image-comparer 1.1.3

Compares two images using siamese networks

Compares two images using Siamese Network (Machine Learning) trained from a Pytorch Implementation

Installation

To install, run

pip install image-comparer

Usage

CLI

image-compare

which wil show the follow help screen

usage: image-compare [-h] [--threshold THRESHOLD] Image1-Path Image2-Path

For example, you can compare two images with

image-compare tests/images/kobe.jpg tests/images/kobe2.jpg

which gives the result

kobe.jpg and kobe2.jpg are not similar

Programmatically

With PIL

import image_comparer
from PIL import Image

image = Image.open("test/kobe.jpg")
image2 = Image.open("test/kobe2.jpg")
image_comparer.is_similar(image, image2, threshold=0.5)

or with OpenCV

import image_comparer
import cv2

image = cv2.imread("test/kobe.jpg")
image2 = cv2.imread("test/kobe2.jpg")
image_comparer.is_similar(image, image2, threshold=0.5)

API

Methods

is_similar(image1: Union[Image.Image, np.ndarray], image2: Union[Image.Image, np.ndarray], threshold=0.5): Checks if the two images are similar based on the reshold passed

calculate_score(image1: Union[Image.Image, np.ndarray], image2: Union[Image.Image, np.ndarray]): Calculates the score between the two images. The higher the score, the more closely the two images are related.

Development

Installation

pip install -r requirements-test.txt

Tests

To run tests, run

pytest