rhBdZddlmZmZddlZddlmZmZm Z ddl m Z m Z m Z ddlmZmZmZmZmZmZmZmZmZmZddlmZmZmZdd lmZmZej@e!Z"Gd d eZ#d gZ$y) z{ Image processor class for InstructBLIPVideo. Largely copy of Blip2Processor with addition of a video processing abilities )OptionalUnionN)BaseImageProcessor BatchFeature get_size_dict)convert_to_rgbresizeto_channel_dimension_format) OPENAI_CLIP_MEANOPENAI_CLIP_STDChannelDimension ImageInputPILImageResamplinginfer_channel_dimension_formatis_scaled_imageto_numpy_array valid_imagesvalidate_preprocess_arguments) TensorTypefilter_out_non_signature_kwargslogging) VideoInputmake_batched_videosc4eZdZdZdgZddej ddddddf dedee e e fded ed e e e fd ed ee e ee fd ee e ee fdeddffd Zej ddfdej"de e e fdedee e efdee e efdej"f dZedddddddddddej*df dedeedee e e fded eed ee d eed ee e ee fd ee e ee fdee e efdeededee e efdefdZddddddddddej*df dedeedee e e fded eed ee d eed ee e ee fd ee e ee fdeededee e efdej"fdZxZS)InstructBlipVideoImageProcessora Constructs a InstructBLIPVideo image processor. Args: do_resize (`bool`, *optional*, defaults to `True`): Whether to resize the image's (height, width) dimensions to the specified `size`. Can be overridden by the `do_resize` parameter in the `preprocess` method. size (`dict`, *optional*, defaults to `{"height": 384, "width": 384}`): Size of the output image after resizing. Can be overridden by the `size` parameter in the `preprocess` method. resample (`PILImageResampling`, *optional*, defaults to `Resampling.BICUBIC`): Resampling filter to use if resizing the image. Only has an effect if `do_resize` is set to `True`. Can be overridden by the `resample` parameter in the `preprocess` method. do_rescale (`bool`, *optional*, defaults to `True`): Whether to rescale the image by the specified scale `rescale_factor`. Can be overridden by the `do_rescale` parameter in the `preprocess` method. rescale_factor (`int` or `float`, *optional*, defaults to `1/255`): Scale factor to use if rescaling the image. Only has an effect if `do_rescale` is set to `True`. Can be overridden by the `rescale_factor` parameter in the `preprocess` method. do_normalize (`bool`, *optional*, defaults to `True`): Whether to normalize the image. Can be overridden by the `do_normalize` parameter in the `preprocess` method. Can be overridden by the `do_normalize` parameter in the `preprocess` method. image_mean (`float` or `list[float]`, *optional*, defaults to `IMAGENET_STANDARD_MEAN`): Mean to use if normalizing the image. This is a float or list of floats the length of the number of channels in the image. Can be overridden by the `image_mean` parameter in the `preprocess` method. Can be overridden by the `image_mean` parameter in the `preprocess` method. image_std (`float` or `list[float]`, *optional*, defaults to `IMAGENET_STANDARD_STD`): Standard deviation to use if normalizing the image. This is a float or list of floats the length of the number of channels in the image. Can be overridden by the `image_std` parameter in the `preprocess` method. Can be overridden by the `image_std` parameter in the `preprocess` method. do_convert_rgb (`bool`, *optional*, defaults to `True`): Whether to convert the image to RGB. pixel_valuesTNgp? do_resizesizeresample do_rescalerescale_factor do_normalize image_mean image_stddo_convert_rgbreturnc  t |di| ||nddd}t|d}||_||_||_||_||_||_||nt|_ ||nt|_ | |_ y)Ni)heightwidthTdefault_to_square)super__init__rrrr r!r"r#r r$r r%r&) selfrrr r!r"r#r$r%r&kwargs __class__s /var/www/html/ai-insurance-compliance-backend/venv/lib/python3.12/site-packages/transformers/models/instructblipvideo/image_processing_instructblipvideo.pyr/z(InstructBlipVideoImageProcessor.__init__Ts "6"'tc-JTT:"   $,((2(>*DT&/&;,image data_formatinput_data_formatc t|}d|vsd|vrtd|j|d|df}t|f||||d|S)a Resize an image to `(size["height"], size["width"])`. Args: image (`np.ndarray`): Image to resize. size (`dict[str, int]`): Dictionary in the format `{"height": int, "width": int}` specifying the size of the output image. resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`): `PILImageResampling` filter to use when resizing the image e.g. `PILImageResampling.BICUBIC`. data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format for the output image. If unset, the channel dimension format of the input image is used. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. - `"none"` or `ChannelDimension.NONE`: image in (height, width) format. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format for the input image. If unset, the channel dimension format is inferred from the input image. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. - `"none"` or `ChannelDimension.NONE`: image in (height, width) format. Returns: `np.ndarray`: The resized image. r)r*zFThe `size` dictionary must contain the keys `height` and `width`. Got )rr r6r7)r ValueErrorkeysr )r0r5rr r6r7r1 output_sizes r3r z&InstructBlipVideoImageProcessor.resizepsyFT" 4 7$#6efjfofofqerst tH~tG}5   #/     r4imagesreturn_tensorscz||n |j}||n |j}||n |j}||n |j}||n |j}||n |j }| | n |j } | | n |j} ||n |j}t|d}t|}tjdt||||| |||t|s td|Dcgc]-}|Dcgc]}|j!