https://github.com/elcuervo/ph

https://github.com/elcuervo/ph

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/elcuervo/ph
• Owner: elcuervo
• License: mit
• Created: 2021-04-02T23:13:26.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2021-05-28T15:29:10.000Z (over 3 years ago)
• Last Synced: 2024-11-28T23:28:28.361Z (about 2 months ago)
• Language: Ruby
• Size: 141 KB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PH

_Perceptual Hashing_

## What is it?

Perceptual hashing is the technique to generate a fingerprint of an image.

- https://en.wikipedia.org/wiki/Perceptual_hashing

- http://hackerfactor.com/blog/index.php%3F/archives/432-Looks-Like-It.html

## Install

```bash

gem install ph

```

## Usage

`PH` Generates a perceptual hash from an array of pixels.

The way you get that pixel data is up to you. Different techniques can shield different values.

Hashes exist on a similar space but different reads could yield different (subtle) hashes.

### Vips

```ruby

size = 64

img = Vips::Image.new_from_file(file)

width, height = img.width, img.height

w_scale, v_scale = size.fdiv(width), size.fdiv(height)

img = img

  .resize(w_scale, vscale: v_scale)

  .colourspace(:grey16)

pixels_2d = img.to_a.map(&:flatten)

PH.hash(pixels_2d)

# => "859091ce633aaebb"

```

### RMagick

```ruby

img = Magick::ImageList.new(file)

size = 64

img = img

  .scale(size, size)

  .dispatch(0, 0, size, size, "I")

  .each_slice(size)

  .to_a

PH.new(img).vector

# => [1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1]

```

### Distance

Since hashes exist on a metric space you can measure how far a hash is from another.

You can use the [hamming gem](https://github.com/elcuervo/hamming) for calculations if needed

```ruby

Hamming.distance(hash_a, hash_b)

# You can also transform hashes based on your storage:

Hamming.vector_to_hash(hash)

Hamming.hash_to_vector(vector)

```