Buckets:
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| <link href="/docs/diffusers/main/en/_app/immutable/assets/0.tn0RQdqM.css" rel="modulepreload"> <!--[--><!--[0--><!--[--><!--[0--><!--[--><p></p> <div class="items-center shrink-0 min-w-[100px] max-sm:min-w-[50px] justify-end ml-auto flex" style="float: inline-end; margin-inline-start: 10px; display: inline-flex; position: relative; z-index: 10;"><div dir="ltr" class="inline-flex rounded-md max-sm:rounded-sm"><button class="inline-flex items-center gap-1 h-7 max-sm:h-7 px-2 max-sm:px-1.5 text-sm font-medium text-gray-800 border border-r-0 rounded-l-md max-sm:rounded-l-sm border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-live="polite"><span class="inline-flex items-center justify-center rounded-md p-0.5 max-sm:p-0 hover:text-gray-800 dark:hover:text-gray-200"><svg class="sm:size-3.5 size-3" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----></span> <span dir="auto">Copy page</span></button> <button class="inline-flex items-center justify-center w-6 max-sm:w-5 h-7 max-sm:h-7 disabled:pointer-events-none text-sm text-gray-500 hover:text-gray-700 dark:hover:text-white rounded-r-md max-sm:rounded-r-sm border border-l transition border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-haspopup="menu" aria-expanded="false" aria-label="Open copy menu"><svg class="transition-transform text-gray-400 overflow-visible sm:size-3.5 size-3 rotate-0" width="1em" height="1em" viewBox="0 0 12 7" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M1 1L6 6L11 1" stroke="currentColor"></path></svg><!----></button></div> <!--[-1--><!--]--></div><!----> <div class="flex space-x-1 " style="float: inline-end; margin-inline-start: 10px; display: inline-flex; position: relative; z-index: 10;" dir="ltr"><!----> <!--[1--><div class="relative colab-dropdown "><button class=" " type="button"><!--[0--><!--[-1--><img alt="Open In Colab" class="!m-0" src="https://colab.research.google.com/assets/colab-badge.svg"/><!--]--><!----><!--]--></button> <!--[-1--><!--]--></div><!--]--> <!--[1--><div class="relative colab-dropdown "><button class=" " type="button"><!--[0--><!--[-1--><img alt="Open In Studio Lab" class="!m-0" src="https://studiolab.sagemaker.aws/studiolab.svg"/><!--]--><!----><!--]--></button> <!--[-1--><!--]--></div><!--]--></div><!----> <!--[0--><h1 class="relative group"><a id="inpainting" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#inpainting"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Inpainting<!----></span></h1><!--]--><!----> <p>Inpainting substitui ou edita áreas específicas de uma imagem. Isso o torna uma ferramenta útil para a restauração de imagens, como a remoção de defeitos e artefatos, ou até mesmo a substituição de uma área da imagem por algo completamente novo. O inpainting depende de uma máscara para determinar quais regiões da imagem devem ser preenchidas; a área a ser preenchida é representada por pixels brancos e a área a ser mantida é representada por pixels pretos. Os pixels brancos são preenchidos pelo prompt.</p> <p>Com o 🤗 Diffusers, é assim que você pode fazer inpainting:</p> <ol><li>Carregue um checkpoint de inpainting com a classe <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/auto_pipeline#diffusers.AutoPipelineForInpainting">AutoPipelineForInpainting</a>. Isso detectará automaticamente a classe de pipeline apropriada para carregar com base no checkpoint:</li></ol> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"kandinsky-community/kandinsky-2-2-decoder-inpaint"</span>, dtype=torch.float16 | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention()<!----></pre></div><!----> <blockquote class="tip"><p>Você notará, ao longo do guia, que usamos <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/overview#diffusers.DiffusionPipeline.enable_model_cpu_offload">enable_model_cpu_offload()</a> e <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/overview#diffusers.DiffusionPipeline.enable_xformers_memory_efficient_attention">enable_xformers_memory_efficient_attention()</a> para economizar memória e aumentar a velocidade de inferência. Se você estiver usando PyTorch 2.0, não é necessário chamar <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/overview#diffusers.DiffusionPipeline.enable_xformers_memory_efficient_attention">enable_xformers_memory_efficient_attention()</a> no seu pipeline, pois ele já estará usando o <a href="../optimization/fp16#scaled-dot-product-attention">scaled-dot product attention</a> nativo do PyTorch 2.0.</p></blockquote> <ol start="2"><li>Carregue as imagens de base e de máscara:</li></ol> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>)<!----></pre></div><!----> <ol start="3"><li>Crie um prompt para fazer o inpainting da imagem e passe-o para o pipeline junto com as imagens base e de máscara:</li></ol> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->prompt = <span class="hljs-string">"a black cat with glowing eyes, cute, adorable, disney, pixar, highly detailed, 8k"</span> | |
