o V h@sddlZddlZddlZddlZddlZddlmZmZddlmZddl m Z ddl m Z m Z mZmZmZmZddlZddlmZddlmZmZmZdd lmZeejejeejejfZeejejeejfZd Zej edd Z!Gd d d eeZ"Gddde"Z#Gddde"Z$Gddde"Z%Gddde"Z&Gddde"Z'Gddde"Z(Gddde"Z)Gddde"Z*Gddde"Z+Gd d!d!e"Z,dS)"N)ABCabstractmethod)glob)Path)CallablecastListOptionalTupleUnion)Image) _read_pfmdownload_and_extract_archiveverify_str_arg) VisionDataset)slice_channelsc seZdZdZdZddeeefdee ddffdd Z d eeefde j fd d Z dd ed eede eeeeffddZed edeeejeejffddZdedeeeffddZdefddZZS)StereoMatchingDatasetz+Base interface for Stereo matching datasetsFNroot transformsreturncs$tj|d||_g|_g|_dS)a} Args: root(str): Root directory of the dataset. transforms(callable, optional): A function/transform that takes in Tuples of (images, disparities, valid_masks) and returns a transformed version of each of them. images is a Tuple of (``PIL.Image``, ``PIL.Image``) disparities is a Tuple of (``np.ndarray``, ``np.ndarray``) with shape (1, H, W) valid_masks is a Tuple of (``np.ndarray``, ``np.ndarray``) with shape (H, W) In some cases, when a dataset does not provide disparities, the ``disparities`` and ``valid_masks`` can be Tuples containing None values. For training splits generally the datasets provide a minimal guarantee of images: (``PIL.Image``, ``PIL.Image``) disparities: (``np.ndarray``, ``None``) with shape (1, H, W) Optionally, based on the dataset, it can return a ``mask`` as well: valid_masks: (``np.ndarray | None``, ``None``) with shape (H, W) For some test splits, the datasets provides outputs that look like: imgaes: (``PIL.Image``, ``PIL.Image``) disparities: (``None``, ``None``) Optionally, based on the dataset, it can return a ``mask`` as well: valid_masks: (``None``, ``None``) rN)super__init__r_images _disparities)selfrr __class__rY/var/www/vscode/kcb/lib/python3.10/site-packages/torchvision/datasets/_stereo_matching.pyrs zStereoMatchingDataset.__init__ file_pathcCs"t|}|jdkr|d}|S)NRGB)r openmodeconvert)rr!imgrrr _read_img:s   zStereoMatchingDataset._read_imgpaths_left_patternpaths_right_patternc Csttt|}|rttt|}n tdd|D}|s%td||s.td|t|t|krKtdt|dt|d|d|d td dt||D}|S) Ncss|]}dVqdSNr.0_rrr Lz4StereoMatchingDataset._scan_pairs..z0Could not find any files matching the patterns: zFound z left files but z# right files using: left pattern: z right pattern:  css|] \}}||fVqdSr*r)r,leftrightrrr r.[s)listsortedrFileNotFoundErrorlen ValueErrorzip)rr(r) left_paths right_pathspathsrrr _scan_pairs@s$z!StereoMatchingDataset._scan_pairscCsdSr*r)rr!rrr _read_disparity^sz%StereoMatchingDataset._read_disparityindexc Cs||j|d}||j|d}||j|d\}}||j|d\}}||f}||f} ||f} |jdurG||| | \}} } |jsP| ddurb|d|d| dttj| dfS|d|d| dfS)aoReturn example at given index. Args: index(int): The index of the example to retrieve Returns: tuple: A 3 or 4-tuple with ``(img_left, img_right, disparity, Optional[valid_mask])`` where ``valid_mask`` can be a numpy boolean mask of shape (H, W) if the dataset provides a file indicating which disparity pixels are valid. The disparity is a numpy array of shape (1, H, W) and the images are PIL images. ``disparity`` is None for datasets on which for ``split="test"`` the authors did not provide annotations. rr N) r'rr=rr_has_built_in_disparity_maskrnpndarray) rr>img_left img_right dsp_map_leftvalid_mask_left dsp_map_rightvalid_mask_rightimgsdsp_maps valid_masksrrr __getitem__cs    $z!StereoMatchingDataset.