media_organizer

Pub Version License: MIT

Normalize photos and videos into self-describing, sortable, dedup-friendly filenames — then they're easy to manage anywhere (local, Google Drive, NAS).

<YYYYMMDDTHHmmss>[_<place>]_<sizeBytes>_<md5-8>.<ext>
20260615T091500_Taipei_1048576_9f3ab2c1.jpg
  • Sortable — sort by name = sort by capture time.
  • Self-describing — capture time + optional place are in the name.
  • Dedup-friendly — the trailing <size>_<md5-8> is a content key; identical bytes ⇒ identical key, so duplicates are detected without a database.

Ships as a CLI and a library, pure dart:io — runs on desktop and mobile (import the library on tablets/phones; not web).

CLI

dart pub global activate media_organizer

# Organize: rename + dedup into an output folder
media_organizer organize -i ~/Camera -o ~/Organized
media_organizer organize -i ~/Camera -o ~/Organized --move       # move, not copy
media_organizer organize -i ~/Camera -o ~/Organized --dry-run    # preview only
media_organizer organize -i ~/Camera -o ~/Organized --verify     # re-hash each copy
#   --move always verifies first: a copy is re-hashed and only on a match is the
#   original deleted, so a bad copy never loses an original. Ctrl-C stops
#   cleanly after the current file; a live [i/total] line shows progress.
media_organizer organize -i ~/Camera -o ~/Organized --transcode  # re-encode videos
#   --transcode re-encodes videos to 1080p H.264 + faststart via ffmpeg.
#   Needs ffmpeg on PATH (or --ffmpeg <path>); if missing it prints install
#   instructions and exits without touching your files.

# Stats: total + per-month photo/video counts (no database — reads the names)
media_organizer stats ~/Organized
#   Total: 120 (95 photos, 25 videos)
#     2026.01    12 photos     3 videos
#     2026.02     8 photos     1 videos

In this repo you can run it without installing:

dart run bin/media_organizer.dart organize -i <in> -o <out>
dart run bin/media_organizer.dart stats <folder>
dart run tool/demo.dart        # organizes the bundled example/demo_input

stats needs no database — the filename is the index (capture time + kind are in the name), so it works on any folder of normalized files.

Library

import 'package:media_organizer/media_organizer.dart';

final report = await MediaOrganizer().run(
  input: '/camera',
  output: '/organized',
  verify: true, // re-hash each copy (forced on when move: true)
  onProgress: (p) => print('[${p.index}/${p.total}] ${p.path}'),
  cancelled: () => false, // return true to stop the run cleanly
);
print(report); // organized / duplicates / failed

Pluggable (cross-platform by design)

The engine is platform-independent; the platform-specific or networked parts are injectable interfaces with safe defaults:

  • MediaProbe — capture time + GPS. Default CompositeMediaProbe routes by kind: ExifMediaProbe (image EXIF) for photos, Mp4MediaProbe (parses the MP4/MOV moov box — Apple creationdate, mvhd time, ISO-6709 GPS) for videos, then falls back to the file's modified time when neither has a date.
  • LocationResolver — GPS → place label for the filename. Default: none (no network). Ships with OfflineGeocoder (haversine nearest-neighbour, fully offline, no API key) — see Offline geocoding.
  • MediaTranscoder — optional transcode before output. Default PassthroughTranscoder (no transcode). A ready-made FfmpegTranscoder re-encodes videos to 1080p H.264 + faststart (FfmpegTranscoder.isAvailable() / FfmpegTranscoder.installHint() let you detect ffmpeg and guide the user); it shells out to ffmpeg and reads/writes real files, so use it with LocalFileSystem.
  • MediaFileSystem — all file IO (list/read/copy/delete) goes through this. Default LocalFileSystem uses dart:io (desktop + mobile). Inject your own for an alternate source or fully in-memory tests — the engine itself never touches dart:io. (dart:io covers every native platform; only web lacks it, and a folder organizer can't run in a browser anyway.)
MediaOrganizer(
  probe: MyVideoAwareProbe(),
  locationResolver: MyGeocoder(),
  transcoder: FfmpegTranscoder(),
);

Upload (Google Drive / NAS)

NAS needs no code — it's a mount, so just organize straight into it:

media_organizer organize -i ~/Camera -o /Volumes/nas/Photos

For cloud targets, UploadTarget is a tiny injectable sink that consumes an organize run. The core stays SDK-free — implement the target in your app (or a side package) with whatever client you like:

final report = await MediaOrganizer().run(input: '/camera', output: '/staged');
final upload = await MediaUploader(target: MyDriveTarget()).run(report.organized);
print(upload); // uploaded / skipped / failed

The same content key that dedups locally also dedups remotely: a target reports the keys it already has via existingContentKeys(), so re-runs upload only what's new (and identical bytes within one run upload once). See test/upload_target_test.dart for the FakeUploadTarget skeleton a real Drive/S3/SFTP target follows.