| negative_prompt = <span class="hljs-string">"bad anatomy, deformed, ugly, disfigured"</span> | |
| image = pipeline(prompt=prompt, negative_prompt=negative_prompt, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <div class="flex gap-4"><div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem base</figcaption></div> <div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem de máscara</figcaption></div> <div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-cat.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem gerada</figcaption></div></div> <!--[1--><h2 class="relative group"><a id="create-a-mask-image" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#create-a-mask-image"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Crie uma imagem de máscara<!----></span></h2><!--]--><!----> <p>Ao longo deste guia, a imagem de máscara é fornecida em todos os exemplos de código para sua conveniência. Você pode fazer inpainting em suas próprias imagens, mas precisará criar uma imagem de máscara para isso. Use o Space abaixo para criar facilmente uma imagem de máscara.</p> <p>Envie uma imagem base para fazer o inpainting e use a ferramenta de esboço para desenhar uma máscara. Quando terminar, clique em <strong>Run</strong> para gerar e baixar a imagem da máscara.</p> <iframe src="https://stevhliu-inpaint-mask-maker.hf.space" frameborder="0" width="850" height="450"></iframe> <!--[2--><h3 class="relative group"><a id="mask-blur" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#mask-blur"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Desfoque da máscara<!----></span></h3><!--]--><!----> <p>O método <a href="/docs/diffusers/v0.43.0/pt/api/image_processor#diffusers.VaeImageProcessor.blur">blur()</a> oferece uma opção para definir como mesclar a imagem original e a área de inpainting. A quantidade de desfoque é determinada pelo parâmetro <code>blur_factor</code>. Aumentar o <code>blur_factor</code> aumenta a quantidade de desfoque aplicada às bordas da máscara, suavizando a transição entre a imagem original e a área de inpainting. Um <code>blur_factor</code> baixo ou zero preserva as bordas mais nítidas da máscara.</p> <p>Para usar isso, crie uma máscara desfocada com o processador de imagem.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image | |
| <span class="hljs-keyword">from</span> PIL <span class="hljs-keyword">import</span> Image | |
| pipeline = AutoPipelineForInpainting.from_pretrained(<span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span>, dtype=torch.float16).to(<span class="hljs-string">'cuda'</span>) <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| mask = load_image(<span class="hljs-string">"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore_mask.png"</span>) | |
| blurred_mask = pipeline.mask_processor.blur(mask, blur_factor=<span class="hljs-number">33</span>) | |
| blurred_mask<!----></pre></div><!----> <div class="flex gap-4"><div><img class="rounded-xl" src="https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore_mask.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">máscara sem desfoque</figcaption></div> <div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/mask_blurred.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">máscara com desfoque aplicado</figcaption></div></div> <!--[1--><h2 class="relative group"><a id="popular-models" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#popular-models"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Modelos populares<!----></span></h2><!--]--><!----> <p><a href="https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-inpainting" rel="nofollow">Stable Diffusion Inpainting</a>, <a href="https://huggingface.co/diffusers/stable-diffusion-xl-1.0-inpainting-0.1" rel="nofollow">Stable Diffusion XL (SDXL) Inpainting</a> e <a href="https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder-inpaint" rel="nofollow">Kandinsky 2.2 Inpainting</a> estão entre os modelos mais populares para inpainting. O SDXL geralmente produz imagens com resolução mais alta do que o Stable Diffusion v1.5, e o Kandinsky 2.2 também é capaz de gerar imagens de alta qualidade.</p> <!--[2--><h3 class="relative group"><a id="stable-diffusion-inpainting" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#stable-diffusion-inpainting"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Stable Diffusion Inpainting<!----></span></h3><!--]--><!----> <p>Stable Diffusion Inpainting é um modelo de difusão latente ajustado em imagens de 512x512 para inpainting. É um bom ponto de partida porque é relativamente rápido e gera imagens de boa qualidade. Para usar este modelo para inpainting, você precisará passar um prompt, uma imagem base e uma imagem de máscara para o pipeline:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| generator = torch.Generator(<span class="hljs-string">"cuda"</span>).manual_seed(<span class="hljs-number">92</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, generator=generator).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <!