- Pin PaddlePaddle to 3.0.0 on ARM64 to fix segfault in PIR inference
engine (3.1+ crashes on aarch64 Debian Bookworm)
- Fix text extraction for PaddleOCR 3.4.x result format (rec_texts)
- Add Node.js-level fallback chain (best -> balanced -> fast) when
Python subprocess crashes
- Add multi-image OCR: processes all uploaded files sequentially with
per-file progress and filename headers in combined output
- Convert input images to PNG via Sharp before OCR so HEIC, AVIF, WebP,
TIFF all work transparently
- Implement real auto-detect language using Tesseract multi-lang script
detection (analyzes Unicode ranges for Hangul, CJK, Kana, Latin)
- Default enhance to off (hurts clean digital images)
- Replace Auto/AI/Fast buttons with Fast/Balanced/Best (consistent with other tools)
- Rename "Denoise" to "Noise Reduction" with explanatory subtitle
- Change output format from 3 buttons to dropdown with all formats (PNG, JPG, WebP, AVIF, TIFF, GIF, HEIC, HEIF)
- Add HEIC/HEIF input decoding (was missing unlike other tools)
- Add HEIC/HEIF/AVIF output conversion via Sharp and heif-enc
- Generate browser-compatible WebP preview for non-previewable output formats
- Fix torchvision compatibility shim so Real-ESRGAN actually loads (was silently falling back to Lanczos)
- Fix denoise crash: Image.fromarray() instead of type(img).fromarray()
- Redirect stdout for entire AI pipeline to prevent library messages corrupting JSON output
- Add GFPGAN model download for face enhancement
- Use batch endpoint for multi-file uploads (enables Download All ZIP)
- Fix multi-image: process selected file, not always first
- Fix progress bar: asymptotic fill prevents visual stalling
- Fix slider: write results to captured index, not current selection
- Add model selection (Auto/AI/Fast), face enhancement, denoise
- Add output format (PNG/JPEG/WebP) with quality control
- Add Upscale All for sequential batch processing with queue
- More granular Python progress stages for smoother UX
Ultra quality (People only):
- BiRefNet-matting ONNX (928MB) for true alpha matting with per-pixel
transparency on hair wisps and fine edges
- Custom rembg session class, zero new Python dependencies
- Model pre-downloaded in Docker build for immediate availability
Quality tier labels: Fast / HD / Max / Ultra (shorter, fits 4-col grid)
Adds a new "Ultra" quality tier for People subject type that uses
BiRefNet-matting (ONNX, 928MB) for true alpha matting instead of
binary segmentation. Produces per-pixel transparency for hair wisps
and fine edges that standard models miss.
- Custom rembg session class loads BiRefNet-matting ONNX from GitHub releases
- Zero new Python dependencies (reuses existing onnxruntime)
- Model pre-downloaded in Docker build alongside existing models
- Ultra option only visible when subject is People
- Falls back to Best when switching to Products/General
Remove Background:
- Two-phase flow: AI removes bg once, then effects adjust instantly
- Blur background effect with real-time CSS preview (portrait mode)
- Drop shadow effect with opacity control
- Gradient backgrounds with presets, custom colors, and angle
- Custom background image upload (including HEIC/HEIF)
- Solid color backgrounds moved from Python to Node.js/Sharp
- Effects-only API endpoint for instant re-renders without AI re-run
- HEIC/HEIF input support (decoded before passing to Python/rembg)
- Passport/ID photo checkbox defaults ON for People subject
- Before/after slider preserved when no effects active
- 15 comprehensive Playwright e2e tests
Color Tools:
- Consolidated 4 tools (brightness-contrast, saturation, color-channels,
color-effects) into single "Adjust Colors" tool
- Added exposure, temperature, tint, hue, sharpness controls
- SVG filter-based live preview for all adjustments
- Backward-compatible URL redirects from old tool paths
Other fixes:
- Favicon tool: download button instead of auto-download
- Batch processing: HEIC filename extension fix
- File store: processedFilename field for proper batch downloads
- Add bidirectional HEIF support: decode (input) and encode (output) via system heif-convert/heif-enc
- Add server-side WebP preview generation for non-browser-previewable formats (HEIC, TIFF)
- Fix content-aware resize failing on HEIF input (decode before passing to caire)
- Fix content-aware resize timeout on large images by downscaling to max 1200px and using JPEG intermediate
- Add HEIF as target format in convert tool
- Add loading spinner for HEIF preview decode in file store
- Fix file picker not accepting HEIF files (explicit .heic,.heif,.hif extensions)
- Extend frontend timeout for medium tools to 180s with 45s progress animation
- Redesign rotate controls with preset buttons and compact flip section
- Remove misleading savings percentage from convert tool
Replace the Python seam-carving library with caire (esimov/caire v1.5.0),
a Go-based content-aware resize engine that is faster and supports both
shrinking and enlarging via seam insertion.
