image_hashing 0.1.1

A Dart library for generating perceptual hashes (AHash, PHash, DHash, WHash) from images, providing efficient single-image hash computation and comparison.

image_hashing

NOTE: UNDER DEVELOPMENT!

A Dart library for generating perceptual hashes (AHash, PHash, DHash, WHash) from images, providing efficient single-image hash computation and comparison with pure Dart implementation.

Compatibility: Dart ^3.6.0

🚀 Getting Started

Installation

Method 1 (Recommended) With Dart:

dart pub add image_hashing

With Flutter:

flutter pub add image_hashing

Method 2 Add to pubspec.yaml:

dependencies:
  image_hashing: ^0.1.1

Then run:

dart pub get

Basic Usage

import 'package:image_hashing/image_hashing.dart';

void main() {
  final hasher = AHash(); // or other hasher types
  final hashRes = hasher.encodeImage("YourImageFile");
}

Currently only AHash is supported, to validate the whole process.

encodeImage will return you a String of hash value.

For AHash and PHash, it will be 64 bits (After hashing, you will obtain an $(8 \times 8)$ image).

For DHash, it will be 128 bits (Here, I decide to use both row difference and column difference to increase the countability, so you will obtain 2 $(8 \times 8)$ images).

WHash is still under-planning.

📦 Features

• Core Feature 1: Different Hashing Methods

  final ahasher = AHash();
  final phasher = PHash();
  final dhasher = DHash();
  final whasher = WHash(); // Wavelet Transform Hashing dependency is under development
  

  To encode an image:

  final ahasher = AHash(useCV: false); // OpenCV compatibility is under development
  final ahash = ahasher.encodeImage("YourImageFile");
  

• Core Feature 2: Hamming Distances of Image Hashing After hashing, you can use the following function to calculate the Hamming Distances

  final distance = hammingDistance(a, b, size: 64)
  

  where a and b are the hash strings. size is 64 for AHash and PHash, 128 for DHash.

  Result will in an int value.

🧪 Testing

Unit tests are under development. Currently only unit tests for hamming distance

dart test

🤝 Contributing

Workflow

1. Fork repository
2. Create feature branch:

   git checkout -b feat/your-feature
   

3. Follow Conventional Commits:

   git commit -m "feat: add new validation method"
   

Code Style

Follow the Effective Dart and analysis_options.yaml

📚 Documentation

📜 License

BSD 3-Clause "New" or "Revised" License © 2025 RequieMa

Full text at LICENSE

🚧 Maintenance Status

Basic functionalities are under development.

Please report issues via GitHub Issues