RGBA/LA/Palette-with-alpha image onto a solid background,
returning an RGB image suitable for saving as JPEG.
"""
# Normalize to RGBA so we can use the alpha channel as a mask
if img.mode == "P":
img = img.convert("RGBA")
if img.mode in ("RGBA", "LA"):
# Ensure we have an explicit alpha channel as last band
if img.mode == "LA":
img = img.convert("RGBA")
alpha = img.split()[-1] # A channel
bg_img = Image.new("RGB", img.size, bg)
bg_img.paste(img, mask=alpha)
return bg_img
# No alpha, just convert to RGB
return img.convert("RGB")
# =============================================================================
# Helpers: Multi-part detection
# =============================================================================
def is_first_volume(path: str) -> bool:
"""
Determine if 'path' is the first volume of a multi-part archive.
We only attempt extraction from the first volume.
"""
name = os.path.basename(path).lower()
# RAR: .partN.rar (only N==1 is first)
m = RAR_PART_RE.search(name)
if m:
n = m.group(1)
return n in ("1", "01", "001")
# RAR old-style: first is .rar, subsequent are .r00, .r01...
if name.endswith(".rar"):
return True
if OLD_RAR_VOL_RE.search(name):
return False
# CBR is typically a single-volume RAR
if name.endswith(".cbr"):
return True
# 7z multi-part: .7z.001 is first
m = SEVENZ_PART_RE.search(name)
if m:
n = m.group(1)
return n in ("1", "01", "001")
if name.endswith(".7z"):
return True # single-volume 7z
# ZIP and tarballs: treat as single-volume (we don't include .z01 in our allowlist)
if name.endswith((".zip", ".tar", ".tar.gz", ".tgz", ".tar.bz2", ".tbz2", ".tar.xz", ".txz")):
return True
return True
def extract_archive_name(filename: str) -> str:
"""
Extract a clean archive name from a filename by removing common prefixes.
Handles patterns like:
- "43387617_attachment_83109081_October 2020 Rewards.rar" -> "October 2020 Rewards"
- "01_Archive Name.zip" -> "Archive Name"
- "Archive Name.rar" -> "Archive Name"
Returns the cleaned name without extension.
"""
import re
from pathlib import Path
# Remove extension
stem = Path(filename).stem
# Pattern 1: Gallery-DL style "{id}_attachment_{id}_{name}" or "{id}_{name}"
# Match one or more numeric_prefix patterns at the start
cleaned = re.sub(r'^(\d+_)+(attachment_)?(\d+_)?', '', stem)
# Pattern 2: Simple numeric prefix "01_name" or "001_name"
if cleaned == stem: # No match from pattern 1
cleaned = re.sub(r'^\d+_', '', stem)
# If we stripped everything or got empty, fall back to original stem
if not cleaned.strip():
cleaned = stem
return cleaned.strip()
def compute_archive_tag_name(artist: str, archive_filename: str) -> str:
"""
Generate an archive tag name in the format: '{artist}:{archive_name}'
Similar to post tags (post:{platform}:{artist}:{id}), archive tags use
a consistent prefix and colon-separated components.
Examples:
- artist="InCaseArt", filename="43387617_attachment_83109081_October 2020 Rewards.rar"
-> "InCaseArt:October 2020 Rewards"
If a tag with the same name already exists, appends a numeric suffix.
"""
archive_name = extract_archive_name(archive_filename)
base_name = f"{artist}:{archive_name}"
# Check if tag already exists
existing = Tag.query.filter_by(kind='archive', name=base_name).first()
if not existing:
return base_name
# Tag exists, add numeric suffix
n = 2
while True:
candidate = f"{base_name} ({n})"
if not Tag.query.filter_by(kind='archive', name=candidate).first():
return candidate
n += 1
def compute_next_archive_tag_name(artist: str, width: int = ARCHIVE_NUM_WIDTH) -> str:
"""
DEPRECATED: Use compute_archive_tag_name() instead.
Return a unique incremental tag name like: '{artist}/0001', '0002', ...
- Looks only at Tag(kind='archive') with names starting '{artist}/'
- Finds max numeric suffix and returns next number (zero-padded).
- Ensures no collision even if tags were renamed.
"""
prefix = f"{artist}/"
# Pull existing tag names for this artist/prefix
rows = (Tag.query
.with_entities(Tag.name)
.filter(Tag.kind == 'archive',
Tag.name.like(prefix + '%'))
.all())
max_n = 0
for (name,) in rows:
tail = name[len(prefix):]
if tail.isdigit():
try:
n = int(tail)
if n > max_n:
max_n = n
except Exception:
pass
# Propose next number and make sure it doesn't already exist
n = max_n + 1
while True:
candidate = f"{prefix}{str(n).zfill(width)}"
if not Tag.query.filter_by(name=candidate).first():
return candidate
n += 1