- Add Go builder stage in Dockerfile to compile caire from source
- Rewrite seam-carving.ts to call caire via execFile (no Python sidecar)
- Remove content-aware-resize from PYTHON_SIDECAR_TOOLS (60s timeout)
- Add new options: blur radius, edge sensitivity, square mode, face detection
- Move content-aware toggle below standard resize in UI (subtler placement)
- Rename "Don't enlarge" to "Limit to original size" with hover tooltip
- Add smooth progress bar for medium-duration tools
- Delete seam_carve.py and remove seam-carving pip dependency
- Update integration tests and visual regression screenshots
- Replace Rule of Thirds button with checkbox for clearer toggle
- Show side-by-side comparison after crop instead of overlay slider
- Add custom aspect ratio option with W:H number inputs
- Fix batch crop failing on files with different dimensions by
sending percentage-based coordinates instead of absolute pixels
- Add failed-file error state display in tool page
* 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>
Centralize duplicated getToken() + Bearer header logic into a single
formatHeaders() helper in lib/api.ts. When no token exists, the
Authorization header is omitted entirely instead of sending an empty
Bearer token, which breaks forward-auth proxies like Authelia behind
Caddy.
Changes:
- Add formatHeaders() with try-catch around localStorage access
- Replace 20+ duplicated getToken() definitions across tool components
- Migrate all call sites including file-details, settings, change-password
- Update tests to verify header omission on empty token
Based on the fix proposed by @jules2689 in #6, with improvements:
file placement (lib/api.ts vs components), localStorage error handling,
simplified truthiness check, and complete call-site coverage.
Co-Authored-By: Julian Nadeau <julian@jnadeau.ca>
Adds a new mode that trims uniform-color borders around the subject,
like GIMP's "Crop to Content." Includes configurable tolerance threshold
and optional pad-to-square with target size for e-commerce workflows.
The original attention-based crop is preserved as "Focus Crop" mode.
Closes#7
Two issues caused intermittent step addition failures in the automation
pipeline:
1. RemoveBgControls had onChange in its useEffect deps. Since onChange is
a new function reference on every parent render, this created an
infinite re-render loop (effect -> setState -> render -> effect).
Fixed by using the onChangeRef pattern matching other settings
components.
2. All step mutation callbacks read from stepsRef.current and passed
values to setSteps. Concurrent callbacks (e.g. addStep + a settings
effect) would overwrite each other. Fixed by switching to functional
state updates (setSteps(prev => ...)) and removing stepsRef.
Also rewrites automate e2e tests to use manual step addition instead of
referencing templates that no longer exist in the UI.
Child component effects (Controls onChange) fire before the parent's
useEffect that synced stepsRef. This caused updateStepSettings to read
stepsRef.current as [] and wipe out newly added steps.
Fix: assign stepsRef.current = steps directly during render so the
ref is always current before any child effects execute.
All step mutation callbacks (addStep, removeStep, moveStep,
updateStepSettings) captured `steps` in their useCallback closures.
When React batched state updates, rapid interactions could use a stale
steps array, causing clicks to silently fail.
Fix: use a stepsRef that always holds the latest value. Callbacks read
from stepsRef.current instead of the captured closure variable, and no
longer need `steps` in their dependency arrays.
When a tool was selected via search, the search text persisted after
the picker closed. Reopening the picker showed a filtered list instead
of all tools, making it look like clicking tools without searching
didn't work.
The settings panel used conditional rendering ({isExpanded && ...})
which unmounted the Controls component on collapse, losing all state.
Switch to CSS hidden class so the component stays mounted and settings
persist when the panel is collapsed and re-expanded.
Extract a *Controls subcomponent from all 16 pipeline-compatible tool
settings components. Each Controls component holds the UI state and
settings controls, accepts an onChange callback, and uses useRef to
prevent infinite re-render loops. The standalone *Settings components
become thin wrappers that add useToolProcessor, useFileStore, and
action buttons.
pipeline-step-settings.tsx is rewritten from ~675 lines to ~55 lines:
the entire TOOL_FIELDS declarative map and generic renderer are deleted
and replaced with direct imports of the Controls components. Pipeline
steps now render the exact same UI as standalone tool pages.
Special cases:
- CropControls: numeric inputs for pipeline (standalone uses canvas)
- RotateControls: resetSignal prop for post-processing reset
- ColorControls: accepts toolId for tab selection
- StripMetadataControls: checkboxes only (no file inspection)
- RemoveBgControls: already extracted, unchanged
Extract the settings controls (subject type, quality, background color)
from RemoveBgSettings into a shared RemoveBgControls component that
accepts settings + onChange props. Both the standalone tool page and the
pipeline step configurator now render the same component, so the UI is
identical and changes only need to be made in one place.