__getitem__cCs t|jSr*)r6r)rrrr __len__s zStereoMatchingDataset.__len__r*)__name__ __module__ __qualname____doc__r?r strrr rrr r'rr r<rr@rAr=intT1T2rKrL __classcell__rrrr rs"(  (#rcsneZdZdZddeeefdeeddffdd Z dede e j dffd d Z d edeffd d ZZS) CarlaStereoaz Carla simulator data linked in the `CREStereo github repo `_. The dataset is expected to have the following structure: :: root carla-highres trainingF scene1 img0.png img1.png disp0GT.pfm disp1GT.pfm calib.txt scene2 img0.png img1.png disp0GT.pfm disp1GT.pfm calib.txt ... Args: root (str or ``pathlib.Path``): Root directory where `carla-highres` is located. transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. Nrrrc st||t|d}t|ddd}t|ddd}|||}||_t|ddd}t|ddd}|||}||_dS)Nz carla-highres trainingF*im0.pngim1.png disp0GT.pfmz disp1GT.pfmrrrrQr<rr) rrrleft_image_patternright_image_patternrHleft_disparity_patternright_disparity_pattern disparitiesrrr rs    zCarlaStereo.__init__r!cCt|}t|}d}||fSr*_read_pfm_filer@absrr! disparity_map valid_maskrrr r= zCarlaStereo._read_disparityr>cttt|SaReturn example at given index. Args: index(int): The index of the example to retrieve Returns: tuple: A 3-tuple with ``(img_left, img_right, disparity)``. The disparity is a numpy array of shape (1, H, W) and the images are PIL images. If a ``valid_mask`` is generated within the ``transforms`` parameter, a 4-tuple with ``(img_left, img_right, disparity, valid_mask)`` is returned. rrSrrKrr>rrr rK zCarlaStereo.__getitem__r*rMrNrOrPr rQrr rrr r@rAr=rRrSrKrUrrrr rVs (rVc zeZdZdZdZddeeefdedee ddffd d Z d ede ee j dffd d Zdedeffdd ZZS)Kitti2012Stereoa  KITTI dataset from the `2012 stereo evaluation benchmark `_. Uses the RGB images for consistency with KITTI 2015. The dataset is expected to have the following structure: :: root Kitti2012 testing colored_0 1_10.png 2_10.png ... colored_1 1_10.png 2_10.png ... training colored_0 1_10.png 2_10.png ... colored_1 1_10.png 2_10.png ... disp_noc 1.png 2.png ... calib Args: root (str or ``pathlib.Path``): Root directory where `Kitti2012` is located. split (string, optional): The dataset split of scenes, either "train" (default) or "test". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. TtrainNrsplitrrcst||t|dddt|d|d}t|dd}t|dd}||||_|d krDt|d d }||d|_dStd d |jD|_dS)Nrsrrtest valid_values Kitti2012ing colored_0z*_10.png colored_1rrdisp_noc*.pngcs|]}dVqdSNNNrr+rrr r.r/z+Kitti2012Stereo.__init__.. rrrrrQr<rrr3)rrrsrleft_img_patternright_img_patterndisparity_patternrrr rszKitti2012Stereo.__init__r!cCB|durdStt|d}|dddddf}d}||fSNrgp@r@asarrayr r#rfrrr r= zKitti2012Stereo._read_disparityr>crjaReturn example at given index. Args: index(int): The index of the example to retrieve Returns: tuple: A 4-tuple with ``(img_left, img_right, disparity, valid_mask)``. The disparity is a numpy array of shape (1, H, W) and the images are PIL images. ``valid_mask`` is implicitly ``None`` if the ``transforms`` parameter does not generate a valid mask. Both ``disparity`` and ``valid_mask`` are ``None`` if the dataset split is test. rlrmrrr rK zKitti2012Stereo.__getitem__rrNrMrNrOrPr?r rQrr rrr r@rAr=rRrSrKrUrrrr rqs &,  rqc rp)Kitti2015StereoaM KITTI dataset from the `2015 stereo evaluation benchmark `_. The dataset is expected to have the following structure: :: root Kitti2015 testing image_2 img1.png img2.png ... image_3 img1.png img2.png ... training image_2 img1.png img2.png ... image_3 img1.png img2.png ... disp_occ_0 img1.png img2.png ... disp_occ_1 img1.png img2.png ... calib Args: root (str or ``pathlib.Path``): Root directory where `Kitti2015` is located. split (string, optional): The dataset split of scenes, either "train" (default) or "test". