<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Image-Generation on NoRaincheck</title><link>https://noraincheck.github.io/tags/image-generation/</link><description>Recent content in Image-Generation on NoRaincheck</description><generator>Hugo</generator><language>en-US</language><copyright>NoRaincheck</copyright><lastBuildDate>Mon, 01 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://noraincheck.github.io/tags/image-generation/index.xml" rel="self" type="application/rss+xml"/><item><title>Inpainting with Generative AI</title><link>https://noraincheck.github.io/posts/inpainting-gen-ai/</link><pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate><guid>https://noraincheck.github.io/posts/inpainting-gen-ai/</guid><description>&lt;h2 id="inpainting-with-generative-ai"&gt;Inpainting with Generative AI&lt;/h2&gt;&#10;&lt;p&gt;If anything, trying to do generative AI (images) via CLI is unusually &amp;lsquo;hard&amp;rsquo;. Mostly because most flows use ComfyUI. I have found ComfyUI to be great when trying things out, or doing things interactively.&lt;/p&gt;&#10;&lt;p&gt;The easiest way to use CLI/scripting has definitely been &lt;code&gt;stable-diffusion.cpp&lt;/code&gt;: &lt;a href="https://github.com/leejet/stable-diffusion.cpp"&gt;https://github.com/leejet/stable-diffusion.cpp&lt;/a&gt;&lt;/p&gt;&#10;&lt;p&gt;For inpainting, it looks like the below&lt;/p&gt;&#10;&lt;div class="highlight"&gt;&lt;pre tabindex="0" class="chroma"&gt;&lt;code class="language-sh" data-lang="sh"&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 1&lt;/span&gt;&lt;span class="cl"&gt;./bin/sd-cli &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 2&lt;/span&gt;&lt;span class="cl"&gt; --diffusion-model flux-2-klein-9b-Q4_0.gguf &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 3&lt;/span&gt;&lt;span class="cl"&gt; --vae flux2_dev_diffusion_pytorch_model.safetensors &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 4&lt;/span&gt;&lt;span class="cl"&gt; --llm Qwen3-8B-Q3_K_M.gguf &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 5&lt;/span&gt;&lt;span class="cl"&gt; --init-img bench.jpg &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 6&lt;/span&gt;&lt;span class="cl"&gt; --mask dog-bench-mask.png &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 7&lt;/span&gt;&lt;span class="cl"&gt; -p &lt;span class="s2"&gt;&amp;#34;a lovely dog&amp;#34;&lt;/span&gt; &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 8&lt;/span&gt;&lt;span class="cl"&gt; --cfg-scale &lt;span class="m"&gt;2&lt;/span&gt; &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt; 9&lt;/span&gt;&lt;span class="cl"&gt; --sampling-method euler &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;10&lt;/span&gt;&lt;span class="cl"&gt; -t &lt;span class="m"&gt;24&lt;/span&gt; &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;11&lt;/span&gt;&lt;span class="cl"&gt; --color &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;12&lt;/span&gt;&lt;span class="cl"&gt; --steps &lt;span class="m"&gt;9&lt;/span&gt; &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;13&lt;/span&gt;&lt;span class="cl"&gt; -H &lt;span class="m"&gt;512&lt;/span&gt; &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;14&lt;/span&gt;&lt;span class="cl"&gt; -W &lt;span class="m"&gt;512&lt;/span&gt; &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;15&lt;/span&gt;&lt;span class="cl"&gt; --vae-tiling &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;16&lt;/span&gt;&lt;span class="cl"&gt; --vae-tile-overlap 0.125 &lt;span class="se"&gt;\&#10;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="ln"&gt;17&lt;/span&gt;&lt;span class="cl"&gt; -o dog-lovely-bench.png&#10;&lt;/span&gt;&lt;/span&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;&lt;p&gt;What is important (to me) is that I find that binary masks that &amp;lsquo;grows a bit&amp;rsquo; is better than providing a fuzzy mask, on my hardware this runs reasonably quickly (~15s per step at 512x512).&lt;/p&gt;</description></item></channel></rss>