FACET is an open source library for human-explainable AI. It combines sophisticated model inspection and model-based simulation to enable better explanations of your supervised machine learning models.
Live real-time avatars from your webcam in the browser. No dedicated hardware or software installation needed. A pure Google Colab wrapper for live First-order-motion-model, aka Avatarify in the browser. And other Colabs providing
Official PyTorch implementation of the ICLR 2021 paper "You Only Need Adversarial Supervision for Semantic Image Synthesis". The code allows the users to reproduce and extend the results reported in the study.
Shapash is a Python library which aims to make machine learning interpretable and understandable by everyone. It provides several types of visualization that display explicit labels that everyone can understand.
Fashionpedia is a new dataset which consists of two parts: (1) an ontology built by fashion experts containing 27 main apparel categories, 19 apparel parts, 294 fine-grained attributes and their relationships; (2) a dataset with e
UltraOpt is a simple and efficient library to minimize expensive and noisy black-box functions, it can be used in many fields, such as HyperParameter Optimization(HPO) and Automatic Machine Learning(AutoML).
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly o