pyiqa.data
==========

.. py:module:: pyiqa.data


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/pyiqa/data/ava_dataset/index
   /autoapi/pyiqa/data/bapps_dataset/index
   /autoapi/pyiqa/data/base_iqa_dataset/index
   /autoapi/pyiqa/data/data_sampler/index
   /autoapi/pyiqa/data/data_util/index
   /autoapi/pyiqa/data/dataset_api/index
   /autoapi/pyiqa/data/general_fr_dataset/index
   /autoapi/pyiqa/data/general_nr_dataset/index
   /autoapi/pyiqa/data/livechallenge_dataset/index
   /autoapi/pyiqa/data/multiscale_trans_util/index
   /autoapi/pyiqa/data/pieapp_dataset/index
   /autoapi/pyiqa/data/piq_dataset/index
   /autoapi/pyiqa/data/prefetch_dataloader/index
   /autoapi/pyiqa/data/transforms/index




Package Contents
----------------

.. py:function:: build_dataset(dataset_opt)

   Build dataset from options.

   :param dataset_opt: Configuration for dataset. It must contain:
                       name (str): Dataset name.
                       type (str): Dataset type.
   :type dataset_opt: dict


.. py:function:: build_dataloader(dataset, dataset_opt, num_gpu=1, dist=False, sampler=None, seed=None)

   Build dataloader.

   :param dataset: Dataset.
   :type dataset: torch.utils.data.Dataset
   :param dataset_opt: Dataset options. It contains the following keys:
                       phase (str): 'train' or 'val'.
                       num_worker_per_gpu (int): Number of workers for each GPU.
                       batch_size_per_gpu (int): Training batch size for each GPU.
   :type dataset_opt: dict
   :param num_gpu: Number of GPUs. Used only in the train phase.
                   Default: 1.
   :type num_gpu: int
   :param dist: Whether in distributed training. Used only in the train
                phase. Default: False.
   :type dist: bool
   :param sampler: Data sampler. Default: None.
   :type sampler: torch.utils.data.sampler
   :param seed: Seed. Default: None
   :type seed: int | None