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    ^i@                     @   s|   d dl Z d dlZd dlmZ d dlmZmZmZmZ d dl	m
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 ddlmZmZ ddlmZ ddlmZ G d	d
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eZdS )    N)Path)AnyCallableOptionalUnion)Tensor   )find_classesmake_dataset)
VideoClips)VisionDatasetc                !       s  e Zd ZdZdZdddZdZdZ									
	
	
	
	d)dee	e
f de	dededee dededee deee	ef  dededededede	ddf  fddZedee	ef fddZd ee	 d!e	dededee f
d"d#Zdefd$d%Zd&edeeeef fd'd(Z  ZS )*HMDB51a  
    `HMDB51 <https://serre-lab.clps.brown.edu/resource/hmdb-a-large-human-motion-database/>`_
    dataset.

    HMDB51 is an action recognition video dataset.
    This dataset consider every video as a collection of video clips of fixed size, specified
    by ``frames_per_clip``, where the step in frames between each clip is given by
    ``step_between_clips``.

    To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5``
    and ``step_between_clips=5``, the dataset size will be (2 + 3) = 5, where the first two
    elements will come from video 1, and the next three elements from video 2.
    Note that we drop clips which do not have exactly ``frames_per_clip`` elements, so not all
    frames in a video might be present.

    Internally, it uses a VideoClips object to handle clip creation.

    Args:
        root (str or ``pathlib.Path``): Root directory of the HMDB51 Dataset.
        annotation_path (str): Path to the folder containing the split files.
        frames_per_clip (int): Number of frames in a clip.
        step_between_clips (int): Number of frames between each clip.
        fold (int, optional): Which fold to use. Should be between 1 and 3.
        train (bool, optional): If ``True``, creates a dataset from the train split,
            otherwise from the ``test`` split.
        transform (callable, optional): A function/transform that takes in a TxHxWxC video
            and returns a transformed version.
        output_format (str, optional): The format of the output video tensors (before transforms).
            Can be either "THWC" (default) or "TCHW".

    Returns:
        tuple: A 3-tuple with the following entries:

            - video (Tensor[T, H, W, C] or Tensor[T, C, H, W]): The `T` video frames
            - audio(Tensor[K, L]): the audio frames, where `K` is the number of channels
              and `L` is the number of points
            - label (int): class of the video clip
    zJhttps://serre-lab.clps.brown.edu/wp-content/uploads/2013/10/hmdb51_org.rarzQhttps://serre-lab.clps.brown.edu/wp-content/uploads/2013/10/test_train_splits.rar 15e67781e70dcfbdce2d7dbb9b3344b5)urlmd5r      NTr   THWCrootannotation_pathframes_per_clipstep_between_clips
frame_ratefoldtrain	transform_precomputed_metadatanum_workers_video_width_video_height_video_min_dimension_audio_samplesoutput_formatreturnc                    s   t  | |dvrtd| d}t| j\| _}t| j||| _dd | jD }t|||||	|
|||||d}|| _	|| _
|| _| ||||| _|| j| _|| _d S )N)r   r      z$fold should be between 1 and 3, got )avic                 S   s   g | ]\}}|qS  r%   ).0path_r%   r%   V/var/www/html/RAG/RAG_venv/lib/python3.10/site-packages/torchvision/datasets/hmdb51.py
<listcomp>[   s    z#HMDB51.__init__.<locals>.<listcomp>)r   r   r   r   r    r!   )super__init__
ValueErrorr	   r   classesr
   samplesr   full_video_clipsr   r   _select_foldindicessubsetvideo_clipsr   )selfr   r   r   r   r   r   r   r   r   r   r   r   r   r    r!   
extensionsclass_to_idxvideo_pathsr4   	__class__r%   r)   r,   =   s<   
zHMDB51.__init__c                 C   s   | j jS N)r0   metadatar5   r%   r%   r)   r<   s   s   zHMDB51.metadata
video_listannotations_dirc              	   C   s   |r| j n| j}d| d}tj||}t|}t }	|D ]2}
t|
}| }W d    n1 s4w   Y  |D ]}|	 \}}t
|}||krP|	| q;qg }t|D ]\}}tj||	v ri|| qX|S )Nz*test_splitz.txt)	TRAIN_TAGTEST_TAGosr'   joinglobsetopen	readlinessplitintadd	enumeratebasenameappend)r5   r>   r?   r   r   
target_tagsplit_pattern_namesplit_pattern_pathannotation_pathsselected_filesfilepathfidlineslinevideo_filename
tag_stringtagr2   video_index
video_pathr%   r%   r)   r1   w   s,   




zHMDB51._select_foldc                 C   s
   | j  S r;   )r4   	num_clipsr=   r%   r%   r)   __len__   s   
zHMDB51.__len__idxc                 C   sJ   | j |\}}}}| j| }| j| \}}| jd ur | |}|||fS r;   )r4   get_clipr2   r/   r   )r5   r^   videoaudior(   	video_idxsample_indexclass_indexr%   r%   r)   __getitem__   s   



zHMDB51.__getitem__)r   Nr   TNNr   r   r   r   r   r   )__name__
__module____qualname____doc__data_urlsplitsr@   rA   r   strr   rI   r   boolr   dictr   r,   propertyr<   listr1   r]   tupler   re   __classcell__r%   r%   r9   r)   r      st    '
	
6&$r   )rD   rB   pathlibr   typingr   r   r   r   torchr   folderr	   r
   video_utilsr   visionr   r   r%   r%   r%   r)   <module>   s    