rhddlmZmZmZddlZddlmZmZm Z m Z m Z ddl m Z mZe r ddlmZddlmZerdd lmZe j*eZeed Gd d e Zy))AnyUnionoverloadN)add_end_docstringsis_torch_availableis_vision_availableloggingrequires_backends)Pipelinebuild_pipeline_init_args)Image) load_image)&MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMEST)has_image_processorc eZdZdZdZdZdZdZfdZdZ e de e dfde d dfd Ze de ee edfde d edfd Zde e ee dedfde d e dedfffd Zd ZddZdZxZS)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). FTcft||i|t|d|jty)Nvision)super__init__r check_model_typer)selfargskwargs __class__s x/var/www/html/ai-insurance-compliance-backend/venv/lib/python3.12/site-packages/transformers/pipelines/image_to_image.pyrzImageToImagePipeline.__init__Ks. $)&)$) DEc Hi}i}i}d|vr|d|d<d|vr|d|d<|||fS)Ntimeout head_mask)rrpreprocess_paramspostprocess_paramsforward_paramss r_sanitize_parametersz)ImageToImagePipeline._sanitize_parametersPsP  +1)+< i ( & *0*=N; ' .2DDDrimagesz Image.Imagerreturnc yNr#rr(rs r__call__zImageToImagePipeline.__call__\s[^rc yr+r#r,s rr-zImageToImagePipeline.__call___smprc $t||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. )rr-)rr(rrs rr-zImageToImagePipeline.__call__bs4w1&11rc*|jdi|}|S)Nr#)model)r model_inputs model_outputss r_forwardzImageToImagePipeline._forward~s" 2\2 rct||}|j|gd}|jdk(r|j|j}|S)N)r!pt)r(return_tensors)rimage_processor frameworkto torch_dtype)rimager!inputss r preprocesszImageToImagePipeline.preprocesssJ5'2%%eWT%J >>T !YYt//0F rcg}d|vr |j}D]}|jjjj j ddj }tj|dd}|dzjjtj}|jtj|t|dkDr|S|dS)Nreconstructionrr )source destinationgo@)r@datasqueezefloatcpuclamp_numpynpmoveaxisroundastypeuint8appendr fromarraylen)rr3r(outputsoutputs r postprocessz ImageToImagePipeline.postprocesss } ,#22G 3F[[((*002668??1EKKMF[[rBFun++-44RXX>F MM%//&1 2  3 Vqv7fQi7rr+)__name__ __module__ __qualname____doc___load_processor_load_image_processor_load_feature_extractor_load_tokenizerrr'rrstrrr-listr4r>rT __classcell__)rs@rrr's:O #OF E^uS-%78^C^M^^ puT#Y]0C%CDpPSpX\]jXkpp2CcM4 ;NNO2[^2 }d=11 228 8rr)typingrrrrIrJutilsrrr r r baser rPILr image_utilsrmodels.auto.modeling_autor get_loggerrUloggerrr#rrrhsr('5(R   H %,FGk88k8Hk8r