Xcedl-Image-Detection 0.1.1

Advanced image fingerprinting and scam detection library

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

pip install Xcedl-Image-Detection

For development and testing:

pip install Xcedl-Image-Detection[dev]

Usage

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