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
Release history Release notifications | RSS feed
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)
Built Distribution
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
Algorithm | Hash digest | |
---|---|---|
SHA256 | 27d8cfe6d6951857cd5ba4359c3b19ebe3b9821f03a05b7e24fea9d4f95d748d |
|
MD5 | d32e448c7074572e3cb5ff9cff47fff2 |
|
BLAKE2b-256 | b6a3ffd10b58c7a9a21cf4d1e32d997262755749c1abcf0e1179092e7ae45af8 |
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
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1fa3e6e24f8a330b825e82c18c5b11d9b384d9e3ab40c990241bc231299c75b8 |
|
MD5 | 902e097aea3f4082cc57a848cbf4dece |
|
BLAKE2b-256 | ab0326abecbcb1e65bbee0f66a5ec39a996bb3e7de933d378867a52c6e5e26c4 |