khT$ddlmZddlmZmZddlmZddlZddlm Z ddl m Z  e dGd d eZd edej"fdZdedej"ddfdZej(dfdej"dededej"fdZd(dej"dedej"fdZd(dej"dedefdZej(ddfdeej"eej"fdedeeej4fdedeej"eej"ff dZ d)deej"eej"fdedeej"eej"ffdZd)dej"dedefd Zej(dfdeej"efdededej"fd!Zej(dfd edededej"fd"Zdej"dej"fd#Z ej(fdej"dedej"fd$Z!da"d%Z#ej(fdej"dedej"fd&Z$ej(fdej"dedej"fd'Z%y#e e f$rZed ed YdZ[\dZ[wwxYw)*)Enum)ListUnion)warnN) _load_library)_log_api_usage_onceimagez(Failed to load image Python extension: 'z'If you don't plan on using image functionality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torchvision` from source?c(eZdZdZdZdZdZdZdZeZ y) ImageReadModeaAllow automatic conversion to RGB, RGBA, etc while decoding. .. note:: You don't need to use this struct, you can just pass strings to all ``mode`` parameters, e.g. ``mode="RGB"``. The different available modes are the following. - UNCHANGED: loads the image as-is - RGB: converts to RGB - RGBA: converts to RGB with transparency (also aliased as RGB_ALPHA) - GRAY: converts to grayscale - GRAY_ALPHA: converts to grayscale with transparency .. note:: Some decoders won't support all possible values, e.g. GRAY and GRAY_ALPHA are only supported for PNG and JPEG images. rrN) __name__ __module__ __qualname____doc__ UNCHANGEDGRAY GRAY_ALPHARGB RGB_ALPHARGBAP/var/www/teggl/fontify/venv/lib/python3.12/site-packages/torchvision/io/image.pyr r s'*I DJ CI Drr pathreturnctjjs-tjjst t tj jj t|}|S)z Return the bytes contents of a file as a uint8 1D Tensor. Args: path (str or ``pathlib.Path``): the path to the file to be read Returns: data (Tensor) ) torchjit is_scripting is_tracingr read_fileopsr str)rdatas rr$r$4sL 99 ! ! #EII,@,@,BI& 99?? $ $SY /D Krfilenamer'ctjjs-tjjst t tj jj t||y)z Write the content of an uint8 1D tensor to a file. Args: filename (str or ``pathlib.Path``): the path to the file to be written data (Tensor): the contents to be written to the output file N) r r!r"r#r write_filer%r r&)r(r's rr*r*DsG 99 ! ! #EII,@,@,BJ' IIOOs8}d3rFinputmodeapply_exif_orientationcTtjjs-tjjst t t |trt|j}tjjj ||j|}|S)a Decodes a PNG image into a 3 dimensional RGB or grayscale Tensor. The values of the output tensor are in uint8 in [0, 255] for most cases. If the image is a 16-bit png, then the output tensor is uint16 in [0, 65535] (supported from torchvision ``0.21``). Since uint16 support is limited in pytorch, we recommend calling :func:`torchvision.transforms.v2.functional.to_dtype()` with ``scale=True`` after this function to convert the decoded image into a uint8 or float tensor. Args: input (Tensor[1]): a one dimensional uint8 tensor containing the raw bytes of the PNG image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. apply_exif_orientation (bool): apply EXIF orientation transformation to the output tensor. Default: False. Returns: output (Tensor[image_channels, image_height, image_width]) ) r r!r"r#r decode_png isinstancer&r upperr%r valuer+r,r-outputs rr/r/Qsk8 99 ! ! #EII,@,@,BJ'$TZZ\* YY__ ' 'tzz;Q RF Mrcompression_levelctjjs-tjjst t tj jj ||}|S)a  Takes an input tensor in CHW layout and returns a buffer with the contents of its corresponding PNG file. Args: input (Tensor[channels, image_height, image_width]): int8 image tensor of ``c`` channels, where ``c`` must 3 or 1. compression_level (int): Compression factor for the resulting file, it must be a number between 0 and 9. Default: 6 Returns: Tensor[1]: A one dimensional int8 tensor that contains the raw bytes of the PNG file. )r r!r"r#r encode_pngr%r )r+r5r4s rr7r7usK 99 ! ! #EII,@,@,BJ' YY__ ' '/@ AF Mrctjjs-tjjst t t ||}t||y)a Takes an input tensor in CHW layout (or HW in the case of grayscale images) and saves it in a PNG file. Args: input (Tensor[channels, image_height, image_width]): int8 image tensor of ``c`` channels, where ``c`` must be 1 or 3. filename (str or ``pathlib.Path``): Path to save the image. compression_level (int): Compression factor for the resulting file, it must be a number between 0 and 9. Default: 6 N)r r!r"r#r write_pngr7r*)r+r(r5r4s rr9r9sB 99 ! ! #EII,@,@,BI& 0 1Fx rcpudevicecPtjjs-tjjst t t |trtj|}t |trt|j}t |trt|dk(r tdtd|Ds tdtd|Ds td|jdk(r5tj j"j%||j&|S|Dcgc]7}tj j"j ||j&|9c}S|jjdk7r td |jdk(r9tj j"j%|g|j&|dStj j"j ||j&|Scc}w) aDecode JPEG image(s) into 