New tool for joining images horizontally or vertically,
distinct from the grid-based collage tool. Preserves aspect
ratios with fit/original resize modes, optional gap, and
multi-format output.
Users running lite mode had no way to tell why AI tools were greyed out.
Now the public health endpoint reports the variant, and a visible banner
appears in the tool panel when running in lite mode.
- Replace OpenCV Haar Cascades with MediaPipe for face detection, using
short-range model first with full-range fallback for better accuracy
- Add auto-orient to remove-background route for EXIF-rotated photos
- Change default background removal model from u2net to birefnet-general-lite
- Fix flaky test by setting SQLite busy_timeout before journal_mode pragma
Co-authored-by: Siddharth Kumar Sah <siddharth123sk@gmail.com>
Batch progress was broken because JobProgress events lacked a `type`
field. The frontend checks `data.type === "batch"` to distinguish batch
from single-file SSE events, so batch progress was silently discarded
and multi-file processing appeared stuck at 15%.
Also improves the processing UX for non-AI (Sharp-based) tools: the
progress bar now pulses during the server processing phase and shows
a "This may take a moment" hint after 10 seconds.
Co-authored-by: Siddharth Kumar Sah <siddharth123sk@gmail.com>
AI routes (remove-background, erase-object, ocr, blur-faces, upscale)
were silently swallowing errors - failures returned HTTP 422 to the
client but never appeared in server logs. This made it impossible for
self-hosters to diagnose issues like 504 timeouts from reverse proxies.
Adds request.log.info() at processing start (tool name, image size, key
settings) and request.log.error() in catch blocks, matching the existing
tool-factory pattern.
Co-authored-by: Siddharth Kumar Sah <siddharth123sk@gmail.com>
Prevent silent data corruption when the API is called directly
(bypassing UI guards). Binary/complex EXIF fields like MakerNote
are now filtered from fieldsToRemove in the image-engine operation.
Move sanitizeValue, parseExif, parseGps, parseXmp into the shared
image-engine package so both strip-metadata and edit-metadata can
reuse them. Includes 13 unit tests covering all four functions.
Design spec for new edit-metadata tool (issue #15). Covers common EXIF
field editing, GPS clearing, granular per-field stripping, and shared
metadata infrastructure extracted from strip-metadata.
* feat: add resolveOutputFormat utility for input format preservation
* fix: preserve file order in batch processing with X-File-Results header
Collect all results before streaming the ZIP to guarantee upload order.
Replace X-File-Order with index-based X-File-Results header that maps
each upload index to its processed filename, handling failures and
duplicate filenames correctly.
Closes#13
* fix: use X-File-Results for index-based batch file matching
The frontend now matches processed files to entries by upload index
instead of fragile name/position matching.
* feat: preserve input format in smart-crop with quality control
Smart crop now outputs in the same format as the input (JPG in, JPG out)
instead of always converting to PNG. Adds an optional quality setting
(default 95) for lossy formats.
Closes#14
* feat: add output quality slider to smart crop settings UI
* feat: preserve input format in crop tool
* feat: preserve input format in color adjustment tools
Applies to brightness-contrast, saturation, color-channels, and
color-effects tool routes.
* refactor: avoid double encode in smart-crop content mode
For the simple trim path (no pad-to-square), chain .toFormat() on the
trim pipeline directly instead of creating a second Sharp instance.
This eliminates a redundant intermediate encode that degraded quality
for lossy formats. Also use trimmed.info dimensions instead of a
separate metadata() call for the pad-to-square path.
---------
Co-authored-by: Siddharth Kumar Sah <siddharth123sk@gmail.com>
Clickable localhost:1349 links are misleading on the GitHub Pages site
since users may not have Stirling Image running locally. Use plain path
references instead so it is clear these live on their own instance.
The links used /Stirling-Image/ (wrong casing) which VitePress then
prefixed with the base /stirling-image/, producing a double-prefixed
404 path. Remove the manual base so VitePress prepends it automatically.
Keep the main docker run command front and center. Lite and CUDA
variants are in a collapsible details block so the quick start
section stays scannable.
onnxruntime-gpu reports CUDAExecutionProvider as "available" just
because the library was compiled with CUDA support, even on machines
with no GPU. This made gpu_available() return True incorrectly,
causing upscale.py to try torch.device("cuda") and fall back to
Lanczos instead of running Real-ESRGAN on CPU.
torch.cuda.is_available() actually probes the hardware. Use it as
the single source of truth for GPU detection.
Verified: CUDA image on Apple Silicon (no GPU) now correctly reports
gpu: false and all AI tools run on CPU without crashes.
The STIRLING_GPU=true env var was baked into the :cuda Dockerfile,
which made gpu_available() return True without checking actual
hardware. On machines without a GPU, this would crash upscale.py
(torch.device("cuda") fails) and ocr.py (PaddleOCR use_gpu=True).
Fix: the env var can only disable GPU (set to false/0), never
force-enable it. Hardware detection always runs. Removed the
baked env var from the Dockerfile since it adds no value now.
semantic-release-bot