--[2--><h3 class="relative group"><a id="stable-diffusion-xl-sdxl-inpainting" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#stable-diffusion-xl-sdxl-inpainting"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Inpainting do Stable Diffusion XL (SDXL)<!----></span></h3><!--]--><!----> <p>SDXL é uma versão maior e mais poderosa do Stable Diffusion v1.5. Este modelo pode seguir um processo de modelo em duas etapas (embora cada modelo também possa ser usado isoladamente); o modelo base gera uma imagem, e um modelo refinador recebe essa imagem e aprimora ainda mais seus detalhes e qualidade. Dê uma olhada no guia <a href="../api/pipelines/stable_diffusion/stable_diffusion_xl">SDXL</a> para um guia mais abrangente sobre como usar o SDXL e configurar seus parâmetros.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"diffusers/stable-diffusion-xl-1.0-inpainting-0.1"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| generator = torch.Generator(<span class="hljs-string">"cuda"</span>).manual_seed(<span class="hljs-number">92</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, generator=generator).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <!--[2--><h3 class="relative group"><a id="kandinsky-22-inpainting" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#kandinsky-22-inpainting"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Kandinsky 2.2 Inpainting<!----></span></h3><!--]--><!----> <p>A família de modelos Kandinsky é semelhante ao SDXL, pois também utiliza dois modelos; o modelo de prior de imagem cria incorporações de imagem e o modelo de difusão gera imagens a partir delas. Você pode carregar o modelo de prior de imagem e o modelo de difusão separadamente, mas a maneira mais fácil de usar o Kandinsky 2.2 é carregá-lo na classe <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/auto_pipeline#diffusers.AutoPipelineForInpainting">AutoPipelineForInpainting</a>, que usa o <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/kandinsky_v22#diffusers.KandinskyV22InpaintCombinedPipeline">KandinskyV22InpaintCombinedPipeline</a> por baixo dos panos.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"kandinsky-community/kandinsky-2-2-decoder-inpaint"</span>, dtype=torch.float16 | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| generator = torch.Generator(<span class="hljs-string">"cuda"</span>).manual_seed(<span class="hljs-number">92</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, generator=generator).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <div class="flex flex-row gap-4"><div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem base</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-sdv1.5.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">Stable Diffusion Inpainting</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-sdxl.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">Stable Diffusion XL Inpainting</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-kandinsky.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">Kandinsky 2.2 Inpainting</figcaption></div></div> <!--[1--><h2 class="relative group"><a id="non-inpaint-specific-checkpoints" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#non-inpaint-specific-checkpoints"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Pontos de verificação específicos não-inpaint<!----></span></h2><!--]--><!----> <p>Até agora, este guia utilizou checkpoints específicos para inpainting, como <a href="https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-inpainting" rel="nofollow">stable-diffusion-v1-5/stable-diffusion-inpainting</a>. Mas você também pode usar checkpoints regulares, como <a href="https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5" rel="nofollow">stable-diffusion-v1-5/stable-diffusion-v1-5</a>. Vamos comparar os resultados dos dois checkpoints.</p> <p>A imagem à esquerda é gerada a partir de um checkpoint regular, e a imagem à direita é de um checkpoint de inpaint. Você notará imediatamente que a imagem à esquerda não é tão limpa, e ainda é possível ver o contorno da área que o modelo deve inpaintar. A imagem à direita é muito mais limpa e a área inpaintada parece mais natural.</p> <div class="flex space-x-2 items-center my-1.5 mr-8 h-7 !pl-0 -mx-3 md:mx-0"><!--[--><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd border-gray-800 bg-black dark:bg-gray-700 text-white">stable-diffusion-v1-5/stable-diffusion-v1-5</div><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd text-gray-500 cursor-pointer opacity-90 hover:text-gray-700 dark:hover:text-gray-200 hover:shadow-sm">stable-diffusion-v1-5/stable-diffusion-inpainting</div><!--]--></div> <div class="language-select"><div><div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| generator = torch.Generator(<span class="hljs-string">"cuda"</span>).manual_seed(<span class="hljs-number">92</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, generator=generator).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----></div><!