+
     °³j8!  ã                   ó  € R t ^ RIHtHt ^ RIt^ RIHtHt ^RIHt	H
t
 . ROt ! R
 R]P                  4      t ! R R]P                  4      t ! R R]P                  4      t ! R R]P                  4      t ! R R	]P                  4      tR# )zÙ
This file is part of the private API. Please do not use directly these classes as they will be modified on
future versions without warning. The classes should be accessed only via the transforms argument of Weights.
)ÚOptionalÚUnionN)ÚnnÚTensor)Ú
functionalÚInterpolationModeÚObjectDetectionÚImageClassificationÚVideoClassificationÚSemanticSegmentationÚOpticalFlowc                   óV   a € ] tR t^t o V 3R lR ltV 3R lR ltV 3R lR ltRtV tR# )	r   c                ó&   <€ V ^8„  d   QhRS[ RS[ /# ©é   ÚimgÚreturn©r   )ÚformatÚ__classdict__s   "€Ú`/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torchvision/transforms/_presets.pyÚ__annotate__ÚObjectDetection.__annotate__   s   ø€ ÷ 7ñ 7™6ð 7¡fñ 7ó    c                ó¤   € \        V\        4      '       g   \        P                  ! V4      p\        P                  ! V\
        P                  4      # ©N)Ú
isinstancer   ÚFÚpil_to_tensorÚconvert_image_dtypeÚtorchÚfloat©Úselfr   s   &&r   ÚforwardÚObjectDetection.forward   s4   € Ü˜#œv×&Ò&Ü—/’/ #Ó&ˆCÜ×$Ò$ S¬%¯+©+Ó6Ð6r   c                ó    <€ V ^8„  d   QhRS[ /# ©r   r   ©Ústr)r   r   s   "€r   r   r      ó   ø€ ÷ .ñ .™#ñ .r   c                ó<   € V P                   P                  R ,           # ©z()©Ú	__class__Ú__name__©r#   s   &r   Ú__repr__ÚObjectDetection.__repr__   ó   € Ø�~‰~×&Ñ&¨Õ-Ð-r   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   r       ó   ø€ ÷ 
ñ 
™#ñ 
r   c                ó   €  R # )z“Accepts ``PIL.Image``, batched ``(B, C, H, W)`` and single ``(C, H, W)`` image ``torch.Tensor`` objects. The images are rescaled to ``[0.0, 1.0]``.© r0   s   &r   ÚdescribeÚObjectDetection.describe    s   € ð9ñ	
r   r7   N©	r/   Ú
__module__Ú__qualname__Ú__firstlineno__r$   r1   r8   Ú__static_attributes__Ú__classdictcell__©r   s   @r   r   r      s#   ø‡ € ÷7ð 7÷
.ð .÷
ö 
r   c            
       ó    a a€ ] tR t^'t oRRRRRRR]P
                  RR/V3R lV 3R	 llltV3R
 lR ltV3R lR ltV3R lR lt	Rt
VtV ;t# )r	   Úresize_sizeé   ÚmeanÚstdÚinterpolationÚ	antialiasTc                óz   <€ V ^8„  d   QhRS[ RS[ RS[S[R3,          RS[S[R3,          RS[RS[S[,          RR	/# )
r   Ú	crop_sizerB   rD   .rE   rF   rG   r   N)ÚintÚtupler!   r   r   Úbool)r   r   s   "€r   r   Ú ImageClassification.__annotate__(   si   ø€ ÷ #ñ #ñ ð#ñ ð	#ñ
 ‘E˜3�JÕð#ñ ‘5˜#�:Õð#ñ )ð#ñ ™D•>ð#ð 