||||||||| | | |  !c}/}}}t#d|i| }|Scc}wcc}}w) a Preprocess a video or batch of images/videos. Args: videos (`VideoInput`): Video frames to preprocess. Expects a single or batch of videos as a list of frames with pixel values ranging from 0 to 255. If passing in video with pixel values between 0 and 1, set `do_rescale=False`. do_resize (`bool`, *optional*, defaults to `self.do_resize`): Whether to resize the video. size (`dict[str, int]`, *optional*, defaults to `self.size`): Controls the size of the video after `resize`. The shortest edge of the image is resized to `size["shortest_edge"]` whilst preserving the aspect ratio. If the longest edge of this resized image is > `int(size["shortest_edge"] * (1333 / 800))`, then the image is resized again to make the longest edge equal to `int(size["shortest_edge"] * (1333 / 800))`. resample (`PILImageResampling`, *optional*, defaults to `self.resample`): Resampling filter to use if resizing the video. Only has an effect if `do_resize` is set to `True`. do_rescale (`bool`, *optional*, defaults to `self.do_rescale`): Whether to rescale the video values between [0 - 1]. rescale_factor (`float`, *optional*, defaults to `self.rescale_factor`): Rescale factor to rescale the video by if `do_rescale` is set to `True`. do_normalize (`bool`, *optional*, defaults to `self.do_normalize`): Whether to normalize the video. image_mean (`float` or `list[float]`, *optional*, defaults to `self.image_mean`): Image mean to normalize the video by if `do_normalize` is set to `True`. image_std (`float` or `list[float]`, *optional*, defaults to `self.image_std`): Image standard deviation to normalize the video by if `do_normalize` is set to `True`. do_convert_rgb (`bool`, *optional*, defaults to `self.do_convert_rgb`): Whether to convert the image to RGB. return_tensors (`str` or `TensorType`, *optional*): The type of tensors to return. Can be one of: - Unset: Return a list of `np.ndarray`. - `TensorType.TENSORFLOW` or `'tf'`: Return a batch of type `tf.Tensor`. - `TensorType.PYTORCH` or `'pt'`: Return a batch of type `torch.Tensor`. - `TensorType.NUMPY` or `'np'`: Return a batch of type `np.ndarray`. - `TensorType.JAX` or `'jax'`: Return a batch of type `jax.numpy.ndarray`. data_format (`ChannelDimension` or `str`, *optional*, defaults to `ChannelDimension.FIRST`): The channel dimension format for the output image. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. - Unset: Use the channel dimension format of the input image. input_data_format (`ChannelDimension` or `str`, *optional*): The channel dimension format for the input image. If unset, the channel dimension format is inferred from the input image. Can be one of: - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format. - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format. - `"none"` or `ChannelDimension.NONE`: image in (height, width) format. Fr+z`InstructBlipVideoImageProcessor` is deprecated and will be removed in v5.0. We recommend to load an instance of `InstructBlipVideoVideoProcessor` to process videos for the model. )r!r"r#r$r%rrr zkInvalid input type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.) r5rrr r!r"r#r$r%r&r6r7r)data tensor_type)rr r!r"r#r$r%r&rrrloggerwarningrrr9_preprocess_imager)r0r<rrr r!r"r#r$r%r=r&r6r7videosvideoframerencoded_outputss r3 preprocessz*InstructBlipVideoImageProcessor.preprocesss@"+!6IDNN '38#-#9Zt +9+E4K^K^'3'?|TEVEV #-#9Zt !*!6IDNN +9+E4K^K^'tTYYTU;$V, v &!)%! F#: . % $# &&'%)#1!-)'#1 +&7'    *'^\,JXfg+  s, D75$D2 D72D7c 8| r t|}t|}|r t|rtj d| t |} |r|j |||| }|r|j||| }|r|j||| | }t|| | }|S)NzIt looks like you are trying to rescale already rescaled video frames. If the input images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again.)r5rr r7)r5scaler7)r5meanstdr7)input_channel_dim) r rrrA warning_oncerr rescale normalizer ) r0r5rrr r!r"r#r$r%r&r6r7s r3rCz1InstructBlipVideoImageProcessor._preprocess_images "5)Eu% /%0   s   $ >u E  KKe$]nKoE LLuNVgLhE NNZYbsNtE+E;Rcd r4)__name__ __module__ __qualname____doc__model_input_namesrBICUBICboolrdictstrintrfloatlistr/npndarrayrr rFIRSTrrrrHrrC __classcell__)r2s@r3rr/s D(()-'9'A'A,3!:>9=#--tCH~&-% -  - c5j) --U5$u+#567-E%e"456-- -@(:'A'A>BDH / zz/ 38n/ % / eC)9$9:; / $E#/?*?$@A /  / d%&"$()-'+%)*.'+:>9=;?)-(8(>(>DHxxD>xtCH~& x % x TN x!xtnxU5$u+#567xE%e"456x!sJ!78x!x&x$E#/?*?$@Ax x'xz!$()-'+%)*.'+:>9=)-(8(>(>DH++D>+tCH~& + % + TN +!+tn+U5$u+#567+E%e"456+!+&+$E#/?*?$@A+ +r4r)%rTtypingrrnumpyr]image_processing_utilsrrrimage_transformsr r r image_utilsr r rrrrrrrrutilsrrr video_utilsrr get_loggerrQrAr__all__r-r4r3rjsg #UUSS   JI:   H % Z&8Zz - -r4