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A library for video frame prediction using PredRNN++, MIM, and Causal LSTM.

Project description

vPredicto

Predicto is a Python library for video frame prediction, featuring three state-of-the-art models: PredRNN++, MIM, and Causal LSTM. This library is designed to cater to both expert and non-expert users, providing an API for developers and a simple interface for non-experts.

Features

  • Three video frame prediction models: PredRNN++, MIM, and Causal LSTM.
  • Easy-to-use interface for training and testing models.
  • Supports custom dataloaders or default to MovingMNIST dataset.
  • Pre and post-processing for input and output in each model.

Installation

pip install vpredicto

Usage

Quick Start

from predicto import PredRNN, MIM, CausalLSTM, Predicto

# Create a model object
model_object = MIM()

# Initialize Predicto with the model object
model = Predicto(model_object)

# Train the model
model.train(train_loader)

# Test the model
model.test(test_loader)

Models

  • PredRNN++: A recurrent neural network model for video frame prediction.
  • MIM: Memory In Memory network for spatiotemporal predictive learning.
  • Causal LSTM: A causal LSTM model for video frame prediction.

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