Day 30 - March 10, 2026

Today’s Work (2026-03-10)

Summary

High-level: Merged v2 into main, restored and fixed the SvelteKit frontend, added a favicon, fixed an accessibility issue, and updated the backend loader to auto-detect new label columns (C_*, R_*, D_*).
Date / Context: Work performed during Day 30 of Week 26; frontend dev server ran at http://localhost:5173/ and backend Uvicorn started at http://0.0.0.0:8001 during the session.

Key Areas

Branches / Git

Merged v2 → main (merge-base updated; aa2a230 commit from v2 brought dynamic column detection).
Resolved merge conflicts in package.json and related files; working tree clean.

Backend changes

Updated multi_column_loader.py to dynamically detect columns matching the C_*, R_*, D_* patterns (regex-based). New columns like R_10 / R_11 are discovered automatically.

Frontend (SvelteKit) changes

Resolved and updated package.json (upgraded to modern SvelteKit/Vite deps) and fixed svelte.config.js (added adapter import).
Added/created vite.config.ts, src/app.html, src/routes/+layout.svelte, src/routes/+page.svelte.
Added static/favicon.svg and linked it from src/app.html.
Fixed accessibility warning by adding id="hoverImageSizeRange" and for="hoverImageSizeRange" on the hover-size slider label in src/routes/+page.svelte.
Commit message: “Add SVG favicon and fix label accessibility on hover image size slider”.

Install / Dev server

Ran npm install --legacy-peer-deps in the frontend-sveltekit directory and resolved package merge issues.
Started frontend dev server with:

npx vite dev --port 5173

Combined npm run dev previously started backend Uvicorn at http://0.0.0.0:8001 (dataset initialization logs showed datasets loaded).

Files touched (high level)

multi_column_loader.py
package.json, svelte.config.js, vite.config.ts, src/app.html, src/routes/+page.svelte, src/routes/+layout.svelte, static/favicon.svg (+ other generated .svelte-kit files)

Next recommended actions

Restart backend (or call POST /api/initialize) to confirm the new loader detects R_10 / R_11.
Open the app at http://localhost:5173/ and verify: favicon, hover-size slider accessibility, scatterplot drag/tooltip behavior, and available columns dropdown.
Optional: choose one action for me to perform now:
- Restart the backend and show logs
- Open the frontend in a browser and verify UI
- Create PNG/ICO favicon variants

Overview

Today’s work focused on expanding the dataset architecture to include new regional features and formalizing high-priority analytical tasks for model evaluation. The infrastructure for R_10 and R_11 is prepared and the next phase of research (relationship mapping and prediction distributions) is structured.

Dataset Expansion (R_10 & R_11 Integration)

We verified and prepared the integration of two new facial regions into the core pipeline.

Schema Verification: Confirmed that R_10 and R_11 are present in vishal.csv. They are initialized with -0.01 (masked values) so they won’t affect training until labeled.
Legend Mapping: Drafted UI updates for the Legend Gallery to include these regions, designated as Left Temple/Ear and Right Temple/Ear.

Analytical Task Formalization (GitHub Issue)

We converted verbal tasks into a structured GitHub Issue to ensure reproducibility and tracking.

Inter-Region Dependency Study: Created a task to analyze dependencies among $R_1 \dots R_{11}$ to detect redundancy or unique signals.
Prediction Distribution Analysis: Created a task to generate histograms of model outputs to detect bias toward specific severity levels (e.g., many 0s or 3s).

Data Integrity & Pipeline Readiness

Masking Logic: Verified that train.py treats -0.01 values as “ignored”, allowing continued training on R_1 \\dots R_9.
LFS Stability: Confirmed git lfs pull stabilized image serving; the Legend Gallery can render the full 2,864-image set.

Current Project Status

Milestone	Status	Details
Dataset Schema	✅ Updated	`R_10` and `R_11` added to CSV and masking active.
Analysis Roadmap	✅ Documented	GitHub Issue created for Region Dependency & Histograms.
Frontend UI	🛠️ In Progress	Extending Gallery dropdowns to include 11 regions.
Training Flow	✅ Stable	Masked loss function handling new columns correctly.

Recommended Focus for Tomorrow

Region Correlation: Generate a correlation heatmap for $R_1 \dots R_9$ to supply initial data for the GitHub Issue.
Histogram Generation: Build a script to visualize label distributions in vishal.csv to check for imbalance before the next training run.
UI Update: Finalize legend_gallery.py changes so the new R_10 / R_11 tabs are visible in the UI.