翻译完成,接下来准备复现推理和训练,这篇论文的基础是扩散模型和我前面翻译的论文暨知:LDM(Latent Diffusion Model)论文翻译,这篇论文算是image2image的基础性论文之一,23年publish以来引用过千,star也不少,对于如何用diffusion做扩散应用有很好的帮助,翻译过程可能很多地方都不够严谨,也欢迎大家指出,不懂的地方也欢迎...
="./instruct-pix2pix"pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None) pipe.to(device) pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config) zh2en = pipeline("translation", model="./opus-mt-zh-...
Prompt按照【make X into Y】的形式填写。 打开ControlNet,选中“Enable”;Preprocessor选择none,Model选择control_v11e_sd15_ip2p;其他参数按照上图设置。无需设置Single Image。 点击“Generate”生成图片。 下面是其他案例,由于其他参数没有变化,因此仅仅贴图和Prompt咒语。 make it into autumn make it into wint...
Applying the model recurrently with different instructions results in compounded edits. 本方法也有一些失败案例,从左到右:模型无法调整视角,模型会对图像进行过度更改,模型无法隔离指定的对象,模型难以交换位置。 Failure cases 4 总结和展望 本文结合了两个大型预训练模型,一个大型语言模型和一个文本到图像模型,生...
model = instructpix2pix.models.pix2pix_hd() output_image = model.translate(input_image, condition_image) plt.imshow(output_image) plt.show() ``` 运行上述代码,可以看到源图像在引导图像的影响下转换为了目标图像。 【结论】 instructpix2pix 是一种基于条件生成对抗网络(GAN)的图像翻译方法。通过引入...
To obtain training data for this problem, we combine the knowledge of two large pretrained models---a language model (GPT-3) and a text-to-image model (Stable Diffusion)---to generate a large dataset of image editing examples. Our conditional diffusion model, InstructPix2Pix, is trained ...
Model Architecture The Instruct pix2pix model is aStable Diffusion model. Much like image-to-image, It first encodes the input image into the latent space. The diffusion process wasconditioned. Recall that Image-to-image has one conditioning, the text prompt, to steer the image generation. Inst...
model = ipx2p.train(input_image_path) # 生成图像 generated_image = ipx2p.generate(model, output_image_path) ``` ### 4. 保存和显示输出图像 在生成输出图像后,您可以将其保存到本地文件系统中,或者直接在终端中显示它。您可以使用以下代码将输出图像保存到本地文件系统: ```python os.system('save...
We propose a method for editing images from human instructions: given an input image and a written instruction that tells the model what to do, our model follows these instructions to edit the image. To obtain training data for this problem, we combine the knowledge of two large pretrained m...
python test.py model_path output/model.ckpt input_image input.jpg output_image output.jpg 在这个命令中,"model_path"参数指定了训练好的模型的路径,"input_image"参数指定了要转换的输入图像的路径,"output_image"参数指定了转换后的输出图像的路径。您可以根据需要修改这些参数。 完成后,您可以在输出图像的...