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. TrrNrrsrrcst||t|dddt|d|d}t|dd}t|dd}||||_|d krLt|d d}t|d d}||||_dStd d |jD|_dS)Nrsrtrv Kitti2015ryimage_2r}image_3rr disp_occ_0 disp_occ_1csr~rrr+rrr r.Zr/z+Kitti2015Stereo.__init__..rrrrsrrrr_r`rrr rKszKitti2015Stereo.__init__r!cCrrrrfrrr r=\rzKitti2015Stereo._read_disparityr>crjrrlrmrrr rKgrzKitti2015Stereo.__getitem__rrrrrr rs ),  rcseZdZdZgdgdgddZdZ   dd eeefd ed e ede de e de dd ffdd Z deeefde j ffdd ZdedeedeejejfffddZd eeefdd fddZdedeffdd ZZS) Middlebury2014StereoaZ Publicly available scenes from the Middlebury dataset `2014 version `. The dataset mostly follows the original format, without containing the ambient subdirectories. : :: root Middlebury2014 train scene1-{perfect,imperfect} calib.txt im{0,1}.png im1E.png im1L.png disp{0,1}.pfm disp{0,1}-n.png disp{0,1}-sd.pfm disp{0,1}y.pfm scene2-{perfect,imperfect} calib.txt im{0,1}.png im1E.png im1L.png disp{0,1}.pfm disp{0,1}-n.png disp{0,1}-sd.pfm disp{0,1}y.pfm ... additional scene1-{perfect,imperfect} calib.txt im{0,1}.png im1E.png im1L.png disp{0,1}.pfm disp{0,1}-n.png disp{0,1}-sd.pfm disp{0,1}y.pfm ... test scene1 calib.txt im{0,1}.png scene2 calib.txt im{0,1}.png ... Args: root (str or ``pathlib.Path``): Root directory of the Middleburry 2014 Dataset. split (string, optional): The dataset split of scenes, either "train" (default), "test", or "additional" use_ambient_views (boolean, optional): Whether to use different expose or lightning views when possible. The dataset samples with equal probability between ``[im1.png, im1E.png, im1L.png]``. calibration (string, optional): Whether or not to use the calibrated (default) or uncalibrated scenes. transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. download (boolean, optional): Whether or not to download the dataset in the ``root`` directory. ) Adirondack Jadeplant MotorcyclePianoPipesPlayroom PlaytableRecycleShelvesVintage) BackpackBicycle1Cable Classroom1CouchFlowersMaskShopvacSticksStorageSword1Sword2Umbrella)Plants Classroom2E Classroom2 AustraliaDjembeLCrusadePCrusadeHoopsBicycle2 StaircaseNewkuba AustraliaPDjembe LivingroomComputer)rr additionalruTrrperfectFNrrs calibrationuse_ambient_viewsrdownloadrcst||t|ddd||_|r#t|ddd|dkr"tdn|dkr2td|d |d |r9||t|d }tj ||sOt d |d |j |t fddt ||Dslt d|ddgdgdgddgd|}|D]T}d|} t||| d} t||| d} |j|| | 7_|dkrtdd|jD|_q|t||| d} t||| d} |j|| | 7_q|||_dS)Nrs)rrrurrvr)r imperfectbothNruzMSplit 'test' has only no calibration settings, please set `calibration=None`.zSplit 'zr' has calibration settings, however None was provided as an argument. Setting calibration to 'perfect' for split 'zF'. Available calibration settings are: 'perfect', 'imperfect', 'both'.Middlebury2014zThe z7 directory was not found in the provided root directoryc3s$|] }D]}||VqqdSr*) startswith)r,scenes split_scenesrr r.s z0Middlebury2014Stereo.__init__..z:Provided root folder does not contain any scenes from the z split.z-perfectz -imperfect)NrrrrXrYrZcsr~rrr+rrr r.r/z disp0.pfmz disp1.pfm)rrrrsr7_download_datasetrospathexistsr5splitsanylistdirrQrr<r3rr)rrrsrrrrcalibrartion_suffixescalibration_suffix scene_patternrrleft_dispartity_patternright_dispartity_patternrrr rsT       zMiddlebury2014Stereo.