Offline geocoding

OfflineGeocoder turns the GPS in a photo into the nearest place name for the <place> slot — fully offline, no API key. The core ships no geo data: you pass the place list, so the package never bundles (or assumes a format for) a dataset.

final geocoder = OfflineGeocoder(const [
  GeoPlace('Taipei', 25.0330, 121.5654),
  GeoPlace('Kaohsiung', 22.6273, 120.3014),
  // …
], maxDistanceKm: 50); // farther than this ⇒ no place

await MediaOrganizer(locationResolver: geocoder).run(input: '/camera', output: '/out');
// 20260115T083000_Taipei_2187_de2c09bb.jpg

For real coverage, load a dataset into List<GeoPlace> and localize names by choosing what you put in GeoPlace.name:

  • example/offline_geocoder_example.dart — inline cities + a parseGeoNamesCities helper for GeoNames. Get the data from download.geonames.org: the citiesN.zip files list places with population > N. For reverse-geocoding prefer the dense cities500 (~200k) or cities1000 (~140k); cities5000/ cities15000 are major-cities-only (coarse for reverse, fine for a picker).
  • example/immich_geodata_example.dart — reads the already zh-TW localized CSVs from immich-geodata-zh-TW (latitude,longitude,country,admin_1..4); a Taipei 101 photo comes out as …_臺北市-信義區_…. Fully offline — you supply the downloaded CSV path.

The lookup is a linear scan (fine for thousands of points; a country file like tw is ~8k); for a full global set, wrap it with a spatial index in your app.

Which geocoding strategy?

LocationResolver is just an interface — pick the backing that fits your context (they all inject the same way, no core change):

Strategy Best for Trade-offs
Offline dataset (OfflineGeocoder + GeoNames / immich-geodata) CLI / batch over thousands of files Reproducible, no rate limits, works offline. You ship/download the data; names only as precise as the dataset.
Platform geocoder (iOS/macOS CLGeocoder, Android Geocoder, via the geocoding plugin) Interactive Flutter app, modest volume Best names, auto-localized, no data to ship. But it's an online call, rate-limited (bad for big batches), and Apple/Android-only — so it lives in your app, not this pure-Dart core.
Offline-first hybrid Want quality and scale Resolve offline first; only fall back to the platform geocoder on a miss, and cache results (rounded coords → name) so a trip's worth of nearby photos doesn't hammer the API. 
// Hybrid sketch (lives in your app — the platform geocoder is not pure Dart):
class HybridGeocoder implements LocationResolver {
  HybridGeocoder(this.offline, this.platform);
  final LocationResolver offline;
  final LocationResolver platform; // e.g. backed by package:geocoding
  final _cache = <String, String?>{};

  @override
  Future<String?> resolve(double lat, double lng) async {
    final key = '${lat.toStringAsFixed(2)},${lng.toStringAsFixed(2)}';
    return _cache[key] ??=
        await offline.resolve(lat, lng) ?? await platform.resolve(lat, lng);
  }
}

Geo-data licensing

This package bundles no geo data — you supply it — so nothing here is encumbered. But the datasets the examples point at carry their own licenses, and complying is the responsibility of whoever ships them:

  • GeoNames — CC BY 4.0: free (incl. commercial), attribution required.
  • SimpleMaps (free tier) — CC BY 4.0: attribution required.
  • OpenStreetMap (and OSM-derived data, e.g. the immich-geodata sets) — ODbL 1.0: attribution (“© OpenStreetMap contributors”) and share-alike on a derived database you distribute.
  • Natural Earth — public domain; Wikidata — CC0 (public domain).

Note: the immich-geodata-zh-TW project code is GPL v3, but this package only reads its data output (governed by the data licenses above) — it does not include or link that code, so your MIT package stays MIT.

Filename helper

MediaFilename.build(...) / MediaFilename.parse(name) give you the scheme on its own (e.g. to sort or group an existing library).

Status & limits

  • Capture time: image EXIF for photos, MP4/MOV moov for videos, with a file-mtime fallback. Containers without embedded time (e.g. some camera/transcoded clips) use mtime. mvhd time is treated as UTC; an Apple creationdate (with a real timezone) is preferred when present.
  • Geocoding is not built in — it's an injectable interface (no network by default). Transcoding is opt-in via FfmpegTranscoder (needs ffmpeg installed); the core itself stays ffmpeg-free. Upload targets (Google Drive / NAS) are out of scope for the core and layered on top.
  • No web (uses dart:io).

License

MIT

Libraries

media_organizer
Normalize photos and videos into self-describing, sortable, dedup-friendly filenames (<datetime>[_<place>]_<size>_<md5-8>.<ext>). CLI + library.