ڧg2E ddlmZddlmZmZddlmZddlZddlm Z ddl m Z  e dn##e e f$rZed ed YdZ[ndZ[wwxYwGd d eZd edejfdZdedejddfdZejdfdejdededejfdZd)dejdedejfdZd)dejdedefdZejddfdeejeejfdedeeejfdedeejeejff dZ d*deejeejfd edeejeejffd!Zd*dejded efd"Zejdfdeejefdededejfd#Zejdfd edededejfd$Zdejdejfd%Z ejfdejdedejfd&Z!ejfdejdedejfd'Z"ejfdejdedejfd(Z#dS)+)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 dS) 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/html/ai-engine/env/lib/python3.11/site-packages/torchvision/io/image.pyr r s8*I DJ CI DDDrr pathreturnctjs2tjst t tjjt|}|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$4s_ 9 ! ! # #'EI,@,@,B,B'I&&& 9? $ $SYY / /D Krfilenamer'c tjs2tjst t tjjt||dS)z Write the content of an uint8 1D tensor to a file. Args: filename (str or ``pathlib.Path``): the path to the file to be written data (Tensor): the contents to be written to the output file N) r r!r"r#r write_filer%r r&)r(r's rr*r*Dsc 9 ! ! # #(EI,@,@,B,B(J''' IOs8}}d33333rFinputmodeapply_exif_orientationcdtjs2tjst t t |trt| }tj j ||j |}|S)a Decodes a PNG image into a 3 dimensional RGB or grayscale Tensor. The values of the output tensor are in uint8 in [0, 255] for most cases. If the image is a 16-bit png, then the output tensor is uint16 in [0, 65535] (supported from torchvision ``0.21``). Since uint16 support is limited in pytorch, we recommend calling :func:`torchvision.transforms.v2.functional.to_dtype()` with ``scale=True`` after this function to convert the decoded image into a uint8 or float tensor. Args: input (Tensor[1]): a one dimensional uint8 tensor containing the raw bytes of the PNG image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. apply_exif_orientation (bool): apply EXIF orientation transformation to the output tensor. Default: False. Returns: output (Tensor[image_channels, image_height, image_width]) ) r r!r"r#r decode_png isinstancer&r upperr%r valuer+r,r-outputs rr/r/Qs8 9 ! ! # #(EI,@,@,B,B(J'''$+TZZ\\* Y_ ' 'tz;Q R RF Mrcompression_levelctjs2tjst t tjj||}|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+r6r4s rr8r8us\ 9 ! ! # #(EI,@,@,B,B(J''' Y_ ' '/@ A AF Mrctjs2tjst t t ||}t||dS)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_pngr8r*)r+r(r6r4s rr:r:sc 9 ! ! # #'EI,@,@,B,B'I&&& 0 1 1Fx     rcpudevicectjs2tjst t t |trtj|}t trt t |trt|dkrtdtd|Dstdtd|Dstd|jdkr+tjj|j|Sfd|DS|jjd krtd |jdkr2tjj|gj|dStjj|jS) 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 elementc3JK|]}t|tjVdS)N)r0r Tensor.0ts r zdecode_jpeg..s.>>1:a..>>>>>>rz/All elements of the input list must be tensors.c36K|]}|jjdkVdS)r;N)r<typer@s rrCzdecode_jpeg..s+99a18=E)999999rz'Input list must contain tensors on CPU.cudacfg|]-}tjj|j.Sr)r r%r decode_jpegr2)rAimgr-r,s r zdecode_jpeg..s3jjj]`EIO//TZAWXXjjjrr;z!Input tensor must be a CPU tensor)r r!r"r#r rHr0r&r<r r1listlen ValueErrorallrEr%r decode_jpegs_cudar2)r+r,r<r-s ` `rrHrHsV 9 ! ! # #)EI,@,@,B,B)K(((&#&f%%$+TZZ\\*%Z u::??KLL L>>>>>>> PNOO O99599999 HFGG G ;& 9?44UDJOO Ojjjjjdijjj j <  % %@AA A ;& 9?44eWdj&QQRST T9?..udjBXYY YrKqualitycztjs2tjst t dksdkrt dt|trZ|st d|dj j dkr%tj j |Sfd|DS|j j dkr,tj j |gdStj j |S)aEncode RGB tensor(s) into raw encoded jpeg bytes, on CPU or CUDA. .. note:: Passing a list of CUDA tensors is more efficient than repeated individual calls to ``encode_jpeg``. For CPU tensors the performance is equivalent. Args: input (Tensor[channels, image_height, image_width] or List[Tensor[channels, image_height, image_width]]): (list of) uint8 image tensor(s) of ``c`` channels, where ``c`` must be 1 or 3 quality (int): Quality of the resulting JPEG file(s). Must be a number between 1 and 100. Default: 75 Returns: output (Tensor[1] or list[Tensor[1]]): A (list of) one dimensional uint8 tensor(s) that contain the raw bytes of the JPEG file. r dz;Image quality should be a positive number between 1 and 100zDencode_jpeg requires at least one input tensor when a list is passedrrFcZg|]'}tjj|(Sr)r r%r encode_jpeg)rAr rQs rrJzencode_jpeg..s-SSSEEIO//w??SSSr)r r!r"r#r rUrMr0rKr<rEr%r encode_jpegs_cuda)r+rQs `rrUrUs$ 9 ! ! # #)EI,@,@,B,B)K((({{gmmVWWW% ? ecdd d 8? 