VRC Photo Manager

A Windows desktop tool for curating and uploading VRChat photos to VRCDN object storage — browse a thumbnail grid, pick what goes up and what doesn't, and track upload status per photo, instead of blanket-uploading a whole library by filter alone.

⚠️ Not affiliated with VRCDN. This is an independent, unofficial, community-made tool. It is not endorsed by, sponsored by, or connected to VRCDN in any way. It talks to VRCDN's panel via an API discovered through normal browser inspection of the public web UI — not a published or supported integration — and VRCDN could change or break it at any time without notice. "VRCDN" is a trademark of its respective owner; this project's icon is an original design and does not use VRCDN's logo or branding.

Features

• Thumbnail grid — adjustable size, hover preview (after a brief pause so scrolling doesn't spam previews), scrolls smoothly through large libraries via real UI virtualization. Click a thumbnail (or its checkbox) to select it.
• Filter & sort — by rating, upload status, VRCX player/author name (substring match), and sort by filename or capture date (newest/oldest first).
• Per-photo badges — upload status (Not Uploaded / Uploading / Uploaded / Failed), content rating, detected-face count, and whether VRCX metadata was found for that photo.
• Local nudity/content classifier — runs the open WD14 tagger model in-process via ONNX Runtime (DirectML-accelerated), entirely on-device. No photos or classification results leave your machine for this step.
• Local anime-face detection — Scan Faces finds anime-style faces (an LBP cascade trained for stylized/rendered faces, since detectors trained on real photos miss VRChat avatars) and shows a per-photo face count. Ships bundled with the app, no separate setup.
• VRCX metadata capture — Scan Library reads the author, world, and player list VRCX embeds directly into each screenshot's PNG metadata at capture time (both display names and stable VRChat user IDs), when VRCX was running to record it. Right-click a photo → View Metadata... to see everything captured for it.
• Crop Print Borders — detects photos in VRChat's in-game "Print" format (padded to 2048×1440) and crops the white border back to the real 1920×1080 content, without touching the original file.
• SQLite-backed, EF Core 10 — tracks local file metadata, ratings, and per-photo upload status, with automatic migrations on startup.
• Session login via embedded WebView2 — no external browser required; the login flow happens inside the app.
• Sync Metadata — reconciles the local index against what's actually on VRCDN (matching by filename, with a fallback for objects uploaded under a reformatted name by an older tool), so a fresh install doesn't risk re-uploading photos that already made it up some other way. Safe to re-run any time.
• Upload Selected / Remove from VRCDN — upload picks resize to fit VRChat's image-loader limits before going up; Remove deletes selected, already-uploaded photos from VRCDN's storage (confirmed first — there's no undo except re-uploading).
• Settings screen — configure where the WD14 model files live, with a one-click download straight from Hugging Face (see Local classifier setup).

Requirements

• Windows 10/11
• .NET 10 SDK (or the runtime, if only running a published build)
• WebView2 Runtime (ships with Windows 11 by default; Windows 10 may need it installed separately)
• A VRCDN account with panel access

Building & running

dotnet build
dotnet run

On first run, click Login to authenticate via the embedded browser, then Scan Library to index a folder of photos.

Local classifier setup

The nudity/content classifier (Classify Photos) needs two files from the SmilingWolf/wd-vit-tagger-v3 model (or a compatible WD14-family model):

model.onnx           (~378 MB)
selected_tags.csv    (~300 KB)

Easiest way: open Settings in the app, browse to (or type) a folder for the model files, and click Download Model Files — it fetches both directly from Hugging Face and saves the folder for next time. Restart the app afterward for it to pick up the change.

Manual alternative: download both files yourself into a wd14-model folder next to the built exe:

wd14-model\model.onnx
wd14-model\selected_tags.csv

If neither is set up, Classify Photos is simply disabled at startup (with a status-bar message saying so) — everything else works normally, including the anime-face detector, which is bundled with the app and needs no separate download.

Planned work

• Import/export lists — a general mechanism to import and export the ratings list and the registered-people/tag list (currently only a per-machine SQLite table), so this data isn't locked to one machine's database. Replaces the old narrow "Import Ratings" feature (removed - it only read from one specific external WD14-pipeline index.db format).

How the VRCDN integration works

There's no published VRCDN API. This app replicates the same request flow the browser makes to VRCDN's panel — request a presigned upload URL, then PUT the file directly — reverse engineered by inspecting the panel's own network traffic. It is not guaranteed to keep working if VRCDN changes their panel implementation.

License

MIT — see LICENSE.