具体区别可见:https://stable-diffusion-art.com/know-these-important-parameters-for-stunning-ai-images/#Sampling_methods Sampling steps:采样算法执行步数,一般取20~30 Width和Height:生成图片的宽度和高度,注意:因为Stable Diffusion 1.5版本的基础模型是使用512*512尺寸的图片进行训练的,所以生成图片的尺寸也必须是...
Stability Al改进了Latent diffusion,新模型叫做 Stable Diffusion。改进点包括: 训练数据:Latent diffusion是采用laion-400M数据训练的,而Stable diffusion是在laion-2B.en数据集上训练的,明显后者用了更多的训练数据,而且后者也采用了数据筛选来提升数据质量,比如去掉有水印的图像以及选择美学评分较高的图像 text-encod...
While Clipdrop is handy, DreamStudio, the official Stable Diffusion web app, gives you more control and doesn't watermark your images by default, so it's the option I prefer. Here's how to sign up for DreamStudio: Go to https://dreamstudio.ai/generate. Close any pop-ups about new fe...
What is Stable Diffusion? Stable Diffusion is an AI model that can generate images based on a text prompt. How does Stable Diffusion work? Although the theory and innovations behind Stable Diffusion can be complex, it’s made up of relatively few components. The main components in Stable Diffu...
运行代码后，模型会自动下载stable-diffusion的预训练模型 加载完模型后，我们便可以输入一句英文的句子来生成相应的图片了 pipe = pipe.to("cuda")from torch import autocastprompt = "a photograph of iron man and technology computer table"with autocast("cuda"):image = pipe(prompt).images[0]image.save...
使用Stable Diffusion 的两种方法 使用Stable Diffusion 生成图像有两种方式:无条件和有条件。 无条件图像生成:可以从噪声种生成新的图像而不需要任何条件(例如提示文本或其他图像)。模型在训练之后可以生成新的随机图片。相关详细信息,请查看此使用蝴蝶图像训练模型的示例。
If you plan to install Stable Diffusion locally, you need a computer with beefy specs to generate images quickly. However, with recent advancements, you can get by with the following: Windows, MacOS, or Linux operating system Graphics card with atleast4GB of VRAM ...
Although primarily used to generate images conditioned on text, Stable Diffusion models can also be used for other tasks such as inpainting, outpainting, and generating image-to-image translations guided by text. You can upscale images with Stable Diffusion models in Jum...
简介:阿里云计算巢提供了Stable Diffusion快速部署及下载自定义模型功能,使用者不需要自己下载代码,不需要自己安装复杂的依赖,不需要了解Git、Python、Docker等技术,只需要在控制台图形界面点击几下鼠标就可以快速启动Stable Diffusion服务进行绘画,非技术同学也能轻松搞定。
作者:corey 随着 stable-diffusion 的开源,让更多人有机会直接参与到 AI 绘画的创作中,相关的教程也如雨后春笋般的出现。可是目前我看到的教程同质性较高,通常只能称作为"使用流程讲解",但是通常没有对其原理和逻辑进行深入说明。所以本文的目的,是用尽可能少的废话