Corrupt image data now returns 400 (invalid image) instead of 422
(processing failure) because validation catches it earlier.
Long usernames now return 400 (Zod max length) instead of 401.
The X-File-Results header contained raw JSON with non-ASCII characters
from filenames (Chinese, Japanese, etc.), violating RFC 7230. Node.js
threw ERR_INVALID_CHAR on writeHead(). Fixed by wrapping the JSON in
encodeURIComponent() on the backend and decodeURIComponent() on the
frontend, ensuring only ASCII goes into the header while preserving
the original filenames after decoding.
Closes#133
Users can no longer customize the app name or logo. The branding API
endpoints, permission, frontend UI, env vars (APP_NAME, MAX_LOGO_SIZE_KB),
and all related tests are removed. Includes a migration to clean up
branding data from existing databases.
- Fix resize 20% failure rate: add Zod refine requiring at least one
dimension, enforce integer/max constraints, clamp percentage scaling
to minimum 1px, and guard against missing metadata in withoutEnlargement
- Fix PostHog init race condition: move consent check before async import
so frontend events (search, pageview) are no longer silently dropped
- Fix identify() passing nested $set/$set_once wrappers instead of flat
properties, so version person property now appears on PostHog profiles
- Add error_code and error_message to failed tool_used analytics events
for debugging tool failures from PostHog
- Add Cloudflare Pages deployment for landing page (snapotter.com) and
docs (docs.snapotter.com)
- Create deploy-landing.yml and update deploy-docs.yml workflows
- Update CI to ignore apps/landing/** paths
- Fix logo transparency (remove white background) across all apps
- Recreate social-preview.png with SnapOtter branding
- Update all docs URLs from GitHub Pages to docs.snapotter.com
- Update VitePress config: light theme default, fix llms.txt paths
- Add .vitepress/cache/ and .env.* to gitignore
Pipeline step limit tests now expect success (200/201) since
MAX_PIPELINE_STEPS defaults to 0 (unlimited). Adversarial resize test
reduced from 65536 to 10000 width to prevent Sharp from attempting a
3.2B pixel allocation that times out on CI.
- Pin torch==2.6.0+cu126 and torchvision==0.21.0+cu126 in feature
manifest to prevent NCCL symbol mismatch on CUDA 12.6 base images
- Move lpips after torch in install order to prevent wrong version
resolution from PyPI
- Add einops to upscale-enhance common deps (required by SCUNet)
- Update cpu_fallback_packages to handle multi-package CUDA torch
entries on amd64 without GPU
- Fix gpu.py ONNX CUDA detection: replace hardcoded .so path with
cross-platform session smoke-test
- Fix os.dup(1) crashes on Windows in upscale, enhance_faces, and
noise_removal by wrapping in try/except with sys.stderr fallback
- Guard top-level numpy/cv2 imports in colorize.py and restore.py
with helpful error messages
- Add weights_only=False fallback for torch.load in noise_removal
- Fix integration tests to accept 501 for uninstalled AI features
and 422 for missing system tools (exiftool, libheif)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.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.
---------
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>
Replace the confusing 2-mode smart crop with a clear 3-mode system:
- Subject Focus: Sharp attention/entropy saliency crop with social media presets
- Face Focus: MediaPipe face detection with headshot framing presets
- Auto Trim: Border removal with optional pad-to-square
Adds detectFaces() to AI package, face preset constants, backward
compatibility for old mode names, and comprehensive integration tests.
* 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>
- Health endpoint returns "healthy" instead of "ok" for consistency
- MAX_USERS now configurable via env var (default 5)
- People API returns team names instead of UUIDs in register/list
- PUT user update accepts team names (name-first lookup, fallback to ID)
- Login rate limit follows global rate limit when RATE_LIMIT_PER_MIN > 1000
- Strip-metadata preserves original format encoding instead of always PNG
- Fix e2e tests: rotate/crop/border button selectors match actual UI
- Fix e2e tests: create Engineering/Design teams in people test setup
- Fix e2e tests: people UI uses select for team field, not text input
- Update visual regression baseline for tablet home page
Remove DB probe from public health endpoint - it only needs to confirm
the process is alive. Add test for non-admin user getting 403 on admin
health endpoint.
Public GET /api/v1/health now returns only status and version.
Full diagnostics (uptime, storage, database, queue) moved to
GET /api/v1/admin/health which requires admin authentication.
Validation now runs on all entries before any database writes.
Previously, clean entries could be written before a later malicious
entry triggered a 400 response.
PUT /api/v1/settings now returns 400 if any key or value contains HTML
tags. Settings are configuration values - there is no legitimate use
case for HTML in them.
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).
Add 8 tests that would have caught the pipeline bug where custom-route
tools (remove-background, upscale, ocr, etc.) were shown in the
pipeline picker but failed silently when executed.
New tests:
- GET /api/v1/pipeline/tools returns factory-registered tool IDs
- Verify resize, crop, convert, compress, rotate are included
- Verify remove-background, upscale, ocr, blur-faces, erase-object,
info, collage, compare are excluded
- Pipeline execution returns 400 for each custom-route tool
Extract EXIF auto-orientation logic into a shared auto-orient module
used by both single-tool and batch routes. This ensures camera photos
display correctly after processing regardless of entry point.
Also expands e2e and integration tests significantly.
SnapOtter