Use your images to create collages based on visual similarity, where similar images are located close to each other, like in the example below:
Note: This work was inspired by Andrej Karpathy's visualizations of ImageNet dataset.
Sjaandi is available for installation using pip:
pip install sjaandi
All you need is to have all images for collage in one folder, and use that path as input to VisualSearchEngine():
from sjaandi import VisualSearchEngine
DATA_PATH = # path to the folder with images
collage = VisualSearchEngine(DATA_PATH).make_collage()The collage will be a square, two-dimensional grid of square images. If the number of pictures in your folder is not a square of some number, some photos will not end up in the collage. For example, if you provide 50 images, you will get a 7-by-7 collage having 49 images, which means 1 of the pictures of the 50 will not be included.
Underneath the hood, this library puts your images through a neural network and collects high dimensional activations. The activations are mapped to a two-dimensional Cartesional space using the t-SNE algorithm. The next step is to transform the t-SNE coordinates into a square lattice of coordinates. Finally, your images are laid out at lattice coordinates to produce the final image.
- python 3.6
- fastai
- pytorch
- scikit-learn
- rasterfairy-py3