Metadata-Version: 2.1
Name: minerl-navigate
Version: 1.1.0
Summary: minerl-navigate - MineRL Navigate Video Dataset
Home-page: https://github.com/vaibhavsaxena11/minerl_navigate
Author: Vaibhav Saxena
Author-email: saxena.vaibhav96@gmail.com
License: Attribution-NonCommercial-ShareAlike 4.0 International
Description: # MineRL Navigate Video Dataset
        
        [![PyPI](https://img.shields.io/pypi/v/minerl_navigate.svg)](https://pypi.python.org/pypi/minerl-navigate/#history)
        
        A dataset for long-term video prediction. It shows human players traversing
        worlds of the video game Minecraft, which include forests, mountains, oceans,
        and islands. The dataset contains 961 train videos and 255 test videos. Each
        video contains 500 images of size 64x64x3.
        
        <img src="https://github.com/vaibhavsaxena11/minerl_navigate/raw/main/preview.gif" width="100%"/>
        
        ## Citation
        
        The dataset was originally crowd-sourced by Guss et al. and preprocessed for
        video prediction by Saxena et al. If you use this dataset, please reference:
        
        ```
        @article{saxena2021clockworkvae,
          title={Clockwork Variational Autoencoders},
          author={Saxena, Vaibhav and Ba, Jimmy and Hafner, Danijar},
          journal={arXiv preprint arXiv:2102.09532},
          year={2021},
        }
        ```
        
        ```
        @article{guss2019minerl,
          title={Mine{RL}: A Large-Scale Dataset of {M}inecraft Demonstrations},
          author={William H. Guss and Houghton, Brandon and Topin, Nicholay and Wang, Phillip and Codel, Cayden and Veloso, Manuela and Salakhutdinov, Ruslan},
          journal={International Joint Conference on Artificial Intelligence},
          year={2019},
        }
        ```
        
        ## Instructions
        
        Installation:
        
        ```sh
        pip3 install minerl-navigate
        ```
        
        Usage example:
        
        ```python
        import tensorflow as tf
        import tensorflow_datasets as tfds
        import minerl_navigate
        
        dataset = tfds.load('minerl_navigate', shuffle_files=True)
        
        test = dataset['test']
        
        train = dataset['train'].repeat()
        train = train.flat_map(lambda x: tf.data.Dataset.from_tensor_slices(
            tf.reshape(x['video'], (5, 100, 64, 64, 3))))
        train = train.shuffle(5000).batch(50).prefetch(1)
        
        for batch in train:
          assert batch.shape == (50, 100, 64, 64, 3)
          assert batch.dtype == tf.uint8
          break
        ```
        
        ## Creation
        
        The video dataset was created by combining the *Navigate* and *Navigate
        Extreme* tasks, splitting them into non-overlapping sequences of length 500,
        splitting them into train and test sets, and storing the videos as MP4 files.
        Optionally, the action sequences are available in JSON format. Instead of using
        the data loader, the data can also be [downloaded][download] manually.
        
        [download]: https://archive.org/details/minerl_navigate
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
