- Video QC: Switch to Google Gemini direct video analysis as default (OpenAI frame grid fallback) - HM QC: Group reports by batch with collapsible sections, ZIP download per batch - HM QC: Generate asset thumbnails (150px) displayed in report listings - Speed: Remove artificial delays, add ThreadPoolExecutor(2) for parallel batch processing - Price detection: Improved prompt with country context, detect all prices, increased text limit - New Printer Check module: CSV-to-PDF cross-referencing ported from CrossMatch Rust app Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
||
|---|---|---|
| core | ||
| database | ||
| deploy | ||
| modules | ||
| static | ||
| templates | ||
| .dockerignore | ||
| .env.example | ||
| .gitignore | ||
| app.py | ||
| auth_middleware.py | ||
| box_client.py | ||
| CHANGELOG.md | ||
| config.py | ||
| DEPLOYMENT_CHECKLIST.md | ||
| docker-compose.yml | ||
| Dockerfile | ||
| DOCUMENTATION_SUMMARY.txt | ||
| gunicorn_config.py | ||
| INTEGRATION_TEST_REPORT.md | ||
| jwt_validator.py | ||
| MIGRATION_GUIDE.md | ||
| README.md | ||
| report_parser.py | ||
| requirements.txt | ||
| run.sh | ||
| run_prod.sh | ||
| setup.sh | ||
| test_integration.py | ||
| test_local.sh | ||
| wsgi.py | ||
Unified HM QC Platform
Version: 2.1.0 Status: Production (Deployed) Deployed at: https://ai-sandbox.oliver.solutions/hm-ai-qc-report
A comprehensive quality control platform for H&M marketing assets with AI-powered validation, video matching, and consolidated reporting.
Overview
The platform integrates six tools into a single web application:
- Reporting - Consolidated QC reports from Box.com with search history
- HM QC - AI-powered image quality control (text legibility, language, quality, pricing)
- Video QC - AI-powered video quality control (frame-by-frame analysis)
- Video Master Adot - Campaign-based master-to-adaptation video matching via Box
- Campaigns - Campaign presentation and media plan management for QC reference
- Usage Dashboard - API usage tracking, token counts, and cost estimates
Key Features
- Unified tabbed interface with H&M branding
- Local username/password authentication
- Multi-provider AI: OpenAI GPT-4o and Google Gemini 2.5 Flash
- Campaign presentation & media plan upload for guideline-based QC validation
- Global pricing reference for currency symbol/format validation per country
- Real-time progress tracking (SSE + polling)
- Docker deployment with Apache reverse proxy
- Usage tracking with estimated costs per API call
Deployment
Docker (Production)
# Clone from Bitbucket
git clone git@bitbucket.org:zlalani/hm_ai_qc_report_tool.git /opt/hm-qc-app
cd /opt/hm-qc-app
# Configure environment
cp .env.example .env
# Edit .env with production values (see .env.example)
# Generate password: python3 deploy/generate_password.py
# Build and start
docker compose build
docker compose up -d
# Create database tables
docker exec hm-qc-app python3 -c "from app import app; from core.models.database import db; app.app_context().push(); db.create_all(); print('Tables created')"
The app runs on 127.0.0.1:5050 inside Docker. Configure Apache or Nginx as reverse proxy — see deploy/ for config snippets.
Common Commands
docker compose logs -f # Tail logs
docker compose restart # Quick restart
docker compose down && docker compose up -d --build # Rebuild after code changes
git pull && docker compose down && docker compose up -d --build # Deploy update
Modules
1. Reporting
Consolidated QC report search from Box.com and local database.
Features:
- Job number search (single or comma-separated for multi-job)
- Async search with real-time progress bar
- Box reports saved locally for instant re-viewing (no re-fetch)
- Previous Box Reports section with View/Delete
- Dashboard with designer-friendly error display
- Export: HTML and CSV (full or errors-only)
Workflow: Search job number -> Progress bar -> Dashboard with aggregated results
2. HM QC
AI-powered image quality control for marketing assets.
Profile: H&M Image Check (3 checks)
- Filename Parse (30%) - Flexibly extracts country code, language, dimensions, campaign number from multiple H&M naming conventions (Display, DOOH, OOH, SOME STATIC, Social, POS)
- Image Quality (40%) - AI visual assessment with strict text legibility rules; validates against campaign presentation guidelines when available
- Price/Currency (30%) - Validates currency symbol/format against global pricing reference; validates actual prices against campaign media plan when available
AI Quality Check evaluates:
- Text & title legibility (CRITICAL - illegible text = automatic fail)
- Language word validation (avoids false positives like "Rock" = German for skirt)
- Campaign guideline compliance (typography, layout, copy, logo placement)
- Image quality, color, composition
- Logo and branding clarity
Features:
- Single and batch file upload (up to 100 files)
- LLM provider choice: OpenAI GPT-4o or Google Gemini 2.5 Flash
- Campaign presentation dropdown to validate against campaign guidelines
- Previous QC Reports with View/Delete and Download
- HTML report generation with per-check scoring
- Usage tracking (tokens + estimated cost)
Workflow: Upload -> Configure (provider + campaign + job number) -> Execute -> Results
3. Video QC
AI-powered video quality control with frame-by-frame analysis.
Checks:
- Visual Quality (50%) - Language consistency + text legibility across all frames
- Censorship (50%) - Body coverage compliance (only for
_CENmarket files, skipped otherwise)
How it works:
- Extracts 1 frame per second from the video
- Stitches frames into a labeled grid image
- Sends grid to AI for analysis (1 API call per check)
- Language check includes false-positive prevention (e.g., "Rock" = skirt in German)
Features:
- LLM provider choice (OpenAI / Google Gemini)
- CEN market auto-detection from filename
- Previous Video QC Reports with View/Delete
- Usage tracking
Workflow: Upload video -> Configure -> Execute (frame extraction + AI) -> Results
4. Video Master Adot
Campaign-based master-to-adaptation video matching using Box.com integration.