ñ#r   c               óœ   <€ \         SV `  4        V.V n        V.V n        \	        V4      V n        \	        V4      V n        WPn        W`n        R # r   )	ÚsuperÚ__init__rI   rB   ÚlistrD   rE   rF   rG   )r#   rI   rB   rD   rE   rF   rG   r.   s   &$$$$$$€r   rP   ÚImageClassification.__init__(   sD   ø€ ô 	‰ÑÔØ#˜ˆŒØ'˜=ˆÔÜ˜“JˆŒ	Ü˜“9ˆŒØ*ÔØ"Žr   c                ó&   <€ V ^8„  d   QhRS[ RS[ /# r   r   )r   r   s   "€r   r   rM   :   ó   ø€ ÷ ñ ™6ð ¡fñ r   c                ó®  € \         P                  ! WP                  V P                  V P                  R 7      p\         P
                  ! WP                  4      p\        V\        4      '       g   \         P                  ! V4      p\         P                  ! V\        P                  4      p\         P                  ! WP                  V P                  R7      pV# ©©rF   rG   ©rD   rE   )r   ÚresizerB   rF   rG   Úcenter_croprI   r   r   r   r   r    r!   Ú	normalizerD   rE   r"   s   &&r   r$   ÚImageClassification.forward:   s‡   € Ü�hŠh�s×,Ñ,¸D×<NÑ<NÐZ^×ZhÑZhÔiˆÜ�mŠm˜C§¡Ó0ˆÜ˜#œv×&Ò&Ü—/’/ #Ó&ˆCÜ×#Ò# C¬¯©Ó5ˆÜ�kŠk˜#§I¡I°4·8±8Ô<ˆØˆ
r   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   rM   C   ó   ø€ ÷ ñ ™#ñ r   c                ó.  € V P                   P                  R ,           pVRV P                   2,          pVRV P                   2,          pVRV P                   2,          pVRV P
                   2,          pVRV P                   2,          pVR,          pV# ©Ú(z
    crop_size=ú
    resize_size=ú

    mean=ú	
    std=ú
    interpolation=ú
)©r.   r/   rI   rB   rD   rE   rF   ©r#   Úformat_strings   & r   r1   ÚImageClassification.__repr__C   ó™   € ØŸ™×/Ñ/°#Õ5ˆØÐ+¨D¯N©NÐ+;Ð<Õ<ˆØÐ-¨d×.>Ñ.>Ð-?Ð@Õ@ˆØ˜; t§y¡y kÐ2Õ2ˆØ˜: d§h¡h ZÐ0Õ0ˆØÐ/°×0BÑ0BÐ/CÐDÕDˆØ˜ÕˆØÐr   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   rM   M   ó   ø€ ÷ 
ñ 
™#ñ 
r   c                óŠ   € R V P                    RV P                   RV P                   RV P                   RV P                   R2# )ú‘Accepts ``PIL.Image``, batched ``(B, C, H, W)`` and single ``(C, H, W)`` image ``torch.Tensor`` objects. The images are resized to ``resize_size=ú`` using ``interpolation=ú.``, followed by a central crop of ``crop_size=ú]``. Finally the values are first rescaled to ``[0.0, 1.0]`` and then normalized using ``mean=ú`` and ``std=ú``.©rB   rF   rI   rD   rE   r0   s   &r   r8   ÚImageClassification.describeM   s]   € ð7Ø7;×7GÑ7GÐ6HÐHaÐbf×btÑbtÐauð v9Ø9=¿¹Ð8Hð I?Ø?C¿y¹y¸kÈÐW[×W_ÑW_ÐV`Ð`cðeð	
r   )rG   rI   rF   rD   rB   rE   ©g
×£p=