3D RGB or grayscale Tensor(s), on CPU or CUDA. The values of the output tensor are uint8 between 0 and 255. .. note:: When using a CUDA device, passing a list of tensors is more efficient than repeated individual calls to ``decode_jpeg``. When using CPU the performance is equivalent. The CUDA version of this function has explicitly been designed with thread-safety in mind. This function does not return partial results in case of an error. Args: input (Tensor[1] or list[Tensor[1]]): a (list of) one dimensional uint8 tensor(s) containing the raw bytes of the JPEG image. The tensor(s) must be on CPU, regardless of the ``device`` parameter. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. device (str or torch.device): The device on which the decoded image will be stored. If a cuda device is specified, the image will be decoded with `nvjpeg `_. This is only supported for CUDA version >= 10.1 .. betastatus:: device parameter .. warning:: There is a memory leak in the nvjpeg library for CUDA versions < 11.6. Make sure to rely on CUDA 11.6 or above before using ``device="cuda"``. apply_exif_orientation (bool): apply EXIF orientation transformation to the output tensor. Default: False. Only implemented for JPEG format on CPU. Returns: output (Tensor[image_channels, image_height, image_width] or list[Tensor[image_channels, image_height, image_width]]): The values of the output tensor(s) are uint8 between 0 and 255. ``output.device`` will be set to the specified ``device`` rz,Input list must contain at least one elementc3PK|]}t|tj yw)N)r0r Tensor.0ts r zdecode_jpeg..s>1:a.>s$&z/All elements of the input list must be tensors.c3NK|]}|jjdk(yw)r:N)r;typer?s rrBzdecode_jpeg..s9a188==E)9s#%z'Input list must contain tensors on CPU.cudar:z!Input tensor must be a CPU tensor)r r!r"r#r decode_jpegr0r&r;r r1listlen ValueErrorallrDr%r decode_jpegs_cudar2)r+r,r;r-imgs rrFrFsV 99 ! ! #EII,@,@,BK(&#f%$TZZ\*% u:?KL L>>>NO O9599FG G ;;& 99??44UDJJO Odij]`EIIOO//TZZAWXj j <<   %@A A ;;& 99??44eWdjj&QRST T99??..udjjBXY Yks > Ts1E-ctjjs-tjjst t t ||}t|tjsJt||y)a Takes an input tensor in CHW layout and saves it in a JPEG file. Args: input (Tensor[channels, image_height, image_width]): int8 image tensor of ``c`` channels, where ``c`` must be 1 or 3. filename (str or ``pathlib.Path``): Path to save the image. quality (int): Quality of the resulting JPEG file, it must be a number between 1 and 100. Default: 75 N) r r!r"r#r write_jpegrPr0r>r*)r+r(rMr4s rrSrSsU 99 ! ! #EII,@,@,BJ'  (F fell ++ +x rctjjs-tjjst t t |tjstt|}t |trt|j}tjjj ||j|}|S)aDecode an image into a uint8 tensor, from a path or from raw encoded bytes. Currently supported image formats are jpeg, png, gif and webp. The values of the output tensor are in uint8 in [0, 255] for most cases. If the image is a 16-bit png, then the output tensor is uint16 in [0, 65535] (supported from torchvision ``0.21``). Since uint16 support is limited in pytorch, we recommend calling :func:`torchvision.transforms.v2.functional.to_dtype()` with ``scale=True`` after this function to convert the decoded image into a uint8 or float tensor. .. note:: ``decode_image()`` doesn't work yet on AVIF or HEIC images. For these formats, directly call :func:`~torchvision.io.decode_avif` or :func:`~torchvision.io.decode_heic`. Args: input (Tensor or str or ``pathlib.Path``): The image to decode. If a tensor is passed, it must be one dimensional uint8 tensor containing the raw bytes of the image. Otherwise, this must be a path to the image file. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. apply_exif_orientation (bool): apply EXIF orientation transformation to the output tensor. Only applies to JPEG and PNG images. Default: False. Returns: output (Tensor[image_channels, image_height, image_width]) )r r!r"r#r decode_imager0r>r$r&r r1r%r r2r3s rrUrUsJ 99 ! ! #EII,@,@,BL) eU\\ *#e*%$TZZ\* YY__ ) )%=S TF Mrctjjs-tjjst t t |}t|||S)z<[OBSOLETE] Use :func:`~torchvision.io.decode_image` instead.)r-)r r!r"r#r read_imager$rU)rr,r-r's rrWrWHsD 99 ! ! #EII,@,@,BJ' T?D d;Q RRrctjjs-tjjst t tj jj |S)a& Decode a GIF image into a 3 or 4 dimensional RGB Tensor. The values of the output tensor are uint8 between 0 and 255. The output tensor has shape ``(C, H, W)`` if there is only one image in the GIF, and ``(N, C, H, W)`` if there are ``N`` images. