latentplot 0.0.1

Description

Python package to plot the latent space of a set of images with different methods.

Install with pip

$ python3 -m pip install latentplot --user

Install from source

$ git clone https://github.com/luiscarlosgph/latentplot.git
$ cd latentplot
$ python3 setup.py install --user

Exemplary code snippet

# List of images of shape (H, W, 3) and BGR
images = [ ... ]           

# List of vectors of shape (D,), where D is the vector dimension
feature_vectors = [ ... ]  

# List of integer class labels
labels = [ ... ]           

# Produce a BGR image containing a 2D plot of the latent space with t-SNE
plotter = latentplot.Plotter(method='tsne')                              
im_tsne = plotter.plot(images, feature_vectors, labels)  # Providing labels here is optional

The latentplot.Plotter constructor parameters are:

• method: method used to reduce the feature vectors to a 2D space. Available options: pca, tsne, umap.
• width: desired output image width. Default is 15360 pixels (16K).
• height: desired output image height. Default is 8640 pixels (16K).
• dpi: DPI for the output image. Default is 300.
• cell_factor: proportion of the reduced space that each cell will occupy. Default is 0.01.
• dark_mode: set it to False to have a white background with black font. Default is True.
• hide_axes: hide axes, ticks and marks. Default is True.
• **kwargs: the rest of the arguments you pass will be forwarded to the dimensionality reduction method.

Exemplary results

• CIFAR-10:

Author

Luis Carlos Garcia Peraza Herrera (luiscarlos.gph@gmail.com), 2023.

License

This code repository is shared under an MIT license.