imagehash VS awesome-python

When an image is uploaded, generate its perceptual hash using an existing library like ImageHash (Python) or pHash (C++). You can find the ImageHash library here: https://github.com/JohannesBuchner/imagehash

My tool is based around the imagehash library which did a great job of weeding out the duplicates at first but has the tendency to report "similar" images. Which happens quite a lot for the 3,000+ landscape images I have :)

If you're using Python there's a good library for perceptual hashing, you'll only have to write a few lines of code: https://github.com/JohannesBuchner/imagehash

About the hashing. There are special image comparison hashing algorithms. These can still "recognize" an image. Even if 1 is a png and another a jpg with a different resolution. An example of that is https://github.com/JohannesBuchner/imagehash.

I am using imagehash to generate image hashes for two groups of images. Group A has 6 images, group B has anywhere from 120 to 600 images.

Python: https://github.com/vinta/awesome-python

6) Awesome Python: Embrace the power of Python with this extensive collection of awesome libraries, frameworks, resources, and software. Whether you're a seasoned Pythonista or just starting your journey, this repository is your ultimate guide to maximizing the potential of this versatile language. (https://github.com/vinta/awesome-python)

- https://github.com/vinta/awesome-python

🎇 Repository Link: Awesome Python

Explore here.

I know of curated lists like https://github.com/vinta/awesome-python but they are nowhere close to alternativeto.net in terms of information (relations) and community involvement.

https://github.com/vinta/awesome-python

There are a lot of python packages for engineering and scientific applications (as well as other applications in general, and, thanks to the inherently collaborative nature of free software, they are only growing in quantity and quality. Many MATLAB toolboxes already have Python equivalents.