evalify 0.1.0

Evaluate your face verification models literally in seconds.

evalify

Evaluate your face verification models literally in seconds.

Installation

Stable release

pip install evalify

Bleeding edge

• From source

  pip install git+https://github.com/ma7555/evalify.git
  

• From TestPyPI

  pip install --index-url https://test.pypi.org/simple/evalify
  

Usage

import numpy as np
from evalify import Experiment

rng = np.random.default_rng()
nphotos = 500
emb_size = 32
nclasses = 10
X = rng.random((self.nphotos, self.emb_size))
y = rng.integers(self.nclasses, size=self.nphotos)

experiment = Experiment()
experiment.run(X, y)
experiment.get_roc_auc()
print(experiment.df.roc_auc)

Documentation:

• https://ma7555.github.io/evalify/

Features

• Blazing fast implementation for metrics calculation through optimized einstein sum.
• Many operations are dispatched to canonical BLAS, cuBLAS, or other specialized routines.
• Smart sampling options using direct indexing from pre-calculated arrays.
• Supports common evaluation metrics like cosine similarity, euclidean distance and l2 normalized euclidean distance.

Contribution

• Contributions are welcomed, and they are greatly appreciated! Every little bit helps, and credit will always be given.
• Please check CONTRIBUTING.md for guidelines.

Citation

• If you use this software, please cite it using the metadata from CITATION.cff