Commit Graph

8 Commits

Author SHA1 Message Date
3e6e733a9d [0.0.13] Segmentation phase 4: per-folder opt-in, the segmentation scan, -segment
- .library-folders in the library (src/app/library_folders.jai): each library folder's options,
  starting with segment: true. Every folder starts off; unknown keys are kept when it is rewritten.
- The Segmentation window (Segments, above the grid): each folder's Segment checkbox, how many of
  its images are segmented, and Erase per folder; a button to segment the folders set to segment.
- The segmentation scan (src/app/segment_ui.jai) runs on the OCR thread as its own task, with the
  OCR scan's progress, pause and cancel: images only (never videos), not yet segmented, in folders
  set to segment. The engine loads with the first scan (2.4 GB of GPU memory). Each image's segs and
  mask are stored in one rewrite and its catalog entry loaded again.
- Importing into a folder set to segment segments the new images; the Import window's checkbox is
  the folder's setting.
- -segment segments and exits; -erase segments, and -erase all now includes segments.
- The catalog reads each capture's segs (class list hash, segment count). The exit overlay names the
  segmentation scan and model. segment_mcap_chunks moved into modules/Segment, shared with
  segment-probe. The quoting helpers of Capture_File's text formats are public.
- Tests: .library-folders read and written back (quoted names, unknown keys, versions).
2026-10-10 04:13:03 +01:00
8b6602119a [0.0.12] Segmentation phase 3: segs and mask chunks in .mcap files
- modules/Capture_File/segment_chunks.jai: a front "segs" chunk (text: engine, date, the image read
  and its size, the class list's hash, and each segment's id, score, area, box and class) and a back
  "mask" chunk (a segment id per pixel, run-length encoded with LEB128 lengths, longest side at most
  1024), keyed by model. No new file version: chunks came in version 3.
- mcap_store takes back chunks too, so a model's summary and mask are stored in one rewrite.
- Tests: the text round trip, the runs' edge cases (one segment over everything, none, runs across
  rows, multi-byte lengths, id 255), bad masks refused, and storing, replacing and erasing both
  chunks in a file with other chunks kept.
- segment-probe takes .mcap files (the image each is shown as; videos skipped) and with -store stores
  its segments in them. On 27 images a mask is 0.8 to 6.4 KB.
- The format README's "Segmentation chunks" section; the plan's phase 3 results.
2026-10-10 03:44:41 +01:00
cb21b73460 [0.0.11] Segmentation phases 1-2: Mask2Former exported to ONNX, and modules/Segment to run it
- segmentation-plan.html: the plan for panoptic segmentation of images, per library folder, stored
  in .mcap chunks (no file version bump), in six phases.
- tools/export_mask2former.py: exports facebook/mask2former-swin-base-coco-panoptic to ONNX (opset 17,
  dynamic batch, 384 x 384 input) and checks it against PyTorch: on 25 images, all 180 segments
  identical (IoU 1.000). Writes the class list with names for people ("sky-other-merged" is "sky"),
  and PyTorch's own segmentations for segment-probe -check.
- modules/Segment: runs the model with onnxruntime (CUDA, else the CPU) and makes segments of its
  outputs as transformers' post_process_panoptic_segmentation does: a segment id map (longest side at
  most 1024) and each segment's class, score, area and bounds. Matches PyTorch on 99.8% of pixels,
  every segment scored 0.6 or more found. 57 ms an image at batch 4 on an RTX 5080 laptop.
- tools/segment_probe.jai (jai first.jai - segment_probe): segments image files; -out draws them,
  -check compares with PyTorch, -dump-input writes the model's input.
- modules/onnxruntime: ort_run_float_outputs, for a model with several outputs.
- first.jai copies the model to bin/segment-models. The model itself is not in git
  (modules/Segment/models, 462 MB); tools/export_mask2former.py makes it.
2026-10-10 03:39:28 +01:00
baa188b0e4 [0.0.9] Import: videos and animated GIFs, in .mcap version 4
- Import brings in videos (MP4, MOV, MKV, WebM, AVI, WMV, MPEG, MTS/M2TS, FLV) on Windows, read with
  FFmpeg: the file as it was in the original, a frame a tenth of the way in (at most 3 s), turned
  the right way up, as the rendered image (what the grid, Capture window, OCR and labels see), and
  import.json with Duration, FrameRate, VideoCodec, Rotation, PosterTime, Audio, and the camera,
  date and location from the container. Elsewhere videos are skipped as "video (Windows only)".
- .mcap version 4: the original's size is a u64, so a video can be any size. Versions 1-3 still read.
  mcap_read_without_original and mcap_write_streamed read and rewrite a file with its original left
  on disk; mcap_store, mcap_erase, the import index and the import itself never hold a video in memory.
- Animated GIFs: Frames and Duration in import.json (gif_info).
- Grid: a play mark and duration on video thumbnails, GIF on animations. Capture window: what the
  video is, and Play in the default player (written out to %TEMP%\mcap).
- modules/ffmpeg: FFmpeg 6.0 bindings and the five DLLs used (avformat, avcodec, avutil, swscale,
  swresample), copied beside the executable by the build.
  swscale converts into a buffer of its own allocator with padded rows: an exact-sized one let
  its SIMD write past the end, crashing on frames of odd widths (1916, 1106 ...).
- image-probe shows videos and GIF frame counts; ocr-bench reads a video's frame.
- Tests: new video formats, display-matrix rotation, ISO 6709, video dates, GIF frames, and v4
  serialize/parse, v3 compatibility, streamed writes, store/erase and extraction.

SnagitConverter's copy of Capture_File needs syncing to read version 4 files.
2026-10-09 23:10:55 +01:00
811c096dd0 [0.0.8] Import: any folder of screenshots and photos into the library, a folder for each source
- Import window (and -import SOURCE DEST): every image under a folder (PNG, JPEG, HEIC, AVIF, WebP,
  GIF, BMP, TIFF, camera RAW) becomes an .mcap holding the file as it was, a preview turned by its
  EXIF orientation, and metadata.json and import.json Capture Text (date from EXIF, the file name or
  its time; file name as title; camera as app). .snagx files become the same .mcap SnagitConverter
  makes. Duplicates across the whole library are skipped by a hash index (.import-index); videos
  and sidecars are skipped; source files are only read.
- modules/Image_Decode: stb_image, then WIC for everything else; EXIF; orientation; previews.
  tools/image_probe.jai shows what it reads.
- modules/Snagx (and modules/jaison), copied from SnagitConverter.
- The library is a folder of folders: recursive scan, a folder filter, and a folder: search prefix.
- OCR, the viewer and ocr-bench decode any image format, turned the right way up.
- Rename D:\SnagitIndex to D:\McapIndex.
2026-10-09 08:15:12 +01:00
e2334e8be5 [0.0.0] OCR on the GPU: measured defaults for memory and batching; scan progress bars 2026-10-07 22:27:29 +01:00
ea9f055abc [0.0.0] .mcap version 2: OCR stored in each capture, search, a library scan, sorting by date; turned text 2026-10-07 21:51:18 +01:00
bb94f03b94 [0.0.0] OCR: an onnxruntime module and an OCR module, PP-OCRv5 mobile and server, on the GPU through CUDA when it can 2026-10-07 20:45:05 +01:00