The pipeline step settings had an empty array for remove-background,
showing "No configurable settings" even though the tool supports
model selection and background color. Add AI model selector (u2net,
birefnet-general-lite, birefnet-general, birefnet-portrait, bria-rmbg)
and background color picker matching the standalone tool's options.
Register remove-background, upscale, and blur-faces in the pipeline
tool registry via registerToolProcessFn(). These tools keep their
custom HTTP routes (with progress callbacks) for direct use, but now
also provide a simple process function for pipeline/batch execution.
Add a search bar to the pipeline tool picker so users can quickly
find tools by name or description. Uses the existing SearchBar
component and the same filtering pattern as the main tool panel.
Update tests to reflect that these 3 AI tools are now pipeline-
compatible (moved from excluded to included assertions).
The pipeline tool picker was showing all tools, but only tools
registered via createToolRoute() support pipeline execution. Tools
with custom routes (remove-background, upscale, ocr, etc.) would
silently fail with "Tool not found" and the empty catch block hid
the error from users.
Add GET /api/v1/pipeline/tools endpoint that returns the IDs of
pipeline-compatible tools. The frontend fetches this list and filters
the tool picker accordingly. Also surface pipeline execution errors
in the UI instead of swallowing them.
Remove hardcoded --platform=linux/amd64 from Dockerfile so buildx produces
native arm64 images for Apple Silicon and Raspberry Pi. Add audit logging
for auth events, harden file storage with extension whitelists and
double-extension attack prevention, reject null-byte buffers in validation,
add data-testid attributes to all tool settings components, update
deployment docs with architecture notes and correct CI workflow references,
and fix unit test mock to match throwWithMessage error extraction.
Replace the external mask file upload workflow with an interactive
canvas-based brush tool. Users now paint directly on the image to
mark areas for erasure. Adds EraserCanvas component with adjustable
brush size, undo/clear, and mask export. Switch Python inpainting
from broken lama-cleaner to OpenCV cv2.inpaint (Telea algorithm).
Add before/after comparison slider after processing.
Remove approximate processing times from remove-bg quality options.
Update tool count from 37 to 33 across README, settings dialog, login
page, and i18n strings to reflect the accurate count.
Fix face detection failure caused by MediaPipe 0.10.33 removing the
mp.solutions API. Replace with OpenCV Haar cascade which works reliably
in headless Docker. Add autoOrient() call before detection to handle
EXIF-rotated phone photos. Remove technical jargon from UI.
Fix rotated output by calling autoOrient() before passing images to
the Python upscaler, correcting EXIF orientation metadata. Replace
2x/4x buttons with 2x-8x slider plus quick-select buttons (2x, 3x,
4x, 6x, 8x). Remove technical jargon about Real-ESRGAN/Lanczos from
the UI and progress bar.
Add CSS filter-based live preview for brightness, contrast, saturation,
color effects (grayscale/sepia/invert), and color channels (via SVG
feColorMatrix). The image in the right panel updates instantly as
sliders are adjusted. Adds cssFilter prop to ImageViewer, onPreviewFilter
callback to ColorSettings, and wires them through the tool page.
Add a miniature page preview in the settings panel that shows how the
image will look in the PDF. The preview updates in real-time as the
user changes page size, orientation, or margin. Uses the same scaling
logic as the backend to accurately represent image placement. Preview
tracks the currently selected image when multiple files are uploaded.
Replace the static angle display between Left/Right buttons with an
editable input field that accepts direct angle entry. Add - and +
buttons for 1-degree fine-tuned control. All controls update the
rotation state which triggers real-time CSS preview on the image.
Remove docs/superpowers/, .claude/ config, and PRD.md from version
control (kept locally via .gitignore). Update README, CHANGELOG,
VitePress docs, and .env.example to reflect recent features: Files
page, teams, admin settings, persistent storage, and various API
improvements.
- Add Teams section with CRUD (create, rename, delete) and member count display
- Add Tools section with per-tool enable/disable toggles grouped by category
- Add logo upload/delete, experimental tools toggle, file management settings to System Settings
- Replace free-text team input with dropdown populated from teams API in People section
- Filter disabled/experimental tools in tool panel, pipeline builder, and fullscreen grid
- Display custom logo in mobile header and sidebar when configured
Replace placeholder "default settings" message with actual form controls
when expanding pipeline steps. Each tool now shows its configurable fields
(dimensions, quality, colors, modes, etc.) directly in the pipeline builder.
Covers all 30+ tools with data-driven field definitions: number inputs,
select groups, checkboxes, color pickers, and conditional fields.
- Remove @fastify/swagger and @fastify/swagger-ui (API docs live on GitHub Pages)
- Run typecheck, build, and docker CI jobs in parallel instead of sequentially
react-image-crop's onChange passes (pixelCrop, percentCrop) — we were
using the first arg (display pixels) but treating them as percentages,
causing values to exceed image dimensions.
Siddharth Kumar Sah