
    qi9                        d dl Z d dlZd dlmZ d dlZd dlmc mZ	 d dl
mc mZ  e j        ej        d          ej        ej        j        j        fdej        ej        df         ej        ej        df         z  dededej        j        d	ej        ej        d
f         ej        ej        d
f         z  f
d                        Z	 ddej        dededed	ej        f
dZdS )    N)         )static_argnumsimagesz*b h w cheightwidthmethodreturnz*b {height} {width} cc                 h   | j         dk    }|s| d         } | j        dd         \  }}t          ||z  ||z            }t          ||z            }t          ||z            }	t          j                            | | j        d         ||	| j        d         f|          }
| j        t          j	        k    rFt          j
        |
                              dd                              t          j	                  }
nC| j        t          j        k    r|
                    dd	          }
nt          d
| j                   t          ||z
  d          \  }}||z   }t          ||	z
  d          \  }}||z   }t          j        |
d||f||fdf| j        t          j	        k    rdnd          }|s|d         }|S )zReplicates tf.image.resize_with_pad. Resizes an image to a target height and width without distortion
    by padding with black. If the image is float32, it must be in the range [-1, 1].
       Nr   r   r   )r
                  ?Unsupported image dtype: r   )r   r   )constant_values)ndimshapemaxintjaximageresizedtypejnpuint8roundclipastypefloat32
ValueErrordivmodpad)r   r   r	   r
   has_batch_dim
cur_height	cur_widthratioresized_heightresized_widthresized_imagespad_h0remainder_hpad_h1pad_w0remainder_wpad_w1padded_imagess                     :/home/robot-lab/Pi0.5_yam/src/openpi/shared/image_tools.pyresize_with_padr3      s    K1$M "L1-J		E!:#677Ee+,,N	E)**MY%%a.-aQZ` &  N |sy  >22773??FFsyQQ		$	$',,T377CV\CCDDD .!8!<<FKk!F !6::FKk!FG	&&!FF#3V<#\SY66D  M  )%a(    bilinearmodec                    | j         d         dk    rHd}|                                 dk    r|                     d          } |                     dddd          } n/d}|                                 dk    r|                     d          } | j         \  }}}}t	          ||z  ||z            }	t          ||	z            }
t          ||	z            }t          j        | |
|f||d	k    rdnd
          }| j        t          j
        k    rFt          j        |                              dd                              t          j
                  }nC| j        t          j        k    r|                    dd          }nt          d| j                   t!          ||
z
  d          \  }}||z   }t!          ||z
  d          \  }}||z   }| j        t          j
        k    rdnd}t          j        |||||fd|          }|rD|                    dddd          }|dk    r&| j         d         dk    r|                    d          }|S )a  PyTorch version of resize_with_pad. Resizes an image to a target height and width without distortion
    by padding with black. If the image is float32, it must be in the range [-1, 1].

    Args:
        images: Tensor of shape [*b, h, w, c] or [*b, c, h, w]
        height: Target height
        width: Target width
        mode: Interpolation mode ('bilinear', 'nearest', etc.)

    Returns:
        Resized and padded tensor with same shape format as input
    r   Tr   r   r   r   Fr5   N)sizer6   align_cornersr   r   r   r   constant)r6   value)r   dim	unsqueezepermuter   r   Finterpolater   torchr   r   clamptor    r!   r"   r#   squeeze)r   r   r	   r6   channels_last
batch_sizechannelsr%   r&   r'   r(   r)   r*   r+   r,   r-   r.   r/   r0   constant_valuer1   s                        r2   resize_with_pad_torchrJ   7   sm   & |B1::<<1%%a((F1a++::<<1%%a((F28,/J*i 	E!:#677Ee+,,N	E)**M ]nm44X\`jXjXjuupt  N
 |u{""^44::1cBBEEekRR		&	&'--dC88CV\CCDDD !.!8!<<FKk!F !6::FKk!F !,%+55QQ4NE	(	  M  5%--aAq99??v|A!33)11!44Mr4   )r5   )	functoolsr   	jax.numpynumpyr   rB   torch.nn.functionalnn
functionalr@   openpi.shared.array_typingsharedarray_typingatpartialjit	typecheckr   ResizeMethodLINEARUInt8ArrayFloatr   r3   TensorstrrJ    r4   r2   <module>r`      s       



                 ' ' ' ' ' ' ' ' ' 379555
 &)Y%;%B	' 'HRXz)*RXbh
6J-KK'' ' I"	'
 Xbh//028BHF]<]3^^' ' '  65'\ 	G GLGG G 	G
 \G G G G G Gr4   