setup_folders.py

#!/usr/bin/env python3
"""
Setup and Test Script for Folder-Based Detection

This script helps set up the folder structure and test the 
automatic folder-based damage detection system.

Author: AI Assistant
Date: June 2025
"""

import os
import shutil
from pathlib import Path
import requests
import json

def create_folder_structure():
    """Create the complete folder structure for organized processing."""
    print("🏗️  Creating folder structure...")
    
    base_folders = [
        "input_images", "output_images", "processed_images",
        "reports", "logs", "temp"
    ]
    
    damage_types = [
        "undamaged", "damaged", "tear", "crease", "stain", 
        "fade", "burn", "water_damage", "scratches", "holes", "wrinkles"
    ]
    
    # Create main folders
    for folder in base_folders:
        Path(folder).mkdir(exist_ok=True)
    
    # Create damage type subfolders
    for main_folder in ["input_images", "output_images", "processed_images"]:
        for damage_type in damage_types:
            (Path(main_folder) / damage_type).mkdir(exist_ok=True)
    
    # Create report subfolders
    report_subfolders = ["batch_reports", "individual", "summaries"]
    for subfolder in report_subfolders:
        (Path("reports") / subfolder).mkdir(exist_ok=True)
    
    # Create temp subfolders
    temp_subfolders = ["resized", "cache"]
    for subfolder in temp_subfolders:
        (Path("temp") / subfolder).mkdir(exist_ok=True)
    
    print("✅ Folder structure created successfully!")

def download_sample_images():
    """Download some sample images for testing."""
    print("📥 Downloading sample images...")
    
    # Sample images (Creative Commons/Public Domain)
    sample_images = [
        {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/6/6d/Vintage_poster_art.jpg/512px-Vintage_poster_art.jpg",
            "filename": "vintage_poster_1.jpg",
            "folder": "undamaged"
        },
        {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/a/a9/Old_poster.jpg/512px-Old_poster.jpg", 
            "filename": "old_poster_1.jpg",
            "folder": "damaged"
        }
    ]
    
    for image_info in sample_images:
        try:
            folder_path = Path("input_images") / image_info["folder"]
            file_path = folder_path / image_info["filename"]
            
            if not file_path.exists():
                print(f"  Downloading {image_info['filename']}...")
                response = requests.get(image_info["url"], timeout=30)
                response.raise_for_status()
                
                with open(file_path, 'wb') as f:
                    f.write(response.content)
                
                print(f"  ✅ Saved: {file_path}")
            else:
                print(f"  ⏭️  Already exists: {file_path}")
                
        except Exception as e:
            print(f"  ❌ Failed to download {image_info['filename']}: {e}")
    
    print("📥 Sample image download completed!")

def create_sample_config():
    """Create a sample configuration file."""
    config = {
        "detection_settings": {
            "confidence_threshold": 0.3,
            "device": "auto",
            "batch_size": 1
        },
        "folder_settings": {
            "auto_organize": True,
            "save_annotations": True,
            "backup_processed": True
        },
        "monitoring": {
            "watch_interval": 30,
            "log_level": "INFO",
            "enable_notifications": False
        },
        "output_formats": {
            "save_json_reports": True,
            "save_annotated_images": True,
            "image_annotation_style": "bbox_and_label"
        }
    }
    
    with open("detection_config.json", "w") as f:
        json.dump(config, f, indent=2)
    
    print("⚙️  Created detection_config.json")

def test_folder_detection():
    """Test the folder-based detection system."""
    print("\n🧪 Testing folder-based detection...")
    
    try:
        from pretrained_damage_detector import PretrainedDamageDetector
        
        print("  Initializing detector...")
        detector = PretrainedDamageDetector(device='cpu')  # Use CPU for testing
        
        print("  Scanning input folder...")
        image_files = detector.scan_input_folder()
        
        if image_files:
            print(f"  Found {len(image_files)} images to process")
            
            print("  Running automatic processing...")
            summary = detector.process_folder_automatically(
                auto_organize=True,
                save_annotations=True
            )
            
            print(f"  ✅ Processing completed!")
            print(f"     - Images found: {summary['total_images_found']}")
            print(f"     - Successfully processed: {summary['successfully_processed']}")
            
            if summary['successfully_processed'] > 0:
                print(f"\n📁 Check these folders for results:")
                print(f"   - output_images/ (annotated images)")
                print(f"   - reports/batch_reports/ (analysis reports)")
                print(f"   - logs/ (processing logs)")
        else:
            print("  ⚠️  No images found in input folders")
            print("     Add some images to input_images/ subfolders and try again")
        
    except ImportError:
        print("  ❌ Could not import PretrainedDamageDetector")
        print("     Make sure to install requirements: pip install -r requirements.txt")
    except Exception as e:
        print(f"  ❌ Test failed: {e}")

def show_usage_examples():
    """Show usage examples for the folder-based system."""
    print("\n" + "="*60)
    print("🎯 FOLDER-BASED DETECTION USAGE")
    print("="*60)
    
    examples = [
        {
            "title": "Automatic Processing",
            "command": "python3 pretrained_damage_detector.py --auto-folder",
            "description": "Process all images in input_images/ and organize results"
        },
        {
            "title": "Watch Mode",
            "command": "python3 pretrained_damage_detector.py --watch",
            "description": "Continuously monitor input_images/ for new files"
        },
        {
            "title": "Manual Organization",
            "command": "python3 pretrained_damage_detector.py --auto-folder --no-auto-organize",
            "description": "Process images but don't auto-organize by damage type"
        },
        {
            "title": "Without Annotations",
            "command": "python3 pretrained_damage_detector.py --auto-folder --no-save-annotations",
            "description": "Process images without saving annotated versions"
        }
    ]
    
    for i, example in enumerate(examples, 1):
        print(f"\n{i}. {example['title']}")
        print(f"   Command: {example['command']}")
        print(f"   Description: {example['description']}")
    
    print(f"\n📂 FOLDER STRUCTURE:")
    print("   input_images/        - Place your images here")
    print("   ├── undamaged/       - Clean poster images")
    print("   ├── damaged/         - General damaged images")
    print("   ├── tear/            - Images with tears")
    print("   ├── stain/           - Images with stains")
    print("   └── ... (other damage types)")
    print()
    print("   output_images/       - Annotated results organized by detection")
    print("   processed_images/    - Backup copies")
    print("   reports/             - JSON analysis reports")
    print("   logs/                - Processing logs")

def main():
    """Main setup and test function."""
    print("🎯 FOLDER-BASED DAMAGE DETECTION SETUP")
    print("="*50)
    
    # Create folder structure
    create_folder_structure()
    
    # Download sample images
    download_sample_images()
    
    # Create sample config
    create_sample_config()
    
    # Test the system
    test_folder_detection()
    
    # Show usage examples
    show_usage_examples()
    
    print("\n" + "="*50)
    print("🎉 SETUP COMPLETED!")
    print("="*50)
    print("\n💡 Next Steps:")
    print("1. Add your poster images to input_images/ subfolders")
    print("2. Run: python3 pretrained_damage_detector.py --auto-folder")
    print("3. Check output_images/ for annotated results")
    print("4. Review reports/ for detailed analysis")
    
    print(f"\n📖 For more help, see:")
    print("   - FOLDER_STRUCTURE.md (detailed folder guide)")
    print("   - PRETRAINED_README.md (full documentation)")

if __name__ == "__main__":
    main()