gddlmZmZddlZddlmZmZmZm Z m Z ddl m Z m Z er ddlmZddlmZerdd lmZe jeZee d Gd d e ZdS))ListUnionN)add_end_docstringsis_torch_availableis_vision_availableloggingrequires_backends)Pipelinebuild_pipeline_init_args)Image) load_image)&MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMEST)has_image_processorceZdZdZfdZdZdeeeededfdededfffd Z dZ d d Z d Z xZ S) ImageToImagePipelineao Image to Image pipeline using any `AutoModelForImageToImage`. This pipeline generates an image based on a previous image input. Example: ```python >>> from PIL import Image >>> import requests >>> from transformers import pipeline >>> upscaler = pipeline("image-to-image", model="caidas/swin2SR-classical-sr-x2-64") >>> img = Image.open(requests.get("http://images.cocodataset.org/val2017/000000039769.jpg", stream=True).raw) >>> img = img.resize((64, 64)) >>> upscaled_img = upscaler(img) >>> img.size (64, 64) >>> upscaled_img.size (144, 144) ``` This image to image pipeline can currently be loaded from [`pipeline`] using the following task identifier: `"image-to-image"`. See the list of available models on [huggingface.co/models](https://huggingface.co/models?filter=image-to-image). ctj|i|t|d|tdS)Nvision)super__init__r check_model_typer)selfargskwargs __class__s a/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/pipelines/image_to_image.pyrzImageToImagePipeline.__init__FsJ$)&)))$))) DEEEEEc Ti}i}i}d|vr |d|d<d|vr |d|d<|||fS)Ntimeout head_mask)rrpreprocess_paramspostprocess_paramsforward_paramss r_sanitize_parametersz)ImageToImagePipeline._sanitize_parametersKsV   +1)+< i ( & *0*=N; ' .2DDDrimagesz Image.Imagereturnc 8tj|fi|S)a Transform the image(s) passed as inputs. Args: images (`str`, `List[str]`, `PIL.Image` or `List[PIL.Image]`): The pipeline handles three types of images: - A string containing a http link pointing to an image - A string containing a local path to an image - An image loaded in PIL directly The pipeline accepts either a single image or a batch of images, which must then be passed as a string. Images in a batch must all be in the same format: all as http links, all as local paths, or all as PIL images. timeout (`float`, *optional*, defaults to None): The maximum time in seconds to wait for fetching images from the web. If None, no timeout is used and the call may block forever. Return: An image (Image.Image) or a list of images (List["Image.Image"]) containing result(s). If the input is a single image, the return will be also a single image, if the input is a list of several images, it will return a list of transformed images. )r__call__)rr'rrs rr*zImageToImagePipeline.__call__Ws$4 uww11&111rc |jdi|}|S)Nr")model)r model_inputs model_outputss r_forwardzImageToImagePipeline._forwardss" 22\22 rNct||}||gd}|jdkr||j}|S)N)r pt)r'return_tensors)rimage_processor frameworkto torch_dtype)rimager inputss r preprocesszImageToImagePipeline.preprocesswsT5'222%%eWT%JJ >T ! !YYt/00F rc.g}d|vr|j}|D]}|jdd}tj |dd}|dz tj }| tj|t!|dkr|n|dS)Nreconstructionrr )source destinationgo@)keysr;datasqueezefloatcpuclamp_numpynpmoveaxisroundastypeuint8appendr fromarraylen)rr.r'outputsoutputs r postprocessz ImageToImagePipeline.postprocess~s }1133 3 3#2G 3 3F[((**00226688??1EEKKMMF[rBBBFun++--44RX>>F MM%/&11 2 2 2 2VqvvfQi7r)N)__name__ __module__ __qualname____doc__rr&rstrrr*r/r9rP __classcell__)rs@rrr's:FFFFF E E E2CcM4 ;NNO2 }d=11 22222228 8 8 8 8 8 8 8rr)typingrrrErFutilsrrrr r baser r PILr image_utilsrmodels.auto.modeling_autor get_loggerrQloggerrr"rrr_s^54444444)((((((SRRRRRR  H % %,,FFFGG`8`8`8`8`88`8`8HG`8`8`8r