Release v1.10.0 · nyattic/CloakFrame

Hardens how Redactly reads and writes files end-to-end and scales processing
up for very large photos and videos.

Output files are published atomically inside the chosen output folder using
symlink-safe, no-replace writes on every platform, so crafted links or files
swapped mid-run can never redirect or overwrite results outside it
Videos are processed from a private snapshot of the source, so edits or
swaps to the original while a run is in progress cannot affect the output
Built-in detection models are verified against a pinned SHA-256 digest
before they are loaded, and custom ONNX models get stricter shape and type
validation
Image containers (TIFF, PNG, WebP, animated formats) are parsed with strict
bounds and overflow checks before decoding

Large media limits are now generous: input files up to 2 GB and images up
to 512 megapixels are accepted, and the image pipeline adapts its
parallelism to available memory instead of using a fixed thread count
Crowded scenes track more reliably: up to 1024 detections per frame and
65,536 tracks per video are supported, and license plate detection handles
denser candidate sets
A single unreadable file in a batch no longer slows down processing of the
remaining items
Loaded detection models are reliably reused between runs, including on
systems where GPU acceleration falls back to the CPU, making repeat runs
start much faster
Detection results with invalid coordinates are filtered out before
matching, fixing rare inconsistent masking on corrupted frames
A face seen clearly in just a single frame is now kept and masked instead
of being discarded as noise
Saving to drives that do not support atomic no-replace renames (exFAT or
FAT32 USB drives, SD cards, and some network shares) now works on macOS

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