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the GIF image. Returns: output (Tensor[image_channels, image_height, image_width] or Tensor[num_images, image_channels, image_height, image_width]) )r r!r"r#r decode_gifr%r )r+s rrYrYTsD 99 ! ! #EII,@,@,BJ' 99?? % %e ,,rcNtjjs-tjjst t t |trt|j}tjjj ||jS)a' Decode a WEBP image into a 3 dimensional RGB[A] Tensor. The values of the output tensor are uint8 between 0 and 255. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the WEBP image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. Returns: Decoded image (Tensor[image_channels, image_height, image_width]) ) r r!r"r#r decode_webpr0r&r r1r%r r2r+r,s rr[r[hsd& 99 ! ! #EII,@,@,BK($TZZ\* 99?? & &udjj 99rctry ddl}t|dsJ |j day#ttf$r}t d|d}~wwxYw)Nrexpose_extra_decodersaIn order to enable the AVIF and HEIC decoding capabilities of torchvision, you need to `pip install torchvision-extra-decoders`. Just install the package, you don't need to update your code. This is only supported on Linux, and this feature is still in BETA stage. Please let us know of any issue: https://github.com/pytorch/vision/issues/new/choose. Note that `torchvision-extra-decoders` is released under the LGPL license. T)_EXTRA_DECODERS_ALREADY_LOADEDtorchvision_extra_decodershasattrAssertionError ImportError RuntimeErrorr^)r`es r_load_extra_decoders_oncerfsg%)13JKKK446%)" K ( Z  s/A A  Act|jtjk7rt d|jtj j j||jS)aDecode an AVIF image into a 3 dimensional RGB[A] Tensor. .. warning:: In order to enable the AVIF decoding capabilities of torchvision, you first need to run ``pip install torchvision-extra-decoders``. Just install the package, you don't need to update your code. This is only supported on Linux, and this feature is still in BETA stage. Please let us know of any issue: https://github.com/pytorch/vision/issues/new/choose. Note that `torchvision-extra-decoders `_ is released under the LGPL license. The values of the output tensor are in uint8 in [0, 255] for most images. If the image has a bit-depth of more than 8, then the output tensor is uint16 in [0, 65535]. Since uint16 support is limited in pytorch, we recommend calling :func:`torchvision.transforms.v2.functional.to_dtype()` with ``scale=True`` after this function to convert the decoded image into a uint8 or float tensor. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the AVIF image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. Returns: Decoded image (Tensor[image_channels, image_height, image_width]) ,Input tensor must have uint8 data type, got ) rfdtyper uint8rdr%extra_decoders_ns decode_avifr2r\s rrlrlR> {{ekk!I%++WXX 99 & & 2 25$** EErct|jtjk7rt d|jtj j j||jS)aDecode an HEIC image into a 3 dimensional RGB[A] Tensor. .. warning:: In order to enable the AVIF decoding capabilities of torchvision, you first need to run ``pip install torchvision-extra-decoders``. Just install the package, you don't need to update your code. This is only supported on Linux, and this feature is still in BETA stage. Please let us know of any issue: https://github.com/pytorch/vision/issues/new/choose. Note that `torchvision-extra-decoders `_ is released under the LGPL license. The values of the output tensor are in uint8 in [0, 255] for most images. If the image has a bit-depth of more than 8, then the output tensor is uint16 in [0, 65535]. Since uint16 support is limited in pytorch, we recommend calling :func:`torchvision.transforms.v2.functional.to_dtype()` with ``scale=True`` after this function to convert the decoded image into a uint8 or float tensor. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the HEIC image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. Returns: Decoded image (Tensor[image_channels, image_height, image_width]) rh) rfrir rjrdr%rk decode_heicr2r\s rrorormr))K)&enumrtypingrrwarningsrr extensionrutilsr rcOSErrorrer r&r>r$r*rboolr/intr7r9r;rFrPrSrUrWrYr[r_rfrlrorrrrzsl %''D< C ELL  4 4ELL 4T 4(11#(! <<! !!! \\ !Hells5<<*!U\\!S!S!((11',#( DZ tELL11 2DZ DZ #u||# $DZ! DZ  5<<ell+ +, DZPDF!? tELL11 2!?=@!? 5<<ell+ +,!?H!ell!c!C!((11#(, s" #, ,!, \\ ,b(11#( S  S  S! S \\ S-ell-u||-,(11: <<: : \\:Z"'*@