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-0.1.16.tar.gz
(26.7 kB
view details)
Built Distribution
File details
Details for the file vpredicto-0.1.16.tar.gz
.
File metadata
- Download URL: vpredicto-0.1.16.tar.gz
- Upload date:
- Size: 26.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | eebc0a16899f56f628c669e37553ad3544fc7e6d2362b5fd20481f2aa22263c1 |
|
MD5 | 4f95c00d0c5acf135281af8258b94132 |
|
BLAKE2b-256 | 99c07657f4142df3442ed9f4dbf16ba6ff6a0b242e2a4c2914db1e3c705aeace |
File details
Details for the file vpredicto-0.1.16-py3-none-any.whl
.
File metadata
- Download URL: vpredicto-0.1.16-py3-none-any.whl
- Upload date:
- Size: 45.2 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 | cecda4ed9ff58462cd59cb32f3b9ef18d25420cabf37509f1be4b3568b57828d |
|
MD5 | e2b3bdd560a2cc3fbd5d8e78d4860fb6 |
|
BLAKE2b-256 | ee7d3b2457a96cbbd09dece206532313db4ba30c419b89c0bf246beff8cbd8d1 |