o oi7@sddlmZddlmZddlmZddlZddlmZm Z ddl Z ddl m Z mZmZddlmZmZddlmZmZmZmZmZdd lmZmZmZdd lmZeZeZ Gd d d Z!dS) ) annotations)Path)AnyN) from_dlpack to_dlpack)DeviceDtypeTensor) KORNIA_CHECKKORNIA_CHECK_SHAPE) ChannelsOrder ColorSpace ImageLayout ImageSize PixelFormat) ImageLoadType load_image write_image)image_to_stringc@sZeZdZdZdSd d ZdTd dZdUdVddZdWddZedXddZ edYddZ edZddZ ed[d!d"Z ed\d#d$Z ed]d%d&Zed^d(d)Zed_d+d,Zed^d-d.Zed^d/d0Zed`d2d3ZdWd4d5ZdWd6d7ZdWd8d9ZdWd:d;Zeejejfdad@dAZdbdBdCZedcdEdFZdddGdHZ ededKdLZ!dfdMdNZ"dgdhdQdRZ#dS)iImagea>Class that holds an Image Tensor representation. .. note:: Disclaimer: This class provides the minimum functionality for image manipulation. However, as soon as you start to experiment with advanced tensor manipulation, you might expect fancy polymorphic behaviours. .. warning:: This API is experimental and might suffer changes in the future. Args: data: a torch tensor containing the image data. layout: a dataclass containing the image layout information. Examples: >>> # from a torch.tensor >>> data = torch.randint(0, 255, (3, 4, 5), dtype=torch.uint8) # CxHxW >>> pixel_format = PixelFormat( ... color_space=ColorSpace.RGB, ... bit_depth=8, ... ) >>> layout = ImageLayout( ... image_size=ImageSize(4, 5), ... channels=3, ... channels_order=ChannelsOrder.CHANNELS_FIRST, ... ) >>> img = Image(data, pixel_format, layout) >>> assert img.channels == 3 >>> # from a numpy array (like opencv) >>> data = np.ones((4, 5, 3), dtype=np.uint8) # HxWxC >>> img = Image.from_numpy(data, color_space=ColorSpace.RGB) >>> assert img.channels == 3 >>> assert img.width == 5 >>> assert img.height == 4 datar pixel_formatrlayoutrreturnNonecCs|jtjkrt|jt|jjt|jjg}n |jtjkr.t|jjt|jjt|jg}n t d|jdt ||t | |j dkd||_||_||_dS)zImage constructor. Args: data: a torch tensor containing the image data. pixel_format: the pixel format of the image. layout: a dataclass containing the image layout information. zLayout z not implemented.zInvalid bit depth.N)channels_orderr CHANNELS_FIRSTstrchannels image_sizeheightwidth CHANNELS_LASTNotImplementedErrorr r element_size bit_depth_data _pixel_format_layout)selfrrrshaper,F/home/ubuntu/.local/lib/python3.10/site-packages/kornia/image/image.py__init__Os " "  zImage.__init__rcCsd|jd|jd|jS)Nz Image data: z Pixel Format: z Layout: )rrrr*r,r,r-__repr__gszImage.__repr__NdevicerdtypercCs2|durt|tjr|d}}|j|||_|S)aMove the image to the given device and dtype. Args: device: the device to move the image to. dtype: the data type to cast the image to. Returns: Image: the image moved to the given device and dtype. N) isinstancetorchr2rtor')r*r1r2r,r,r-r5ks zImage.tocCst|j|j|jS)zReturn a copy of the image.)rrclonerrr/r,r,r-r6}sz Image.clonecC|jS)z"Return the underlying tensor data.)r'r/r,r,r-rz Image.datatuple[int, ...]cC|jjS)zReturn the image shape.)rr+r/r,r,r-r+z Image.shape torch.dtypecCr:)zReturn the image data type.)rr2r/r,r,r-r2r;z Image.dtype torch.devicecCr:)zReturn the image device.)rr1r/r,r,r-r1r;z Image.devicecCr7)zReturn the pixel format.)r(r/r,r,r-rr8zImage.pixel_formatcCr7)zReturn the image layout.)r)r/r,r,r-rr8z Image.layoutintcCr:)z(Return the number channels of the image.)rrr/r,r,r-rr;zImage.channelsrcCr:)zReturn the image size.)rr r/r,r,r-r r;zImage.image_sizecCt|jjjS)z"Return the image height (columns).)r>rr r!r/r,r,r-r!z Image.heightcCr?)zReturn the image width (rows).)r>rr r"r/r,r,r-r"r@z Image.widthr cCr:)zReturn the channels order.)rrr/r,r,r-rr;zImage.channels_ordercCs|j|_|S)zReturn the image as float.)rfloatr'r/r,r,r-rAs z Image.floatcCs|jj}|j}|tjkr|S|jjtjk}|r+|j dkr$| ddddn| ddd}|tj kr7t j |}n|tjkrCt j |}ntd||ro|j