# Xcedl-Image-Detection

A professional-grade Python library implementing advanced image fingerprinting and similarity detection algorithms, utilizing perceptual hashing techniques and multi-signal verification for robust content analysis and moderation.

## Key Features

- **Enterprise-Level Fingerprinting**: Simulates Discord's compression pipeline for consistent hash generation
- **Multi-Signal Verification**: Combines perceptual hashing, wavelet hashing, difference hashing, and color histogram analysis
- **Production-Ready**: Optimized for high-performance content moderation and duplicate detection
- **Configurable Parameters**: Tunable thresholds for accuracy optimization across different use cases

## Installation

```bash
pip install Xcedl-Image-Detection
```

For development and testing:
```bash
pip install Xcedl-Image-Detection[dev]
```

## Usage

```python
from PIL import Image
from xcedl_image_detection import MilitaryGradeFingerprinter, find_matching_scam

# Generate comprehensive image fingerprint
img = Image.open('target_image.jpg')
fingerprint = MilitaryGradeFingerprinter.generate_nuclear_fingerprint(img)

# Perform database matching against known content
database_entries = load_content_database()  # Your database loading function
match = find_matching_scam(fingerprint, database_entries)

if match:
    print(f"Content match detected: {match['reason']}")
```

## API Reference

### MilitaryGradeFingerprinter

- `nuclear_normalize(img)`: Normalize image through compression simulation pipeline
- `generate_nuclear_fingerprint(img)`: Generate complete multi-dimensional fingerprint

### Core Functions

- `verify_multisignal(test_fp, db_fp)`: Execute multi-signal similarity verification
- `find_matching_scam(test_fp, database)`: Perform optimized database search and matching

## Technical Specifications

- **Dependencies**: Pillow, imagehash, numpy
- **Python Support**: 3.8+
- **License**: MIT
- **Architecture**: Modular design for enterprise integration

## Performance Characteristics

- Optimized for high-throughput content processing
- Memory-efficient fingerprint generation
- Configurable accuracy vs. performance trade-offs
- Comprehensive error handling and logging

## Use Cases

- Content moderation and spam detection
- Duplicate image identification
- Digital asset management
- Copyright infringement detection
- Social media content analysis