a
    PSic                     @   sx   d dl Z d dlZd dlmZmZmZmZmZmZ d dl	m
Z
 ddlmZmZ ddlmZ ddlmZ G dd	 d	eZdS )
    N)OptionalCallableTupleDictAnyList)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eee	e	e
e	 e	ee
e e
eeef  e	e	e	e	e	edd fddZeeeef dddZee ee	eee	 dddZe	dddZe	eeee	f d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 (string): 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.rarZ 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$fold should be between 1 and 3, got )avic                 S   s   g | ]\}}|qS  r%   ).0path_r%   r%   W/var/www/html/django/DPS/env/lib/python3.9/site-packages/torchvision/datasets/hmdb51.py
<listcomp>Z       z#HMDB51.__init__.<locals>.<listcomp>)r   r   r   r   r    r!   )super__init__
ValueErrorr
   r   classesr   samplesr   full_video_clipsr   r   _select_foldindicessubsetvideo_clipsr   )selfr   r   r   r   r   r   r   r   r   r   r   r   r   r    r!   
extensionsclass_to_idxZvideo_pathsr5   	__class__r%   r)   r-   <   s<    zHMDB51.__init__)r"   c                 C   s   | j jS N)r1   metadatar6   r%   r%   r)   r<   r   s    zHMDB51.metadata)
video_listannotations_dirr   r   r"   c              	   C   s   |r
| j n| j}d| d}tj||}t|}t }	|D ]d}
t|
}| }W d    n1 sh0    Y  |D ]*}|	 \}}t
|}||krv|	| qvq>g }t|D ]"\}}tj||	v r|| q|S )Nz*test_splitz.txt)	TRAIN_TAGTEST_TAGosr'   joinglobsetopen	readlinessplitintadd	enumeratebasenameappend)r6   r>   r?   r   r   Z
target_tagZsplit_pattern_nameZsplit_pattern_pathZannotation_pathsZselected_filesfilepathfidlineslineZvideo_filenameZ
tag_stringtagr3   Zvideo_indexZ
video_pathr%   r%   r)   r2   v   s$    

&zHMDB51._select_foldc                 C   s
   | j  S r;   )r5   Z	num_clipsr=   r%   r%   r)   __len__   s    zHMDB51.__len__)idxr"   c                 C   sJ   | j |\}}}}| j| }| j| \}}| jd ur@| |}|||fS r;   )r5   Zget_clipr3   r0   r   )r6   rT   videoaudior(   Z	video_idxZsample_indexclass_indexr%   r%   r)   __getitem__   s    


zHMDB51.__getitem__)r	   Nr	   TNNr	   r   r   r   r   r   )__name__
__module____qualname____doc__Zdata_urlsplitsr@   rA   strrI   r   boolr   r   r   r-   propertyr<   r   r2   rS   r   r   rX   __classcell__r%   r%   r9   r)   r      sT   '            6r   )rD   rB   typingr   r   r   r   r   r   torchr   folderr
   r   Zvideo_utilsr   visionr   r   r%   r%   r%   r)   <module>   s    