Skip to main content

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vpredicto-0.1.12.tar.gz (15.7 kB view details)

Uploaded Source

Built Distribution

vpredicto-0.1.12-py3-none-any.whl (23.1 kB view details)

Uploaded Python 3

File details

Details for the file vpredicto-0.1.12.tar.gz.

File metadata

  • Download URL: vpredicto-0.1.12.tar.gz
  • Upload date:
  • Size: 15.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for vpredicto-0.1.12.tar.gz
Algorithm Hash digest
SHA256 27d8cfe6d6951857cd5ba4359c3b19ebe3b9821f03a05b7e24fea9d4f95d748d
MD5 d32e448c7074572e3cb5ff9cff47fff2
BLAKE2b-256 b6a3ffd10b58c7a9a21cf4d1e32d997262755749c1abcf0e1179092e7ae45af8

See more details on using hashes here.

File details

Details for the file vpredicto-0.1.12-py3-none-any.whl.

File metadata

  • Download URL: vpredicto-0.1.12-py3-none-any.whl
  • Upload date:
  • Size: 23.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for vpredicto-0.1.12-py3-none-any.whl
Algorithm Hash digest
SHA256 1fa3e6e24f8a330b825e82c18c5b11d9b384d9e3ab40c990241bc231299c75b8
MD5 902e097aea3f4082cc57a848cbf4dece
BLAKE2b-256 ab0326abecbcb1e65bbee0f66a5ec39a996bb3e7de933d378867a52c6e5e26c4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page