ß?gÉv¾Ÿ/Ý?g–C‹lçûÙ?©gZd;ßOÍ?gyé&1¬Ì?gÍÌÌÌÌÌÌ?©r/   r;   r<   r=   r   ÚBILINEARrP   r$   r1   r8   r>   r?   Ú__classcell__©r.   r   s   @@r   r	   r	   '   sj   ù‡ € ð#ð ð	#ð
 #8ð#ð "7ð#ð ,=×+EÑ+Eð#ð %)÷#õ #÷$ð ÷ð ÷
÷ 
ð 
r   c                   ó˜   a a€ ] tR t^Vt oRRRRR]P
                  /V3R lV 3R llltV3R lR ltV3R lR	 ltV3R
 lR lt	Rt
VtV ;t# )r
   rD   rE   rF   c                ó¶   <€ V ^8„  d   QhRS[ S[S[3,          RS[S[ S[,          S[ S[S[3,          3,          RS[ S[R3,          RS[ S[R3,          RS[RR/# )	r   rI   rB   rD   .rE   rF   r   N)rK   rJ   r   r!   r   )r   r   s   "€r   r   Ú VideoClassification.__annotate__W   sy   ø€ ÷ +ñ +ñ ™™c˜•?ð+ñ ™5¡�:¡u©S±#¨X¥Ð6Õ7ð	+ñ
 ‘E˜3�JÕð+ñ ‘5˜#�:Õð+ñ )ð+ð 
ñ+r   c               ó°   <€ \         SV `  4        \        V4      V n        \        V4      V n        \        V4      V n        \        V4      V n        WPn        R # r   )rO   rP   rQ   rI   rB   rD   rE   rF   )r#   rI   rB   rD   rE   rF   r.   s   &$$$$$€r   rP   ÚVideoClassification.__init__W   sD   ø€ ô 	‰ÑÔÜ˜i›ˆŒÜ Ó,ˆÔÜ˜“JˆŒ	Ü˜“9ˆŒØ*Ör   c                ó&   <€ V ^8„  d   QhRS[ RS[ /# )r   Úvidr   r   )r   r   s   "€r   r   r   g   s   ø€ ÷ ñ ™6ð ¡fñ r   c                óv  € R pVP                   ^8  d   VP                  ^ R7      pRpVP                  w  r4rVpVP                  RWVV4      p\        P
                  ! WP                  V P                  R R7      p\        P                  ! WP                  4      p\        P                  ! V\        P                  4      p\        P                  ! WP                  V P                  R7      pV P                  w  rgVP                  W4WVV4      pVP!                  ^ ^^^^4      pV'       d   VP#                  ^ R7      pV# )F)ÚdimTrW   rX   éÿÿÿÿ)ÚndimÚ	unsqueezeÚshapeÚviewr   rY   rB   rF   rZ   rI   r   r    r!   r[   rD   rE   ÚpermuteÚsqueeze)r#   rƒ   Úneed_squeezeÚNÚTÚCÚHÚWs   &&      r   r$   ÚVideoClassification.forwardg   sô   € ØˆØ�8‰8�aŒ<Ø—-‘- A�-Ó&ˆCØˆLàŸ	™	‰ˆˆa�AØ�h‰h�r˜1 Ó#ˆô
 �hŠh�s×,Ñ,¸D×<NÑ<NÐZ_Ô`ˆÜ�mŠm˜C§¡Ó0ˆÜ×#Ò# C¬¯©Ó5ˆÜ�kŠk˜#§I¡I°4·8±8Ô<ˆØ�~‰~‰ˆØ�h‰h�q˜Q 1Ó%ˆØ�k‰k˜!˜Q  1 aÓ(ˆçØ—+‘+ !�+Ó$ˆCØˆ
r   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   r      r^   r   c                ó.  € V P                   P                  R ,           pVRV P                   2,          pVRV P                   2,          pVRV P                   2,          pVRV P
                   2,          pVRV P                   2,          pVR,          pV# r`   rg   rh   s   & r   r1   ÚVideoClassification.__repr__   rk   r   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   r   ‰   s   ø€ ÷ 