__init__r!cspt|ts t|}|jdkr2|jr2|jtfdddD}ttdd|}||t |}t |S)a Function that reads either the original right image or an augmented view when ``use_ambient_views`` is True. When ``use_ambient_views`` is True, the dataset will return at random one of ``[im1.png, im1E.png, im1L.png]`` as the right image. rZc3s|]}|VqdSr*r)r, view_name base_pathrr r.0sz1Middlebury2014Stereo._read_img..)zim1E.pngzim1L.pngcSs tj|Sr*)rrr)prrr 2s z0Middlebury2014Stereo._read_img..) isinstancernamerparentr3filterappendrandomchoicerr')rr!ambient_file_pathsrrr r'"s    zMiddlebury2014Stereo._read_imgrcCsB|durdSt|}t|}d||tjk<|dkd}||fS)Nrr)rdr@reinfsqueezerfrrr r=8s z$Middlebury2014Stereo._read_disparitycs@d}td|j}|dkrD|j|D]-}|}dD]$}|d|}|d|d}||s@t||dt|dd qqdStdtfd d |jdDrd } t| tdd t tdD]%\} } } | D]} d}t| | }tj|ddt t|t|qtqmt tddSdS)Nz8https://vision.middlebury.edu/stereo/data/scenes2014/ziprru)rr-/z.zipT)urlfilename download_rootremove_finishedc3s"|] }|tdvVqdS)ruN)rr)r,rrrr r.Ys z9Middlebury2014Stereo._download_dataset..zEhttps://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-data-F.zip)rrrzMiddEval3/testF)exist_ok MiddEval3) rrsrrrrQrmakedirsrwalkshutilmovermtree)rrbase_url split_name split_scene split_rootr scene_name scene_url test_set_url scene_dir scene_namesr-r scene_dst_dir scene_src_dirrrr rCs@   z&Middlebury2014Stereo._download_datasetr>crj)azReturn example at given index. Args: index(int): The index of the example to retrieve Returns: tuple: A 4-tuple with ``(img_left, img_right, disparity, valid_mask)``. The disparity is a numpy array of shape (1, H, W) and the images are PIL images. ``valid_mask`` is implicitly ``None`` for `split=test`. rrTrrKrmrrr rKi z Middlebury2014Stereo.__getitem__)rrrFNF)rMrNrOrPrr?r rQrr boolrrr r'r r@rAr=rrRrTrKrUrrrr rws>9 /  A* &rcsteZdZdZdZ ddeeefdee ddffdd Z d ede e j dffd d Zd edeffd d ZZS) CREStereoaSynthetic dataset used in training the `CREStereo `_ architecture. Dataset details on the official paper `repo `_. The dataset is expected to have the following structure: :: root CREStereo tree img1_left.jpg img1_right.jpg img1_left.disp.jpg img1_right.disp.jpg img2_left.jpg img2_right.jpg img2_left.disp.jpg img2_right.disp.jpg ... shapenet img1_left.jpg img1_right.jpg img1_left.disp.jpg img1_right.disp.jpg ... reflective img1_left.jpg img1_right.jpg img1_left.disp.jpg img1_right.disp.jpg ... hole img1_left.jpg img1_right.jpg img1_left.disp.jpg img1_right.disp.jpg ... Args: root (str): Root directory of the dataset. transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. TNrrrc st||t|d}gd}|D]<}t||d}t||d}|||}|j|7_t||d}t||d} ||| } |j| 7_qdS)Nr)shapenet reflectivetreeholez *_left.jpgz *_right.jpgz*_left.disp.pngz*_right.disp.pngr\) rrrdirsrr]r^rHr_r`rarrr rs   zCREStereo.__init__r!cC<tjt|tjd}|dddddfd}d}||fS)Ndtypeg@@r@rr r#float32rfrrr r=zCREStereo._read_disparityr>crj)aReturn example at given index. Args: index(int): The index of the example to retrieve Returns: tuple: A 4-tuple with ``(img_left, img_right, disparity, valid_mask)``. The disparity is a numpy array of shape (1, H, W) and the images are PIL images. ``valid_mask`` is implicitly ``None`` if the ``transforms`` parameter does not generate a valid mask. rlrmrrr rKrnzCREStereo.