dkrZ| dddd}n|j dkrg| ddd}ntd|jttj|jjd}t|jjd|jjd }t|||S) z Converts the image to grayscale.rz.Unsupported source color space for to_gray(): z-Unexpected shape after grayscale conversion:  color_spacer&rr)r(rGr'r GRAYr)rr r#ndimpermuteRGBkorniacolorrgb_to_grayscaleBGRbgr_to_grayscale ValueErrorr+rr&rr rr*srcris_channels_lastoutnew_pf new_layoutr,r,r-to_grays* (     z Image.to_graycCs|jj}|j}|tjkr|S|jjtjk}|r+|j dkr$| ddddn| ddd}|tj kr7t j |}n%|tjkrU|j dkrL|ddgddfn|gddf}ntd ||rr|j dkrk| ddddn| ddd}ttj|jjd }t|jjd|jjd }t|||S) zConverts the image to RGB.rBrrCrDrENrErDr.z-Unsupported source color space for to_rgb(): rFrH)r(rGr'r rLr)rr r#rJrKrIrMrNgrayscale_to_rgbrPrRrr&rr rrSr,r,r-to_rgbs" (  2( z Image.to_rgbcCsH|jj}|j}|tjkr|S|jjtjk}|r+|j dkr$| ddddn| ddd}|tj krOt j |}|j dkrF|ddgddfn|gddf}n%|tjkrm|j dkrd|ddgddfn|gddf}ntd ||r|j dkr| ddddn| ddd}ttj|jjd }t|jjd|jjd }t|||S) zConverts the image to BGR.rBrrCrDrENrZ.z-Unsupported source color space for to_bgr(): rFrH)r(rGr'r rPr)rr r#rJrKrIrMrNr[rLrRrr&rr r)r*rTrrUrgb_datarVrWrXr,r,r-to_bgrs$ (  2 2( z Image.to_bgr np_ndarrayrGr rcCs|tjkrt|jd|jdd}|jd}n|tjkr.t|jd|jdd}|jd}ntdt||jdd}t|||d}|t |||S) aVConstruct an image tensor from a numpy array. Args: data: a numpy array containing the image data. color_space: the color space of the image. pixel_format: the pixel format of the image. channels_order: what dimension the channels are in the image tensor. Example: >>> data = np.ones((4, 5, 3), dtype=np.uint8) # HxWxC >>> img = Image.from_numpy(data, color_space=ColorSpace.RGB) >>> assert img.channels == 3 >>> assert img.width == 5 >>> assert img.height == 4 rrDr!r"rEzAchannels_order must be either `CHANNELS_LAST` or `CHANNELS_FIRST`rrFr rr) r r#rr+rrRritemsizerr4 from_numpy)clsrrGrr rrrr,r,r-rcs    zImage.from_numpycCs|jS)z2Return a numpy array in cpu from the image tensor.)rcpudetachnumpyr/r,r,r-to_numpy<szImage.to_numpyDLPackcCsTt|}ttj|dd}tt|jd|jdd|jdtj d}||||S)zConstruct an image tensor from a DLPack capsule. Args: data: a DLPack capsule from numpy, tvm or jax. Example: >>> x = np.ones((4, 5, 3)) >>> img = Image.from_dlpack(x.__dlpack__()) rrFrDrEr`rra) rrr rLr%rrr+r r)rdrr'rrr,r,r-r@s  zImage.from_dlpackcCs t|jS)z.Return a DLPack capsule from the image tensor.)rrr/r,r,r-rYs zImage.to_dlpack file_path str | PathcCs\t|tjdd}ttj|dd}tt|j d|j dd|j dt j d }||||S) zConstruct an image tensor from a file. Args: file_path: the path to the file to read the image from. re) desired_typer1rrFrDrEr`rra) rrRGB8rr rLr%rrr+r r)rdrjrrrr,r,r- from_file]s  zImage.from_filecCs.|j}|jtjkr|ddd}t||dS)aUWrite the image to a file. For now, only support writing to JPEG format. Args: file_path: the path to the file to write the image to. Example: >>> data = np.ones((4, 5, 3), dtype=np.uint8) # HxWxC >>> img = Image.from_numpy(data) >>> img.write("test.jpg") rErrDN)rrr r#rKr)r*rjrr,r,r-writeqs z Image.write max_widthcCstt|j|dS)a=Print the image tensor to the console. Args: max_width: the maximum width of the image to print. .. code-block:: python img = Image.from_file("panda.png") img.print() .. image:: https://github.com/kornia/data/blob/main/print_image.png?raw=true N)printrr)r*rqr,r,r-rrsz Image.print)rr rrrrrr)rr)NN)r1rr2rrr)rr)rr )rr9)rr<)rr=)rr)rr)rr>)rr)rr )rr_rGr rr rr)rr_)rrirr)rri)rjrkrr)rjrkrr)rp)rqr>rr)$__name__ __module__ __qualname____doc__r.r0r5r6propertyrr+r2r1rrrr r!r"rrArYr\r^ classmethodr rLr r#rcrhrrrnrorrr,r,r,r-r&sX (                  (    r)" __future__rpathlibrtypingrr4torch.utils.dlpackrr kornia.colorrM kornia.corerrr kornia.core.checkr r kornia.image.baser r rrr kornia.io.iorrrkornia.utils.image_printrr_rirr,r,r,r-s