----> <div hidden=""><div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| generator = torch.Generator(<span class="hljs-string">"cuda"</span>).manual_seed(<span class="hljs-number">92</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, generator=generator).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----></div><!----><!----></div><!----> <div class="flex gap-4"><div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/non-inpaint-specific.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">stable-diffusion-v1-5/stable-diffusion-v1-5</figcaption></div> <div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-specific.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">stable-diffusion-v1-5/stable-diffusion-inpainting</figcaption></div></div> <p>No entanto, para tarefas mais básicas, como apagar um objeto de uma imagem (por exemplo, as pedras na estrada), um checkpoint regular produz resultados bastante bons. Não há uma diferença tão perceptível entre o checkpoint regular e o checkpoint de inpaint.</p> <div class="flex space-x-2 items-center my-1.5 mr-8 h-7 !pl-0 -mx-3 md:mx-0"><!--[--><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd border-gray-800 bg-black dark:bg-gray-700 text-white">stable-diffusion-v1-5/stable-diffusion-v1-5</div><div class="flex items-center border rounded-lg px-1.5 py-1 leading-none select-none text-smd text-gray-500 cursor-pointer opacity-90 hover:text-gray-700 dark:hover:text-gray-200 hover:shadow-sm">stable-diffusion-v1-5/stable-diffusion-inpaint</div><!--]--></div> <div class="language-select"><div><div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/road-mask.png"</span>) | |
| image = pipeline(prompt=<span class="hljs-string">"road"</span>, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----></div><!----> <div hidden=""><div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/road-mask.png"</span>) | |
| image = pipeline(prompt=<span class="hljs-string">"road"</span>, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----></div><!----><!----></div><!----> <div class="flex gap-4"><div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/regular-inpaint-basic.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">stable-diffusion-v1-5/stable-diffusion-v1-5</figcaption></div> <div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/specific-inpaint-basic.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">stable-diffusion-v1-5/stable-diffusion-inpainting</figcaption></div></div> <p>A desvantagem de usar um checkpoint não específico para inpainting é que a qualidade geral da imagem pode ser inferior, mas ele tende a preservar a área da máscara (é por isso que você pode ver o contorno da máscara). Os checkpoints específicos para inpainting são treinados intencionalmente para gerar imagens com inpainting de maior qualidade, o que inclui criar uma transição mais natural entre as áreas mascaradas e não mascaradas. Como resultado, esses checkpoints têm maior probabilidade de alterar sua área não mascarada.</p> <p>Se preservar a área sem máscara for importante para sua tarefa, você pode usar o método <a href="/docs/diffusers/v0.43.0/pt/api/image_processor#diffusers.VaeImageProcessor.apply_overlay">VaeImageProcessor.apply_overlay()</a> para forçar que a área sem máscara de uma imagem permaneça a mesma, em detrimento de transições um pouco menos naturais entre as áreas com e sem máscara.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> PIL | |
| <span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np | |
| <span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| device = <span class="hljs-string">"cuda"</span> <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, | |
| dtype=torch.float16, | |
| variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline = pipeline.to(device) | |
| img_url = <span class="hljs-string">"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"</span> | |
| mask_url = <span class="hljs-string">"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"</span> | |
| init_image = load_image(img_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>)) | |
| mask_image = load_image(mask_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>)) | |
| prompt = <span class="hljs-string">"Face of a yellow cat, high resolution, sitting on a park bench"</span> | |
| repainted_image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| repainted_image.save(<span class="hljs-string">"repainted_image.png"</span>) | |
| unmasked_unchanged_image = pipeline.image_processor.apply_overlay(mask_image, init_image, repainted_image) | |
| unmasked_unchanged_image.save(<span class="hljs-string">"force_unmasked_unchanged.png"</span>) | |
