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-0.1.19.tar.gz
(27.3 kB
view details)
Built Distribution
File details
Details for the file vpredicto-0.1.19.tar.gz
.
File metadata
- Download URL: vpredicto-0.1.19.tar.gz
- Upload date:
- Size: 27.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | faacf7ed0bd2f7696aed0cbdf9d845e9816f57247414a2530650a08c9e689f6c |
|
MD5 | 8a204fcc8d9d6a4072e9dc0369423fa5 |
|
BLAKE2b-256 | 8f54afca2d249da231986b2a0844fe5ff37c890619dd8a174a28dcd38074d69b |
File details
Details for the file vpredicto-0.1.19-py3-none-any.whl
.
File metadata
- Download URL: vpredicto-0.1.19-py3-none-any.whl
- Upload date:
- Size: 46.2 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 | f92b6b612dce9cd80a9f0ff90af8a17ac7e3b3bbb000ba0a610c11f4fe8c91f3 |
|
MD5 | f1cf2aefca051c009b8485777d457aae |
|
BLAKE2b-256 | 5b2ff77790a67705375d947d2ece8cf9fd50ea8570ecb29b0890a9fa73411483 |