* feat(shared): add enhance-faces tool definition and i18n strings
* feat(ai): add face enhancement script with GFPGAN and CodeFormer support
Detects faces via MediaPipe dual-model approach, then enhances using
GFPGAN (proven) or CodeFormer (via codeformer-pip) with auto fallback.
Supports strength-based alpha blending with original image.
* feat(ai): add TypeScript bridge for face enhancement
* feat(api): add enhance-faces route with GFPGAN/CodeFormer support
* feat(web): add enhance-faces settings component and register in tool registry
* feat(docker): add CodeFormer dependency and model download
- Add codeformer-pip to both CPU and GPU requirements
- Download CodeFormer model (~375MB) at Docker build time
- Add CodeFormer to smoke test verification
* fix(enhance-faces): address code review findings
- Skip alpha blend for CodeFormer (strength already applied via fidelity weight)
- Hide "only enhance main face" checkbox when Best (CodeFormer) is selected
- Fix sensitivity slider labels (swap More/Fewer faces to match actual behavior)
- Register EnhanceFacesControls in pipeline step settings
- Remove model names from user-facing descriptions
* fix(enhance-faces): fix CodeFormer integration and Docker setup
- Add codeformer-pip install to Dockerfile with --no-deps to avoid numpy 2.x conflict
- Re-pin numpy==1.26.4 after codeformer-pip install
- Pin codeformer-pip==0.0.4 in requirements files
- Broaden auto-mode fallback to catch any Exception from CodeFormer
---------
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
* feat(noise-removal): register tool in shared constants and i18n
* feat(noise-removal): add SCUNet and NAFNet model architectures
* feat(noise-removal): add Python denoising engine with 4 quality tiers
* feat(noise-removal): add TypeScript bridge for Python sidecar
* feat(noise-removal): add frontend settings with 4-tier selector
* feat(noise-removal): register in tool registry and pipeline
* feat(noise-removal): add Fastify API route with Zod validation
* feat(noise-removal): add SCUNet and NAFNet model downloads to Docker build
* test(noise-removal): add to e2e tool page rendering tests
* test(noise-removal): add integration tests for API endpoint
* style: fix biome formatting and import ordering
* fix(noise-removal): use correct model download URLs
NAFNet model is hosted on HuggingFace, not GitHub releases.
Also align SCUNet URL to use the KAIR releases (same as Docker build).
* fix(noise-removal): remove emojis from tier selector, simplify labels
Drop emoji icons from Quick/Balanced/Quality/Maximum buttons. Replace
technical algorithm names with plain descriptions users can understand.
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Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
Add AI-powered photo colorization that converts B&W/grayscale images to
full color using DDColor (ICCV 2023 dual-decoder architecture) via ONNX
Runtime. Includes model selection (Auto/DDColor/Classic), adjustable color
intensity, batch processing, before/after preview, and full HEIC/HEIF support.
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
* feat(image-enhancement): add analysis and correction types
* feat(image-enhancement): implement auto-enhance analysis and correction engine
* test(image-enhancement): add unit tests for auto-enhance engine
* feat(image-enhancement): add API route with analyze endpoint and register in constants/i18n
* feat(image-enhancement): add UI component with mode selector, intensity slider, and analysis badges
* test(image-enhancement): add integration and e2e tests
* fix(image-enhancement): use modulate instead of gamma for exposure correction
Sharp's gamma() only accepts values between 1.0 and 3.0, but brightening
underexposed images computed gamma < 1.0. Switch to modulate({ brightness })
which handles both brightening and darkening correctly.
---------
Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
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
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>
- Backend: look up teams by name first (frontend sends name, not ID)
- Frontend: parse response body on API errors instead of showing
generic "API error: 400" — now shows the actual server message
(e.g. "Password must be at least 8 characters...")
Adds UserFile/UserFileDetail types plus apiListFiles, apiGetFileDetails,
apiUploadUserFiles, apiDeleteUserFiles, getFileThumbnailUrl, and
getFileDownloadUrl to support the Files page.
- Add user management endpoints (register, list, delete, change password)
- Add API key management (create, list, delete)
- Add settings persistence endpoints (get, put)
- Wire settings dialog to real backend (People, API Keys, System, Security)
- Fix login auth flow (window.location.href for full reload)
- Fix download URLs returning 401 (make public since UUIDs are unguessable)
- Fix border tool shadowColor validation (accept 6-8 hex digits)
- Fix remove-bg alpha matting fallback (retry without on failure)
- Fix AI tool silent fallbacks (report errors instead of no-ops)
- Add checkerboard background to before/after slider for transparency
- Add progress bars to all AI tool components
- Add Playwright E2E test suite (131 tests across 9 test files)
- Rewrite Dockerfile for production (tsx runtime, pre-baked AI models)
- Add .dockerignore for faster builds
- Add proper accessible labels to login form
After upload: dropzone replaced by image viewer with zoom controls.
After processing: review panel shows result preview, file info, download,
undo button, and suggested next tools for chaining.
- Register @fastify/multipart plugin with size limits from env config
- Workspace manager: createWorkspace, getWorkspacePath, cleanupWorkspace
- File validation: magic byte detection, format check, megapixel limit
- POST /api/v1/upload: multipart upload with validation, returns jobId + file metadata
- GET /api/v1/download/:jobId/:filename: serve files with Content-Disposition
- Path traversal guards on all file-serving endpoints
- Add @stirling-image/image-engine and sharp as API dependencies
- Add apiUpload, getDownloadUrl, apiDownloadBlob to web client