__getitem__r*rrrrr rws) rc reZdZdZddeeefdedeeddffdd Z d ede e j dffd d Z d edeffdd ZZS)FallingThingsStereoa`FallingThings `_ dataset. The dataset is expected to have the following structure: :: root FallingThings single dir1 scene1 _object_settings.json _camera_settings.json image1.left.depth.png image1.right.depth.png image1.left.jpg image1.right.jpg image2.left.depth.png image2.right.depth.png image2.left.jpg image2.right ... scene2 ... mixed scene1 _object_settings.json _camera_settings.json image1.left.depth.png image1.right.depth.png image1.left.jpg image1.right.jpg image2.left.depth.png image2.right.depth.png image2.left.jpg image2.right ... scene2 ... Args: root (str or ``pathlib.Path``): Root directory where FallingThings is located. variant (string): Which variant to use. Either "single", "mixed", or "both". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. singleNrvariantrrc st||t|d}t|ddddgdgddgd|}tddtdd}|D]H}t||||d }t||||d }|j|||7_t||||d } t||||d } |j|| | 7_q-dS) N FallingThingsr)rmixedrrvrrrX)rrz *.left.jpgz *.right.jpgz*.left.depth.pngz*.right.depth.pngrrrrrQrr<r) rrrrvariants split_prefixrrrr_r`rrr rs(  zFallingThingsStereo.__init__r!c Cstt|}t|jd}t|d8}t|}|dddd}d\}}||||tj } | dddddf} d} | | fWdS1sOwYdS)Nz_camera_settings.jsonrcamera_settingsrintrinsic_settingsfx)d) r@rr r#rrjsonloadastyper ) rr!depthcamera_settings_pathf intrinsicsfocalbaselinepixel_constantrgrhrrr r=s  $z#FallingThingsStereo._read_disparityr>crjrkrlrmrrr rK(rnzFallingThingsStereo.__getitem__)rNrorrrr r s ,,r c s|eZdZdZ   ddeeefdededeed df fd d Z d ed e e j dffd dZ ded effdd ZZS)SceneFlowStereoaDataset interface for `Scene Flow `_ datasets. This interface provides access to the `FlyingThings3D, `Monkaa` and `Driving` datasets. The dataset is expected to have the following structure: :: root SceneFlow Monkaa frames_cleanpass scene1 left img1.png img2.png right img1.png img2.png scene2 left img1.png img2.png right img1.png img2.png frames_finalpass scene1 left img1.png img2.png right img1.png img2.png ... ... disparity scene1 left img1.pfm img2.pfm right img1.pfm img2.pfm FlyingThings3D ... ... Args: root (str or ``pathlib.Path``): Root directory where SceneFlow is located. variant (string): Which dataset variant to user, "FlyingThings3D" (default), "Monkaa" or "Driving". pass_name (string): Which pass to use, "clean" (default), "final" or "both". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. FlyingThings3DcleanNrr pass_namerrc s(t||t|d}t|dddt|ddddgdgddgd|}||}td td d d td d d d }|D]P}t||||d d }t||||d d } |j||| 7_t|d||d d} t|d||d d} |j|| | 7_qAdS)N SceneFlowr)r&DrivingMonkaarvr()r'finalrframes_cleanpassframes_finalpassrX)r+r&r*r1r}r2 disparityz*.pfmr) rrrr(rpassesprefix_directoriesrr]r^r_r`rrr rms. zSceneFlowStereo.__init__r!cCrbr*rcrfrrr r=rizSceneFlowStereo._read_disparityr>crjrkrlrmrrr rKrnzSceneFlowStereo.__getitem__)r&r'Nrorrrr r%7s$8 %r%c seZdZdZdZddeeefdedee ddffd d Z d ede eeffd d Z d edee de e je jfffddZdedeffdd ZZS) SintelStereoaSintel `Stereo Dataset `_. The dataset is expected to have the following structure: :: root Sintel training final_left scene1 img1.png img2.png ... ... final_right scene2 img1.png img2.png ... ... disparities scene1 img1.png img2.png ... ... occlusions scene1 img1.png img2.png ... ... outofframe scene1 img1.png img2.png ... ... Args: root (str or ``pathlib.Path``): Root directory where Sintel Stereo is located. pass_name (string): The name of the pass to use, either "final", "clean" or "both". