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@ -156,8 +156,8 @@ class LlavaNextImageProcessor(BaseImageProcessor):
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number of channels in the image. Can be overridden by the `image_std` parameter in the `preprocess` method.
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Can be overridden by the `image_std` parameter in the `preprocess` method.
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do_pad (`bool`, *optional*, defaults to `True`):
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Whether to pad the image. If `True` will pad the images in the batch to the largest image in the batch
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and create a pixel mask. Padding will be applied to the bottom and right of the image with zeros.
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Whether to pad the image. If `True`, will pad the patch dimension of the images in the batch to the largest
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number of patches in the batch. Padding will be applied to the bottom and right with zeros.
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do_convert_rgb (`bool`, *optional*, defaults to `True`):
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Whether to convert the image to RGB.
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"""
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@ -203,6 +203,7 @@ class LlavaNextImageProcessor(BaseImageProcessor):
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self.do_normalize = do_normalize
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self.image_mean = image_mean if image_mean is not None else OPENAI_CLIP_MEAN
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self.image_std = image_std if image_std is not None else OPENAI_CLIP_STD
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self.do_pad = do_pad
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self.do_convert_rgb = do_convert_rgb
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# Copied from transformers.models.clip.image_processing_clip.CLIPImageProcessor.resize with CLIP->LLaVa
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@ -572,7 +573,7 @@ class LlavaNextImageProcessor(BaseImageProcessor):
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do_normalize: bool = None,
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image_mean: Optional[Union[float, List[float]]] = None,
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image_std: Optional[Union[float, List[float]]] = None,
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do_pad: Optional[bool] = True,
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do_pad: Optional[bool] = None,
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do_convert_rgb: bool = None,
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return_tensors: Optional[Union[str, TensorType]] = None,
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data_format: Optional[ChannelDimension] = ChannelDimension.FIRST,
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@ -609,9 +610,9 @@ class LlavaNextImageProcessor(BaseImageProcessor):
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image_std (`float` or `List[float]`, *optional*, defaults to `self.image_std`):
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Image standard deviation to use for normalization. Only has an effect if `do_normalize` is set to
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`True`.
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do_pad (`bool`, *optional*, defaults to self.do_pad):
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Whether to pad the image. If `True` will pad the images in the batch to the largest image in the batch
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and create a pixel mask. Padding will be applied to the bottom and right of the image with zeros.
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do_pad (`bool`, *optional*, defaults to `self.do_pad`):
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Whether to pad the image. If `True`, will pad the patch dimension of the images in the batch to the largest
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number of patches in the batch. Padding will be applied to the bottom and right with zeros.
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do_convert_rgb (`bool`, *optional*, defaults to `self.do_convert_rgb`):
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Whether to convert the image to RGB.
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return_tensors (`str` or `TensorType`, *optional*):
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@ -647,6 +648,7 @@ class LlavaNextImageProcessor(BaseImageProcessor):
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do_normalize = do_normalize if do_normalize is not None else self.do_normalize
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image_mean = image_mean if image_mean is not None else self.image_mean
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image_std = image_std if image_std is not None else self.image_std
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do_pad = do_pad if do_pad is not None else self.do_pad
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do_convert_rgb = do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb
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images = make_list_of_images(images)
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