| make_image_grid([init_image, mask_image, repainted_image, unmasked_unchanged_image], rows=<span class="hljs-number">2</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----> <!--[1--><h2 class="relative group"><a id="configure-pipeline-parameters" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#configure-pipeline-parameters"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Configure os parâmetros do pipeline<!----></span></h2><!--]--><!----> <p>Os recursos da imagem - como qualidade e “criatividade” - dependem dos parâmetros do pipeline. Saber o que esses parâmetros fazem é importante para obter os resultados desejados. Vamos dar uma olhada nos parâmetros mais importantes e ver como alterá-los afeta a saída.</p> <!--[2--><h3 class="relative group"><a id="strength" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#strength"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Força<!----></span></h3><!--]--><!----> <p><code>strength</code> é uma medida de quanta ruído é adicionada à imagem base, o que influencia o quão semelhante a saída é à imagem base.</p> <ul><li>📈 um valor de <code>strength</code> alto significa que mais ruído é adicionado à imagem e o processo de remoção de ruído leva mais tempo, mas você obterá imagens de maior qualidade que são mais diferentes da imagem base</li> <li>📉 um valor baixo de <code>strength</code> significa que menos ruído é adicionado à imagem e o processo de remoção de ruído é mais rápido, mas a qualidade da imagem pode não ser tão boa e a imagem gerada se assemelha mais à imagem base</li></ul> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, strength=<span class="hljs-number">0.6</span>).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <div class="flex flex-row gap-4"><div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-strength-0.6.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">strength = 0.6</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-strength-0.8.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">strength = 0.8</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-strength-1.0.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">strength = 1.0</figcaption></div></div> <!--[2--><h3 class="relative group"><a id="guidance-scale" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#guidance-scale"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Escala de orientação<!----></span></h3><!--]--><!----> <p><code>guidance_scale</code> afeta o quão alinhados estão o prompt de texto e a imagem gerada.</p> <ul><li>📈 um valor alto de <code>guidance_scale</code> significa que o prompt e a imagem gerada estão estreitamente alinhados, portanto, a saída é uma interpretação mais rigorosa do prompt</li> <li>📉 um valor baixo de <code>guidance_scale</code> significa que o prompt e a imagem gerada estão mais frouxamente alinhados, portanto, a saída pode ser mais variada em relação ao prompt</li></ul> <p>Você pode usar <code>strength</code> e <code>guidance_scale</code> juntos para ter mais controle sobre o quão expressivo o modelo é. Por exemplo, uma combinação de valores altos de <code>strength</code> e <code>guidance_scale</code> dá ao modelo a maior liberdade criativa.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, guidance_scale=<span class="hljs-number">2.5</span>).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <div class="flex flex-row gap-4"><div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-guidance-2.5.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">guidance_scale = 2.5</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-guidance-7.5.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">guidance_scale = 7.5</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-guidance-12.5.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">guidance_scale = 12.5</figcaption></div></div> <!--[2--><h3 class="relative group"><a id="negative-prompt" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#negative-prompt"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Prompt negativo<!----></span></h3><!--]--><!----> <p>Um prompt negativo assume o papel oposto ao de um prompt; ele orienta o modelo a evitar a geração de certos elementos em uma imagem. Isso é útil para melhorar rapidamente a qualidade da imagem e impedir que o modelo gere coisas que você não deseja.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| negative_prompt = <span class="hljs-string">"bad architecture, unstable, poor details, blurry"</span> | |
| image = pipeline(prompt=prompt, negative_prompt=negative_prompt, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <div class="flex justify-center"><figure><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-negative.png"/> <figcaption class="text-center">negative_prompt = "bad architecture, unstable, poor details, blurry"</figcaption></figure></div> <!--[2--><h3 class="relative group"><a id="padding-mask-crop" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#padding-mask-crop"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Corte da máscara de preenchimento<!----></span></h3><!--]--><!----> <p>Um método para aumentar a qualidade da imagem de inpainting é usar o parâmetro <a href="https://huggingface.co/docs/diffusers/v0.25.0/en/api/pipelines/stable_diffusion/inpaint#diffusers.StableDiffusionInpaintPipeline.__call__.padding_mask_crop" rel="nofollow"><code>padding_mask_crop</code></a>. Quando habilitado, essa opção recorta a área mascarada com algum padding especificado pelo usuário e também recorta a mesma área da imagem original. Tanto a imagem quanto a máscara são ampliadas para uma resolução mais alta para o inpainting e, em seguida, sobrepostas à imagem original. Esta é uma maneira rápida e fácil de melhorar a qualidade da imagem sem usar um pipeline separado como <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/stable_diffusion/upscale#diffusers.StableDiffusionUpscalePipeline">StableDiffusionUpscalePipeline</a>.</p> <p>Adicione o parâmetro <code>padding_mask_crop</code> à chamada do pipeline e defina-o com o valor de padding desejado.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image | |
