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Add support for eye_anime-capable nodes across network, API, and UI. - Treat node_type "eye_anime" like other tracking nodes in CoordinatePublisher so /track/norm messages are sent. - Implement OSCSender.send_eye_animation to send /eye/anime messages, validate and clamp loops (1–20) and include a source field. - Add /api/eye_animation endpoint in app.py to validate target, parse animation_id and loops, call osc.send_eye_animation and return status/metadata. - Update device_registry.json with an eye_anime device entry, name-matching rules, and a descriptor for the node type. - Add UI template/controls for eye_anime: control priority, tracking enable/center, animation trigger (loops input) and client-side sendEyeAnime helper which posts to the new API and refreshes history. Loops are clamped to 1–20 and the API returns an error when no target is selected.
Add a new docs/DATT3700_Collaborative_Project_ZH_EN.md file providing a bilingual (Chinese/English) overview of the DATT3700 collaborative installation. The document covers project overview, hardware layout and team roles, refactored ESP32 firmware and Python host stack, ML/behavior design, display assets (Animated_Eye12), known limitations and roadmap, quick run instructions, and repo paths. Intended to centralize demo/run guidance and design notes for the course deliverable (document version 2026-03-30).
Introduce randomized command selection for the 'kait' node by adding KAIT_COMMAND_POOLS and using random.choice for active emotions; ensure REST always maps to /stop. Import random in emotion_reactor and update _command_for to pick from the pools. Expand tests to cover deterministic randomness (seeding), normalize commands for comparison, assert REST -> /stop, and verify all command variants are observed across seeds.
- Adjusted SERVO_SAFE_MIN_ANGLE and SERVO_SAFE_MAX_ANGLE to broaden the operational range. - Modified PETAL_CLOSED_ANGLE and PETAL_OPEN_ANGLE for improved petal movement dynamics. - Enhanced emotion reactor tests to validate face track mapping and command dispatching for multiple targets. - Implemented logic to suppress emotion commands for actively tracked nodes in the UI to prevent command contention.
…vo control and improved WiFi retry logic - Added configurable state patterns for flower motions (bloom, rest, soothe, alert, breathe). - Enhanced servo control with safety limits and smooth angle transitions. - Implemented reactive modulation based on tracking input for dynamic flower responses. - Refined WiFi and mDNS retry logic for better connectivity reliability. - Improved OSC message routing for state control and diagnostics.
…firmware flashing guide - Deleted bilingual project documentation (DATT3700_Collaborative_Project_ZH_EN.md) and firmware flashing guides (FIRMWARE_FLASH_GUIDE.md and FIRMWARE_FLASH_GUIDE_zh.md) to streamline the documentation repository. - Removed AI instructions and Kait v2 delivery reports to eliminate redundancy and focus on current project resources. - Cleaned up upgrade summary files to maintain clarity in project documentation.
- Introduced a new README.md file detailing the interactive AI flower installation project, including project overview, system architecture, and early interaction concepts. - Enhanced bilingual documentation with links to related resources and project showcases. - Provided insights into the Python control system, face tracking, emotion recognition, and core implementation details for better understanding and accessibility.
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This pull request adds comprehensive English and bilingual (Chinese/English) documentation for the "The Garden's Response" interactive AI flower installation project. The new documents detail the project's architecture, hardware/software integration, emotion AI pipeline, technical challenges, and future roadmap. They provide both a high-level portfolio case study and a course-focused technical overview, supporting both portfolio and course documentation needs.
Major documentation additions:
Portfolio and technical overview:
docs/PORTFOLIO_EN.md, a detailed English portfolio case study covering system architecture, Python/ESP32 integration, emotion AI, dashboard UI, technical challenges, and resume-ready summary for "The Garden's Response" installation.Course and bilingual documentation:
docs/deprecated/DATT3700_Collaborative_Project_ZH_EN.md, a bilingual (Chinese/English) technical document summarizing project concept, hardware/software roles, ML pipeline, limitations, and quick-start instructions for the DATT 3700 course project.