ñ 
™#ñ 
r   c                óŠ   € R V P                    RV P                   RV P                   RV P                   RV P                   R2# )zŽAccepts batched ``(B, T, C, H, W)`` and single ``(T, C, H, W)`` video frame ``torch.Tensor`` objects. The frames are resized to ``resize_size=rp   rq   rr   rs   zP``. Finally the output dimensions are permuted to ``(..., C, T, H, W)`` tensors.ru   r0   s   &r   r8   ÚVideoClassification.describe‰   sa   € ð7Ø7;×7GÑ7GÐ6HÐHaÐbf×btÑbtÐauð v9Ø9=¿¹Ð8Hð I?Ø?C¿y¹y¸kÈÐW[×W_ÑW_ÐV`ð aHðHð	
r   )rI   rF   rD   rB   rE   )gFë¨j‚¨Û?gñõµ.5BÙ?g�¥½ÁØ?)grá@H0Í?gcÙ=yXÌ?gD¾K©KÆË?ry   r|   s   @@r   r
   r
   V   sV   ù‡ € ð+ð
 #?ð+ð ">ð+ð ,=×+EÑ+E÷+õ +÷ ð ÷0ð ÷
÷ 
ð 
r   c                   óœ   a a€ ] tR t^“t oRRRRR]P
                  RR/V3R lV 3R llltV3R lR	 ltV3R
 lR ltV3R lR lt	Rt
VtV ;t# )r   rD   rE   rF   rG   Tc                ó„   <€ V ^8„  d   QhRS[ S[,          RS[S[R3,          RS[S[R3,          RS[RS[ S[,          RR/# )	r   rB   rD   .rE   rF   rG   r   N)r   rJ   rK   r!   r   rL   )r   r   s   "€r   r   Ú!SemanticSegmentation.__annotate__”   sc   ø€ ÷ #ñ #ñ ™c•]ð#ñ ‘E˜3�JÕð	#ñ
 ‘5˜#�:Õð#ñ )ð#ñ ™D•>ð#ð 
ñ#r   c               ó˜   <€ \         SV `  4        Ve   V.MR V n        \        V4      V n        \        V4      V n        W@n        WPn        R # r   )rO   rP   rB   rQ   rD   rE   rF   rG   )r#   rB   rD   rE   rF   rG   r.   s   &$$$$$€r   rP   ÚSemanticSegmentation.__init__”   sB   ø€ ô 	‰ÑÔØ,7Ò,C˜K™=ÈˆÔÜ˜“JˆŒ	Ü˜“9ˆŒØ*ÔØ"Žr   c                ó&   <€ V ^8„  d   QhRS[ RS[ /# r   r   )r   r   s   "€r   r   rœ   ¤   rT   r   c                ó®  € \        V P                  \        4      '       d8   \        P                  ! WP                  V P
                  V P                  R 7      p\        V\        4      '       g   \        P                  ! V4      p\        P                  ! V\        P                  4      p\        P                  ! WP                  V P                  R7      pV# rV   )r   rB   rQ   r   rY   rF   rG   r   r   r   r    r!   r[   rD   rE   r"   s   &&r   r$   ÚSemanticSegmentation.forward¤   sˆ   € Ü�d×&Ñ&¬×-Ò-Ü—(’(˜3× 0Ñ 0À×@RÑ@RÐ^b×^lÑ^lÔmˆCÜ˜#œv×&Ò&Ü—/’/ #Ó&ˆCÜ×#Ò# C¬¯©Ó5ˆÜ�kŠk˜#§I¡I°4·8±8Ô<ˆØˆ
r   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   rœ   ­   s   ø€ ÷ ñ ™#ñ r   c                ó  € V P                   P                  R ,           pVRV P                   2,          pVRV P                   2,          pVRV P                   2,          pVRV P