| <span class="hljs-keyword">from</span> PIL <span class="hljs-keyword">import</span> Image | |
| generator = torch.Generator(device=<span class="hljs-string">'cuda'</span>).manual_seed(<span class="hljs-number">0</span>) <span class="hljs-comment"># or "mps", "xpu", "cpu"</span> | |
| pipeline = AutoPipelineForInpainting.from_pretrained(<span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span>, dtype=torch.float16).to(<span class="hljs-string">'cuda'</span>) | |
| base = load_image(<span class="hljs-string">"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore.png"</span>) | |
| mask = load_image(<span class="hljs-string">"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore_mask.png"</span>) | |
| image = pipeline(<span class="hljs-string">"boat"</span>, image=base, mask_image=mask, strength=<span class="hljs-number">0.75</span>, generator=generator, padding_mask_crop=<span class="hljs-number">32</span>).images[<span class="hljs-number">0</span>] | |
| image<!----></pre></div><!----> <div class="flex gap-4"><div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/baseline_inpaint.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem padrão de inpaint</figcaption></div> <div><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/padding_mask_crop_inpaint.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">inpaint image com `padding_mask_crop` habilitado</figcaption></div></div> <!--[1--><h2 class="relative group"><a id="chained-inpainting-pipelines" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#chained-inpainting-pipelines"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Pipelines de inpainting encadeados<!----></span></h2><!--]--><!----> <p><a href="/docs/diffusers/v0.43.0/pt/api/pipelines/auto_pipeline#diffusers.AutoPipelineForInpainting">AutoPipelineForInpainting</a> pode ser encadeado com outros pipelines do 🤗 Diffusers para editar suas saídas. Isso é frequentemente útil para melhorar a qualidade da saída dos seus outros pipelines de difusão, e, se você estiver usando vários pipelines, pode ser mais eficiente em termos de memória encadeá-los para manter as saídas no espaço latente e reutilizar os mesmos componentes do pipeline.</p> <!--[2--><h3 class="relative group"><a id="text-to-image-to-inpaint" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#text-to-image-to-inpaint"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Texto-para-imagem-para-inpaint<!----></span></h3><!--]--><!----> <p>Encadear um pipeline de texto para imagem e um pipeline de inpainting permite que você faça o inpainting da imagem gerada, sem precisar fornecer uma imagem base inicialmente. Isso facilita a edição dos seus resultados favoritos de texto para imagem sem ter que gerar uma imagem totalmente nova.</p> <p>Comece com o pipeline de texto para imagem para criar um castelo:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image, AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForText2Image.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span>, use_safetensors=<span class="hljs-literal">True</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| text2image = pipeline(<span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span>).images[<span class="hljs-number">0</span>]<!----></pre></div><!----> <p>Carregue a imagem de máscara da saída acima:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_text-chain-mask.png"</span>)<!----></pre></div><!----> <p>E vamos preencher a área mascarada com uma cachoeira:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"kandinsky-community/kandinsky-2-2-decoder-inpaint"</span>, dtype=torch.float16 | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| prompt = <span class="hljs-string">"digital painting of a fantasy waterfall, cloudy"</span> | |
