3fec052c12
Organized the application into separate frontend and backend directories for cleaner deployment and better separation of concerns. Frontend Directory (frontend/): - index.html: Single-page web interface (renamed from web_ui.html) - README.md: Frontend deployment guide - Total size: ~113 KB (self-contained) - Smart base path detection (works at / or /ai_qc/) - No configuration changes required Backend Directory (backend/): - All Python files (api_server.py, llm_config.py, etc.) - visual_qc_apps/: 33 QC check modules - profiles/: 6 QC profile configurations - brand_guidelines/: Reference asset storage - config/: Environment configurations - scripts/: Deployment automation - uploads/, output/: Data directories - requirements.txt, ai_qc.service, apache_config.conf - Complete documentation New Documentation: - FOLDER_STRUCTURE.md: Comprehensive guide to new structure - frontend/README.md: Frontend deployment instructions - backend/BACKEND_README.md: Backend deployment guide Deployment Mapping: - frontend/ → /var/www/html/ai_qc/ (web root) - backend/ → /opt/ai_qc/ (application directory) Benefits: - Clear separation of concerns - Backend code not in web-accessible directory - Independent frontend/backend updates - Matches server's existing patterns (/opt/veo3, /opt/voice2text) - Industry-standard architecture - Easy to deploy and maintain Original files preserved in root directory for reference. Ready for production deployment following MIGRATION_GUIDE.md. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
39 lines
2.1 KiB
Python
Executable file
39 lines
2.1 KiB
Python
Executable file
import os
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import sys
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# Add parent directory to path to import shared modules
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from visual_qc_apps.flask_app_template import FlaskAppTemplate
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class LogoVisibilityApp(FlaskAppTemplate):
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"""
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Logo Visibility Check
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"""
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def __init__(self):
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# Define the hardcoded prompt
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prompt = """You are performing a visual quality‐control check on a Point of Sale (POS) advertisement. Your task is to determine whether the brand's logo meets these criteria, based on its intended display size:
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IMPORTANT: This check requires a reference asset (brand guideline document or image) to properly evaluate brand-specific logo requirements including size, placement, and visibility standards. The reference asset will provide the brand's official logo guidelines and standards.
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• For large media (Floor‐Standing Display Units, posters, etc.): The brand logo must be instantly recognizable from about 3 meters away.
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• For smaller media (wobblers, shelf talkers, etc.): The brand must be clearly identifiable from about 1 meter away.
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STEPS TO EVALUATE:
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1. IMPORTANT - If the logo occupies a total area coverage percentage below 8%, it should be considered an automatic FAIL.
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2. Examine the advertisement's overall layout. Check whether the logo is large enough and has sufficient contrast to be immediately noticeable from minimum 3 meters.
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3. Imagine viewing the design at a reduced size or with a slight blur—small details fade out first. Is the logo still quickly recognizable at a glance?
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4. If you can identify the brand right away at the appropriate viewing distance, it passes this checkpoint.
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YOUR OUTPUT:
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Include a JSON code block with two fields:
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- "logo visibility_at_distance": "Pass" or "Fail"
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- "logo_coverage_percentage": (numerical estimate of the fraction of the total ad canvas occupied by the logo)"""
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# Initialize the Flask app with the prompt
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super().__init__(__name__, prompt)
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# Run the app if executed directly
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if __name__ == "__main__":
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app = LogoVisibilityApp()
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app.run(debug=True)
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