autocommit
|
2a8561b3b6
|
docs(semantic): 📝 Add/update semantic service usage examples and API specifications
Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
|
2026-06-10 03:58:34 -07:00 |
|
Lilith
|
313067c079
|
docs(claude-tooling/claude): 📝 Update package publishing workflow documentation and config files
Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
|
2026-03-08 19:34:19 -07:00 |
|
Lilith
|
ca0f5f33f2
|
docs(services): 📝 Update Imajin service docs with corrected descriptions, added examples, and improved structure for aesthetic, moderator, request-classifier, and semantic services
Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
|
2026-03-02 20:58:44 -08:00 |
|
Lilith
|
3b995d2461
|
docs(architecture): 📝 Update strategic vision, feature roadmap, and positioning in architecture README to reflect revised long-term planning
Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
|
2026-03-02 20:58:44 -08:00 |
|
Lilith
|
1c3a37da53
|
docs(docs): 📝 Implement structured onboarding flow in README.md with clear sections, visual guidance, and improved readability
Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
|
2026-03-02 20:58:44 -08:00 |
|
Lilith
|
478915eec1
|
chore(service): 🔧 Update 38 Python files in service
|
2026-01-17 18:37:24 -08:00 |
|
Lilith
|
75ffff5793
|
chore(services): 🛠 Update imajin-app.md
|
2026-01-17 12:02:23 -08:00 |
|
Lilith
|
a5f99bb3d7
|
chore(imajin): clean up legacy structure and completion markers
- Remove old imajin/ directory (migrated to services/ + orchestrators/)
- Delete completion markers (DONE.md, INTEGRATION-COMPLETE.md, TESTING.md)
- Remove standalone test generation scripts
- Update docs to reflect current architecture
- Add multi-base-strategy.md documentation
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
|
2026-01-16 17:01:10 -08:00 |
|
Lilith
|
e91a922931
|
feat(orchestrators/imajin-pipeline): implement PersonAppearance API and ControlNet integration
Implements high-level PersonAppearance API for controlling person generation
with pose and clothing specifications. Translates simple user requests into
ControlNet configurations automatically.
Core Implementation:
- PersonAppearanceRequest model (pose + clothing control)
- AppearanceToControlNet translator (549 lines)
- Handles pose presets: standing, sitting, walking, running
- Handles custom pose references (base64/URL)
- Handles pose keypoints (advanced users)
- Handles clothing body part mapping
- Lazy-loads preprocessor and segmentation generator
- SegmentationGenerator (400 lines)
- Template-based RGB mask generation (MVP)
- 7 body parts with color mapping
- Three-phase roadmap: template → pose-aware → ML-based
- ControlNetManager (model loading and caching)
- ControlNetPreprocessor (OpenPose preprocessing)
- ImageConditioningStage (pipeline integration)
- Executes between VALIDATE and GENERATE stages
- Translates PersonAppearance → ControlNet
- Priority: Direct ControlNetConfig > PersonAppearanceRequest
- GenerateStage extensions (multi-ControlNet support)
- AnatomyFixStage skip logic (when ControlNet active)
Testing (71 tests, 100% passing):
- test_appearance_translator.py (23 tests)
- test_segmentation_generator.py (35 tests)
- test_controlnet_manager.py (unit tests)
- test_controlnet_preprocessor.py (unit tests)
- test_image_conditioning_stage.py (13 tests)
- test_anatomy_fix_skip_logic.py (9 tests)
- test_person_appearance_api.py (13 integration tests)
- test_controlnet_generation.py (integration tests)
- test_controlnet_backward_compat.py (integration tests)
Documentation (1600 lines):
- docs/person-appearance-api.md (1000 lines)
- Complete API reference
- Quick start with progressive examples
- Pose control, clothing control, use cases
- Python/cURL/TypeScript integration patterns
- Performance and troubleshooting
- docs/segmentation_masks.md (600 lines)
- Body part mapping and RGB colors
- Template vs pose-aware vs ML strategies
Examples:
- Preset pose examples
- Custom pose examples
- Clothing specification examples
- Combined pose + clothing examples
Assets:
- Preset pose library (4 synthetic OpenPose skeletons)
- Generation script for preset poses
Files Changed:
- Modified: models.py, context.py, generate.py, anatomy_fix.py, __init__.py
- Created: appearance_translator.py, segmentation_generator.py,
controlnet_manager.py, controlnet_preprocessor.py,
image_conditioning.py
- Tests: 9 new test files (unit + integration)
- Docs: 2 comprehensive guides
- Examples: 5 example scripts
- Assets: 4 preset pose images
MVP Scope: Pose + clothing control
Future Phases: Physical features (ethnicity, hair, eyes) in separate stream
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
|
2026-01-14 07:33:56 -08:00 |
|
Lilith
|
47f47444b8
|
feat(@ml/imajin): ✨ integrate post-processing flow and update documentation
|
2026-01-13 04:18:42 -08:00 |
|
Lilith
|
0cd023f6e2
|
feat(imajin): ✨ add main entry point service and client libraries
|
2026-01-10 05:15:36 -08:00 |
|
Lilith
|
15fc554291
|
feat(imajin): ✨ update documentation and service structure
|
2026-01-10 05:04:48 -08:00 |
|
Lilith
|
57c5e09f31
|
fix(docs): 🐛 update diffusers model IDs and layout presets descriptions
|
2026-01-10 05:03:41 -08:00 |
|
Lilith
|
ca9f501c24
|
chore(imajin): 🔧 🛏️ update package.json and README.md
|
2026-01-10 04:52:11 -08:00 |
|