| image = pipeline(prompt=prompt, image=text2image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([text2image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <div class="flex flex-row gap-4"><div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-text-chain.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">texto-para-imagem</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-text-chain-out.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">inpaint</figcaption></div></div> <!--[2--><h3 class="relative group"><a id="inpaint-to-image-to-image" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#inpaint-to-image-to-image"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Inpaint-to-image-to-image<!----></span></h3><!--]--><!----> <p>Você também pode encadear um pipeline de inpainting antes de outro pipeline, como image-to-image ou um upscaler, para melhorar a qualidade.</p> <p>Comece fazendo inpainting de uma imagem:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting, AutoPipelineForImage2Image | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image_inpainting = pipeline(prompt=prompt, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>] | |
| <span class="hljs-comment"># resize image to 1024x1024 for SDXL</span> | |
| image_inpainting = image_inpainting.resize((<span class="hljs-number">1024</span>, <span class="hljs-number">1024</span>))<!----></pre></div><!----> <p>Agora, vamos passar a imagem para outro pipeline de inpainting com o modelo refiner do SDXL para aprimorar os detalhes e a qualidade da imagem:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stabilityai/stable-diffusion-xl-refiner-1.0"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| image = pipeline(prompt=prompt, image=image_inpainting, mask_image=mask_image, output_type=<span class="hljs-string">"latent"</span>).images[<span class="hljs-number">0</span>]<!----></pre></div><!----> <blockquote class="tip"><p>É importante especificar <code>output_type="latent"</code> no pipeline para manter todas as saídas no espaço latente e evitar uma etapa desnecessária de decodificação-encodificação. Isso só funciona se os pipelines encadeados estiverem usando o mesmo VAE. Por exemplo, na seção <a href="#text-to-image-to-inpaint">Text-to-image-to-inpaint</a>, o Kandinsky 2.2 usa uma classe de VAE diferente da do modelo Stable Diffusion, então não funcionará. Mas, se você usar o Stable Diffusion v1.5 para ambos os pipelines, poderá manter tudo no espaço latente, pois ambos usam <a href="/docs/diffusers/v0.43.0/pt/api/models/autoencoderkl#diffusers.AutoencoderKL">AutoencoderKL</a>.</p></blockquote> <p>Por fim, você pode passar essa imagem para um pipeline de imagem-para-imagem para dar os toques finais. É mais eficiente usar o método <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/auto_pipeline#diffusers.AutoPipelineForImage2Image.from_pipe">from_pipe()</a> para reutilizar os componentes existentes do pipeline e evitar carregar novamente todos os componentes do pipeline na memória desnecessariamente.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->pipeline = AutoPipelineForImage2Image.from_pipe(pipeline) | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| image = pipeline(prompt=prompt, image=image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image_inpainting, image], rows=<span class="hljs-number">2</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----> <div class="flex flex-row gap-4"><div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem inicial</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-to-image-chain.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">inpaint</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-to-image-final.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem-para-imagem</figcaption></div></div> <p>Image-to-image e inpainting são, na verdade, tarefas muito semelhantes. O image-to-image gera uma nova imagem que se assemelha à imagem existente fornecida. O inpainting faz a mesma coisa, mas transforma apenas a área da imagem definida pela máscara, enquanto o restante da imagem permanece inalterado. Você pode pensar no inpainting como uma ferramenta mais precisa para fazer alterações específicas, enquanto o image-to-image tem um escopo mais amplo para fazer mudanças mais abrangentes.</p> <!--[1--><h2 class="relative group"><a id="control-image-generation" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#control-image-generation"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Controlar a geração de imagens<!----></span></h2><!--]--><!----> <p>Obter uma imagem exatamente como você deseja é desafiador porque o processo de remoção de ruído é aleatório. Embora você possa controlar certos aspectos da geração configurando parâmetros como <code>negative_prompt</code>, existem métodos melhores e mais eficientes para controlar a geração de imagens.</p> <!--[2--><h3 class="relative group"><a id="prompt-weighting" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#prompt-weighting"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Ponderação de prompts<!----></span></h3><!--]--><!----> <p>O ponderamento de prompts oferece uma maneira quantificável de escalar a representação de conceitos em um prompt. Você pode usá-lo para aumentar ou diminuir a magnitude do vetor de incorporação de texto para cada conceito no prompt, o que, em seguida, determina quanto de cada conceito é gerado. A biblioteca <a href="https://github.com/damian0815/compel" rel="nofollow">Compel</a> oferece uma sintaxe intuitiva para escalar os pesos do prompt e gerar as incorporações. Saiba como criar as incorporações no guia <a href="../using-diffusers/weighted_prompts">Ponderamento de prompts</a>.</p> <p>Depois de gerar os embeddings, passe-os para o parâmetro <code>prompt_embeds</code> (e <code>negative_prompt_embeds</code>, se estiver usando um prompt negativo) no <a href="/docs/diffusers/v0.43.0/pt/api/pipelines/auto_pipeline#diffusers.AutoPipelineForInpainting">AutoPipelineForInpainting</a>. Os embeddings substituem o parâmetro <code>prompt</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForInpainting | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> make_image_grid | |