6 ) )9?44UGDD DSSSSUSSS S <  & &9?44eWgFFqI I9?..ug>> >rctjs2tjst t t ||}t|tjsJt||dS)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_jpegrUr0r?r*)r+r(rQr4s rrXrXsz 9 ! ! # #(EI,@,@,B,B(J'''  ( (F fel + ++++x     rctjs2tjst t t |tjstt|}t |trt| }tj j ||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. 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$r&r r1r%r r2r3s rrZrZs> 9 ! ! # #*EI,@,@,B,B*L))) eU\ * *&#e**%%$+TZZ\\* Y_ ) )%=S T TF Mrctjs2tjst t t |}t|||S)z<[OBSOLETE] Use :func:`~torchvision.io.decode_image` instead.)r-)r r!r"r#r read_imager$rZ)rr,r-r's rr\r\Bs^ 9 ! ! # #(EI,@,@,B,B(J''' T??D d;Q R R RRrctjs2tjst t tjj|S)a& Decode a GIF image into a 3 or 4 dimensional RGB Tensor. The values of the output tensor are uint8 between 0 and 255. The output tensor has shape ``(C, H, W)`` if there is only one image in the GIF, and ``(N, C, H, W)`` if there are ``N`` images. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the GIF image. Returns: output (Tensor[image_channels, image_height, image_width] or Tensor[num_images, image_channels, image_height, image_width]) )r r!r"r#r decode_gifr%r )r+s rr^r^NsU 9 ! ! # #(EI,@,@,B,B(J''' 9? % %e , ,,rc^tjs2tjst t t |trt| }tj j ||j S)a' Decode a WEBP image into a 3 dimensional RGB[A] Tensor. The values of the output tensor are uint8 between 0 and 255. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the WEBP image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. Returns: Decoded image (Tensor[image_channels, image_height, image_width]) ) r r!r"r#r decode_webpr0r&r r1r%r r2r+r,s rr`r`bs}& 9 ! ! # #)EI,@,@,B,B)K((($+TZZ\\* 9? & &udj 9 99rc^tjs2tjst t t |trt| }tj j ||j S)a Decode an AVIF image into a 3 dimensional RGB[A] Tensor. 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]) )r r!r"r#r _decode_avifr0r&r r1r%r decode_avifr2ras rrcrc|s}0 9 ! ! # #*EI,@,@,B,B*L)))$+TZZ\\* 9? & &udj 9 99rc^tjs2tjst t t |trt| }tj j ||j S)a Decode an HEIC image into a 3 dimensional RGB[A] Tensor. The values of the output tensor are in uint8 in [0, 255] for most images. If the image has a bit-depth of more than 8, then the output tensor is uint16 in [0, 65535]. Since uint16 support is limited in pytorch, we recommend calling :func:`torchvision.transforms.v2.functional.to_dtype()` with ``scale=True`` after this function to convert the decoded image into a uint8 or float tensor. Args: input (Tensor[1]): a one dimensional contiguous uint8 tensor containing the raw bytes of the HEIC image. mode (str or ImageReadMode): The mode to convert the image to, e.g. "RGB". Default is "UNCHANGED". See :class:`~torchvision.io.ImageReadMode` for available modes. Returns: Decoded image (Tensor[image_channels, image_height, image_width]) )r r!r"r#r _decode_heicr0r&r r1r%r decode_heicr2ras rrfrfs}* 9 ! ! # #*EI,@,@,B,B*L)))$+TZZ\\* 9? & &udj 9 99r)r5)rP)$enumrtypingrrwarningsrr extensionrutilsr ImportErrorOSErrorer r&r?r$r*rboolr/intr8r:r<rHrUrXrZr\r^r`rcrfrrrrrs %%%%%%''''''M'WD c1 c c cD< C EL     4 4EL 4T 4 4 4 4(1#(!! <! !!! \ !!!!Hels5<*!!U\!S!S!!!!((1',#( DZDZ tEL11 2DZ DZ #u|# $DZ! DZ  5<el+ +, DZDZDZDZPDF!?!? tEL11 2!?=@!? 5<el+ +,!?!?!?!?H!!el!c!C!!!!((1#(&& s" #& &!& \ &&&&V(1#( S S  S  S! S \ S S S S-el-u|----,(1:: <: : \::::8(1:: <: : \::::>=J