How it works:
- User enters campaign name
- System searches Box for campaign folder, finds Global Masters and Regional Masters
- Preview shows: master count, countries, adaptation count
- Phase 1: Downloads each master temporarily, fingerprints it (~50KB), deletes video
- Phase 2: Downloads each adaptation temporarily, matches against fingerprints, deletes video
- Results: per-master adaptation mapping, unmatched items, match rate
Matching Engine (4-tier cascade):
- Stage 0: Metadata filtering (80-95% reduction)
- Tier 1: Perceptual hash matching
- Tier 2: AKAZE feature verification
- Tier 3: AI Vision fallback (smart triggering)
Storage: Only fingerprints (~50KB/master) stored permanently. Videos deleted after processing.
Box Folder Structure:
CAMPAIGNS/{campaign_name}/
├── Global Masters/ (various casing)
│ ├── DOOH/
│ ├── DS/
│ ├── OLV/
│ └── ... (video files with MASTER in name)
└── Regional Masters/ (various casing)
├── DE/ (country code folders)
├── FR/
└── ...
5. Campaigns
Campaign presentation and pricing reference management.
Purpose: Upload campaign-specific documents that QC checks reference when validating assets.
Document Types:
- Campaign Presentation (PDF) - Creative guidelines with typography specs, layout rules, copy text, ratio-specific mockups. Parsed via LlamaParse (text + page images).
- Media Plan / Price Sheet (Excel .xlsx) - Product names, prices, and currency per country/language. Parsed via openpyxl into structured text.
- Global Pricing Reference (PDF) - Single document mapping all countries to currency symbol, position, and format. Parsed once into
storage/reference/global_pricing.json.
Workflow:
- Upload campaign presentation PDF for a campaign (e.g.,
1022B) — leave "has pricing" unchecked - Upload media plan Excel for the same campaign ID — check "Contains campaign-specific pricing"
- Both documents are linked by Campaign ID and loaded together during QC
- On HM QC or Video QC configure page, select the campaign from the dropdown
Features:
- Multiple documents per campaign (guidelines + media plan)
- Auto-polling: status updates in-place when parsing completes
- View parsed content and page images
- Global pricing reference upload (format-only, not actual prices)
- API endpoints for QC modules:
/campaigns/api/list,/campaigns/api/<campaign_id>
6. Usage Dashboard
API usage tracking across all tools.
Displays:
- Summary cards: total API calls, tokens used, estimated cost (USD)
- Breakdowns: by provider, model, tool, user
- Recent API calls table with full details
- Time filters: All Time, 30 Days, 7 Days, Today
Cost estimates based on per-model token pricing (GPT-4o, Gemini 2.5 Flash, etc.)
Configuration
Environment Variables (.env)
# Authentication
AUTH_USERS=admin:pbkdf2:sha256:600000$$salt$$hash
# Session
SESSION_COOKIE_PATH=/hm-ai-qc-report
# Box
BOX_CONFIG_PATH=config/box_config.json
BOX_REPORT_FOLDER_ID=133295752718
BOX_CAMPAIGNS_FOLDER_ID=156182880490
# Flask
SECRET_KEY=<generate-random-key>
FLASK_ENV=production
# Database (use absolute path for Docker)
DATABASE_URI=sqlite:////app/database/qc_platform.db
# LLM Providers
OPENAI_API_KEY=<your-key>
GOOGLE_API_KEY=<your-key>
Note: $$ in AUTH_USERS hash is required for Docker Compose (escapes $).
Architecture
Tech Stack
- Backend: Flask 3.0, SQLAlchemy, Gunicorn
- Frontend: Bootstrap 5, Vanilla JS, Server-Sent Events
- AI: OpenAI GPT-4o, Google Gemini 2.5 Flash (via
google-generativeai) - Video: FFmpeg, OpenCV (AKAZE), Chromaprint
- Storage: Box.com (JWT auth), SQLite
- Deployment: Docker, Apache reverse proxy
Directory Structure
hm_ai_qc_report_tool/
├── app.py # Application factory
├── config.py # Configuration
├── Dockerfile # Docker image
├── docker-compose.yml # Docker services
├── deploy/ # Deployment scripts & configs
│
├── core/ # Shared infrastructure
│ ├── auth/ # Session-based authentication
│ ├── models/ # Database models (QCReport, UsageLog, CampaignPresentation)
│ ├── services/ # LLM config, Box client
│ └── utils/ # Progress tracker, report parser
│
├── modules/
│ ├── hm_qc/ # HM QC (checks, executor, profiles)
│ ├── video_qc/ # Video QC (executor, frame extraction)
│ ├── video_master/ # Video Master (matching engine, campaign matcher)
│ ├── campaigns/ # Campaign presentations & pricing reference
│ ├── reporting/ # Reporting (aggregator, Box search, cache)
│ └── usage/ # Usage dashboard
│
├── templates/ # Shared templates (base.html, login.html)
├── static/ # CSS, JavaScript
├── database/ # SQLite database
└── storage/ # Reports, fingerprints, campaigns, reference
Security
- Local username/password auth with PBKDF2/scrypt hashing
- Session-based with
before_requestlogin enforcement - No hardcoded API keys (all from environment)
- Docker container binds to 127.0.0.1 only (not exposed to internet)
- HTTPS via Apache with wildcard SSL certificate
- httpOnly, Secure, SameSite=Lax cookies
License
Proprietary - H&M Hennes & Mauritz AB