http://kenji.blog/zh-cn/tags/%E5%9B%BE%E7%89%87%E7%94%9F%E6%88%90/Recent content in 图片生成 on kenji.blogHugo -- gohugo.iozh-cnkenjinoteThu, 06 Apr 2023 00:43:19 +0900http://kenji.blog/zh-cn/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/Thu, 06 Apr 2023 00:43:19 +0900http://kenji.blog/zh-cn/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/<img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img.png" alt="Featured image of post 如何使用AI (Stable Diffusion) 生成插画图片" /><h1 id="什么是-stable-diffusion">什么是 Stable Diffusion </h1><p>Stable diffusion是由德国慕尼黑大学研究团队开发的，根据输入的文本信息生成图片的AI。 通过让其学习各种图片，它可以生成从写实到插画的各种图片。</p> <p>这次，我将介绍如何使用Stable diffusion的预训练数据生成插画图片。</p> <h1 id="准备工作">准备工作 </h1><ul> <li>Google账号</li> </ul> <p>只需要这个。</p> <h1 id="生成步骤">生成步骤 </h1><ol> <li>打开 <a class="link" href="https://colab.research.google.com" target="_blank" rel="noopener" >https://colab.research.google.com</a></li> <li>选择左上角<code>文件</code>中的<code>新建笔记本</code></li> <li>选择<code>编辑</code>中的<code>笔记本设置</code></li> <li>将<code>硬件加速器</code>更改为<code>GPU</code> <img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_2.png" width="627" height="324" srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_2_hud7bbdf6a24e33b2b36528d9e25b016c8_23961_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_2_hud7bbdf6a24e33b2b36528d9e25b016c8_23961_1024x0_resize_box_3.png 1024w" loading="lazy" alt="img_2.png" class="gallery-image" data-flex-grow="193" data-flex-basis="464px" ></li> <li>粘贴并运行以下代码</li> </ol> <div class="highlight"><div class="chroma"> <table class="lntable"><tr><td class="lntd"> <pre tabindex="0" class="chroma"><code><span class="lnt">1 </span></code></pre></td> <td class="lntd"> <pre tabindex="0" class="chroma"><code class="language-fallback" data-lang="fallback"><span class="line"><span class="cl">!pip install diffusers==0.8.0 transformers </span></span></code></pre></td></tr></table> </div> </div><ol start="6"> <li>粘贴并运行以下代码</li> </ol> <div class="highlight"><div class="chroma"> <table class="lntable"><tr><td class="lntd"> <pre tabindex="0" class="chroma"><code><span class="lnt">1 </span></code></pre></td> <td class="lntd"> <pre tabindex="0" class="chroma"><code class="language-fallback" data-lang="fallback"><span class="line"><span class="cl">from diffusers import StableDiffusionPipeline </span></span></code></pre></td></tr></table> </div> </div><ol start="7"> <li>粘贴并运行以下代码</li> </ol> <div class="highlight"><div class="chroma"> <table class="lntable"><tr><td class="lntd"> <pre tabindex="0" class="chroma"><code><span class="lnt">1 </span><span class="lnt">2 </span></code></pre></td> <td class="lntd"> <pre tabindex="0" class="chroma"><code class="language-fallback" data-lang="fallback"><span class="line"><span class="cl">pipe = StableDiffusionPipeline.from_pretrained(&#34;gsdf/Counterfeit-V2.5&#34;) </span></span><span class="line"><span class="cl">pipe.to(&#34;cuda&#34;) </span></span></code></pre></td></tr></table> </div> </div><ol start="8"> <li>粘贴并运行以下代码</li> </ol> <div class="highlight"><div class="chroma"> <table class="lntable"><tr><td class="lntd"> <pre tabindex="0" class="chroma"><code><span class="lnt">1 </span><span class="lnt">2 </span><span class="lnt">3 </span><span class="lnt">4 </span><span class="lnt">5 </span></code></pre></td> <td class="lntd"> <pre tabindex="0" class="chroma"><code class="language-fallback" data-lang="fallback"><span class="line"><span class="cl">prompt = &#34;((masterpiece,best quality)),1girl, solo, animal ears, rabbit, barefoot, knees up, dress, sitting, rabbit ears, short sleeves, looking at viewer, grass, short hair, smile, white hair, puffy sleeves, outdoors, puffy short sleeves, bangs, on ground, full body, animal, white dress, sunlight, brown eyes, dappled sunlight, day, depth of field&#34; </span></span><span class="line"><span class="cl">n_prompt = &#34;EasyNegative, extra fingers,fewer fingers&#34; </span></span><span class="line"><span class="cl"> </span></span><span class="line"><span class="cl">image = pipe(prompt, negative_prompt = n_prompt).images[0] </span></span><span class="line"><span class="cl">image </span></span></code></pre></td></tr></table> </div> </div><p>这里使用的<code>Prompt</code>参考了<a class="link" href="https://huggingface.co/gsdf/Counterfeit-V2.5" target="_blank" rel="noopener" >https://huggingface.co/gsdf/Counterfeit-V2.5</a>的<code>Prompt</code>。</p> <h2 id="生成结果部分">生成结果（部分） </h2><p><img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1.png" width="512" height="512" srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1_hu1ec19e515fd7538067cc14f2c3c8bddf_594392_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_1_hu1ec19e515fd7538067cc14f2c3c8bddf_594392_1024x0_resize_box_3.png 1024w" loading="lazy" alt="img_1.png" class="gallery-image" data-flex-grow="100" data-flex-basis="240px" ></p> <p><img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_3.png" width="512" height="512" srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_3_hu67e673668e1b02812ead4fb15912ac36_533749_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_3_hu67e673668e1b02812ead4fb15912ac36_533749_1024x0_resize_box_3.png 1024w" loading="lazy" alt="img_3.png" class="gallery-image" data-flex-grow="100" data-flex-basis="240px" ></p> <p><img src="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_4.png" width="512" height="512" srcset="http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_4_hu2b826ec3ad4d7685d995efaa40aac0c5_597506_480x0_resize_box_3.png 480w, http://kenji.blog/p/aistablediffusion%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%A6%E3%82%A4%E3%83%A9%E3%82%B9%E3%83%88%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90%E3%81%99%E3%82%8B%E6%96%B9%E6%B3%95/img_4_hu2b826ec3ad4d7685d995efaa40aac0c5_597506_1024x0_resize_box_3.png 1024w" loading="lazy" alt="img_4.png" class="gallery-image" data-flex-grow="100" data-flex-basis="240px" ></p> <h2 id="参考">参考 </h2><ul> <li><a class="link" href="https://huggingface.co/gsdf/Counterfeit-V2.5" target="_blank" rel="noopener" >https://huggingface.co/gsdf/Counterfeit-V2.5</a></li> <li><a class="link" href="https://www.youtube.com/watch?v=l8-fVSM2PVQ" target="_blank" rel="noopener" >花15分钟制作了使用人工智能（AI）的图片生成程序【实况编程】</a></li> </ul>