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. Tr,Nrr(rrc st||t|dddt|d}dgdgddgd|}|D]B}t|d|dd d }t|d|d d d }|j|||7_t|dd d d }|j||d7_q"dS) Nr()r,r'rrvSintelr,r'training_leftrXr}_rightra)rrrrrQrr<r) rrr(r pass_namesrrrrrrr rs  zSintelStereo.__init__r!cCst|}|j}|j}|jj}t|d|j|}t|d|j|}tj|s2td|dtj|s@td|d||fS)N occlusions outofframezOcclusion mask z does not existzOut of frame mask )rrrrQrrrr5)rr!fpathbasenamescenedir sampledirocclusion_pathoutofframe_pathrrr _get_occlussion_mask_pathss  z'SintelStereo._get_occlussion_mask_pathsrc Cs|durdStjt|tjd}tj|ddd\}}}|d|d|d}t|d }||\}}tt|d k}tt|d k} t| |}||fS) Nrr)axis@i@)rr r) r@rr r#r rs transposer@ logical_and) rr!rgrgbocclued_mask_pathout_of_frame_mask_pathrhoff_maskrrr r=s  zSintelStereo._read_disparityr>crj)aReturn example at given index. Args: index(int): The index of the example to retrieve Returns: tuple: A 4-tuple with ``(img_left, img_right, disparity, valid_mask)`` is returned. The disparity is a numpy array of shape (1, H, W) and the images are PIL images whilst the valid_mask is a numpy array of shape (H, W). rrmrrr rKrzSintelStereo.__getitem__)r,N)rMrNrOrPr?r rQrr rrr r@r@rAr=rRrTrKrUrrrr r2s,,*r2c r ) InStereo2ka`InStereo2k `_ dataset. The dataset is expected to have the following structure: :: root InStereo2k train scene1 left.png right.png left_disp.png right_disp.png ... scene2 ... test scene1 left.png right.png left_disp.png right_disp.png ... scene2 ... Args: root (str or ``pathlib.Path``): Root directory where InStereo2k is located. split (string): Either "train" or "test". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. rrNrrsrrcst||t|d|}t|dddt|dd}t|dd}||||_t|dd}t|dd }||||_dS) NrNrsrtrvrXzleft.pngz right.pngz left_disp.pngzright_disp.png)rrrrrQr<rrrrrr rAszInStereo2k.__init__r!cCr)Nrg@r rfrrr r=Pr zInStereo2k._read_disparityr>crjrkrlrmrrr rKWrnzInStereo2k.__getitem__rrorrrr rN!s ,rNc seZdZdZdZddeeefdedee ddffd d Z d edee d e e j e j fffd dZdedeffdd ZZS) ETH3DStereoafETH3D `Low-Res Two-View `_ dataset. The dataset is expected to have the following structure: :: root ETH3D two_view_training scene1 im1.png im0.png images.txt cameras.txt calib.txt scene2 im1.png im0.png images.txt cameras.txt calib.txt ... two_view_training_gt scene1 disp0GT.pfm mask0nocc.png scene2 disp0GT.pfm mask0nocc.png ... two_view_testing scene1 im1.png im0.png images.txt cameras.txt calib.txt scene2 im1.png im0.png images.txt cameras.txt calib.txt ... Args: root (str or ``pathlib.Path``): Root directory of the ETH3D Dataset. split (string, optional): The dataset split of scenes, either "train" (default) or "test". transforms (callable, optional): A function/transform that takes in a sample and returns a transformed version. TrrNrrsrrc st||t|dddt|d}|dkrdnd}d}t||d d }t||d d }||||_|d krJtd d|jD|_dSt||d d}||d|_dS)NrsrtrvETH3Drrtwo_view_training two_view_testtwo_view_training_gtrXrYrZrucsr~rrr+rrr r.r/z'ETH3DStereo.__init__..r[) rrrrrQr<rr3r) rrrsrimg_diranot_dirrrrrrr rs zETH3DStereo.__init__r!rcCsN|durdSt|}t|}t|jd}t|}t|t }||fS)Nrz mask0nocc.png) rdr@rerrr r#rrr)rr!rg mask_pathrhrrr r=s  zETH3DStereo._read_disparityr>crjrrrmrrr rKrzETH3DStereo.__getitem__r)rMrNrOrPr?r rQrr rrr r@rAr=rRrTrKrUrrrr rOfs 1,* rO)- functoolsrrrrabcrrrpathlibrtypingrrrr r r numpyr@PILr utilsrrrvisionrrArSrT__all__partialrdrrVrqrrrr r%r2rNrOrrrr s<     q@UXXhpzE