                   2,          pVR,          pV# )ra   rb   rc   rd   re   rf   )r.   r/   rB   rD   rE   rF   rh   s   & r   r1   ÚSemanticSegmentation.__repr__­   s‚   € ØŸ™×/Ñ/°#Õ5ˆØÐ-¨d×.>Ñ.>Ð-?Ð@Õ@ˆØ˜; t§y¡y kÐ2Õ2ˆØ˜: d§h¡h ZÐ0Õ0ˆØÐ/°×0BÑ0BÐ/CÐDÕDˆØ˜ÕˆØÐr   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   rœ   ¶   rm   r   c           	     óp   € R V P                    RV P                   RV P                   RV P                   R2	# )ro   rp   rr   rs   rt   )rB   rF   rD   rE   r0   s   &r   r8   ÚSemanticSegmentation.describe¶   sP   € ð7Ø7;×7GÑ7GÐ6HÐHaÐbf×btÑbtÐauð vhØhl×hqÑhqÐgrð sØ—X‘X�J˜cð#ð	
r   )rG   rF   rD   rB   rE   rw   rx   ry   r|   s   @@r   r   r   “   s`   ù‡ € ð#ð #8ð	#ð
 "7ð#ð ,=×+EÑ+Eð#ð %)÷#õ #÷ ð ÷ð ÷
÷ 
ð 
r   c                   óV   a € ] tR t^¿t o V 3R lR ltV 3R lR ltV 3R lR ltRtV tR# )	r   c                óB   <€ V ^8„  d   QhRS[ RS[ RS[S[ S[ 3,          /# )r   Úimg1Úimg2r   )r   rK   )r   r   s   "€r   r   ÚOpticalFlow.__annotate__À   s+   ø€ ÷ ñ ™Fð ©&ð ±U¹6Á6¸>Õ5Jñ r   c                ó   € \        V\        4      '       g   \        P                  ! V4      p\        V\        4      '       g   \        P                  ! V4      p\        P                  ! V\
        P                  4      p\        P                  ! V\
        P                  4      p\        P                  ! V. RO. ROR7      p\        P                  ! V. RO. ROR7      pVP                  4       pVP                  4       pW3# )ç      à?rX   )r®   r®   r®   )	r   r   r   r   r   r    r!   r[   Ú
contiguous)r#   rª   r«   s   &&&r   r$   ÚOpticalFlow.forwardÀ   sª   € Ü˜$¤×'Ò'Ü—?’? 4Ó(ˆDÜ˜$¤×'Ò'Ü—?’? 4Ó(ˆDä×$Ò$ T¬5¯;©;Ó7ˆÜ×$Ò$ T¬5¯;©;Ó7ˆô �{Š{˜4¢oº?ÔKˆÜ�{Š{˜4¢oº?ÔKˆà�‰Ó ˆØ�‰Ó ˆàˆzÐr   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   r¬   Ò   r*   r   c                ó<   € V P                   P                  R ,           # r,   r-   r0   s   &r   r1   ÚOpticalFlow.__repr__Ò   r3   r   c                ó    <€ V ^8„  d   QhRS[ /# r'   r(   )r   r   s   "€r   r   r¬   Õ   r5   r   c                ó   €  R # )z”Accepts ``PIL.Image``, batched ``(B, C, H, W)`` and single ``(C, H, W)`` image ``torch.Tensor`` objects. The images are rescaled to ``[-1.0, 1.0]``.r7   r0   s   &r   r8   ÚOpticalFlow.describeÕ   s   € ð:ñ	
r   r7   Nr:   r@   s   @r   r   r   ¿   s#   ø‡ € ÷ð ÷$.ð .÷
ö 
r   )r   r	   r
   r   r   )Ú__doc__Útypingr   r   r    r   r   Ú r   r   r   Ú__all__ÚModuler   r	   r
   r   r   r7   r   r   Ú<module>r¼      sr   ðñ÷
 #ã ß ç 0ò€ô
�b—i‘iô 
ô ,
˜"Ÿ)™)ô ,
ô^:
˜"Ÿ)™)ô :
ôz)
˜2Ÿ9™9ô )
ôX
�"—)‘)ö 
r   