Image sequences
FreeTreat numbered frames as one board item.
Image sequences collapse numbered still frames into one board item so render outputs, animation frames, timelapse sets, and burst-like frame runs do not flood the canvas. A sequence keeps the full frame list, uses a representative preview from the first frame, draws a sequence corner marker when enabled, and can be expanded back into individual images from the item context menu.
Screenshot coming soon
FenSight image sequence item with a corner marker and frame-count overlay
Sequence access paths
File -> Import Folder...
Detects numbered image runs during folder ingest before layout, then imports each detected run as one ImageSequenceItem.
Explorer -> drag a folder or numbered frame set onto the canvas
Canvas drops use the same DetectImageSequences pass before placing remaining individual files.
Image item -> Collapse sequence
Select at least three related ImageItem frames, or right-click a frame in a detected run, to collapse them into one sequence item.
Image sequence item -> Expand sequence
Replaces the sequence with individual ImageItem frames at the sequence position, then runs thumbnail/high-res backfill as needed.
View -> Sequence Corner Marker
Shows or hides the upper-left sequence triangle on sequence items.
Settings -> Overlay -> Show image sequence corner marker
Persists the same sequence marker preference through ShowSequenceCornerBadge.
Settings -> Performance -> Sequence split gap (sec)
Defaults to 1.0. Values are clamped from 0.1 to 120.0 seconds.
Settings -> Index Roots -> Gen thumbs / Build all
The thumbnail generation flow can backfill the sequence-detection cache so later imports do not re-detect every directory cold.
Detection rules
FenSight detects sequences per directory before creating board items. All of these gates must pass, which prevents ordinary numbered photos from being collapsed accidentally.
Sequence item behavior
Commands and settings
Cache and performance model
Sequence detection can be expensive in very large directories because it must inspect filenames, file sizes, timestamps, and sample dimensions. FenSight keeps a per-directory sequence-detection cache under the configured cache root to avoid repeating that work when the directory candidate count is unchanged.
- The cache file is sequence-detection-cache.json.
- Each directory cache entry is keyed by the candidate image file count; if files are added or removed, that directory is re-detected.
- Settings -> Index Roots thumbnail generation can backfill the same cache used by ingest.
- Detection checks cancellation every 50 files so cancelling a large sequence pass does not wait for the full directory to finish.
Common edge cases
Sequence detection is intentionally conservative. If a numbered run remains as individual images, one of the validation rules probably failed.
- Two-frame runs are not collapsed; a sequence requires at least three frames.
- Names with fewer than three trailing digits are not treated as sequence frames.
- Mixed padding, mixed extensions, missing frame numbers, large size variance, or mismatched dimensions will keep frames separate.
- Long-exposure timelapse or bracketed captures may need a larger Sequence split gap (sec) value.
- If timestamp reads fail, the timestamp-gap splitter leaves the numeric run intact rather than inventing split points.
Image sequence detection, collapse/expand commands, sequence overlays, sequence cache, and source-path expansion are Free. AI/index behavior that consumes sequence previews follows the tier of the AI feature itself.
Connected guides
Follow these related pages when the workflow crosses into setup, search, organization, export, security, or another board-level system.