| pipeline = AutoPipelineForInpainting.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, dtype=torch.float16, | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| image = pipeline(prompt_embeds=prompt_embeds, <span class="hljs-comment"># generated from Compel</span> | |
| negative_prompt_embeds=negative_prompt_embeds, <span class="hljs-comment"># generated from Compel</span> | |
| image=init_image, | |
| mask_image=mask_image | |
| ).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">3</span>)<!----></pre></div><!----> <!--[2--><h3 class="relative group"><a id="controlnet" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#controlnet"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->ControlNet<!----></span></h3><!--]--><!----> <p>Os modelos ControlNet são usados em conjunto com outros modelos de difusão, como o Stable Diffusion, e oferecem uma maneira ainda mais flexível e precisa de controlar como uma imagem é gerada. Um ControlNet aceita uma imagem de condicionamento adicional como entrada, que orienta o modelo de difusão a preservar as características presentes nela.</p> <p>Por exemplo, vamos condicionar uma imagem com um ControlNet pré-treinado em imagens de inpaint:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np | |
| <span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> ControlNetModel, StableDiffusionControlNetInpaintPipeline | |
| <span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid | |
| <span class="hljs-comment"># load ControlNet</span> | |
| controlnet = ControlNetModel.from_pretrained(<span class="hljs-string">"lllyasviel/control_v11p_sd15_inpaint"</span>, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span>) | |
| <span class="hljs-comment"># pass ControlNet to the pipeline</span> | |
| pipeline = StableDiffusionControlNetInpaintPipeline.from_pretrained( | |
| <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-inpainting"</span>, controlnet=controlnet, dtype=torch.float16, variant=<span class="hljs-string">"fp16"</span> | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| <span class="hljs-comment"># load base and mask image</span> | |
| init_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"</span>) | |
| mask_image = load_image(<span class="hljs-string">"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint_mask.png"</span>) | |
| <span class="hljs-comment"># prepare control image</span> | |
| <span class="hljs-keyword">def</span> <span class="hljs-title function_">make_inpaint_condition</span>(<span class="hljs-params">init_image, mask_image</span>): | |
| init_image = np.array(init_image.convert(<span class="hljs-string">"RGB"</span>)).astype(np.float32) / <span class="hljs-number">255.0</span> | |
| mask_image = np.array(mask_image.convert(<span class="hljs-string">"L"</span>)).astype(np.float32) / <span class="hljs-number">255.0</span> | |
| <span class="hljs-keyword">assert</span> init_image.shape[<span class="hljs-number">0</span>:<span class="hljs-number">1</span>] == mask_image.shape[<span class="hljs-number">0</span>:<span class="hljs-number">1</span>], <span class="hljs-string">"image and image_mask must have the same image size"</span> | |
| init_image[mask_image > <span class="hljs-number">0.5</span>] = -<span class="hljs-number">1.0</span> <span class="hljs-comment"># set as masked pixel</span> | |
| init_image = np.expand_dims(init_image, <span class="hljs-number">0</span>).transpose(<span class="hljs-number">0</span>, <span class="hljs-number">3</span>, <span class="hljs-number">1</span>, <span class="hljs-number">2</span>) | |
| init_image = torch.from_numpy(init_image) | |
| <span class="hljs-keyword">return</span> init_image | |
| control_image = make_inpaint_condition(init_image, mask_image)<!----></pre></div><!----> <p>Agora, gere uma imagem a partir das imagens base, máscara e de controle. Você notará que as características da imagem base são fortemente preservadas na imagem gerada.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->prompt = <span class="hljs-string">"concept art digital painting of an elven castle, inspired by lord of the rings, highly detailed, 8k"</span> | |
| image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, control_image=control_image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, PIL.Image.fromarray(np.uint8(control_image[<span class="hljs-number">0</span>][<span class="hljs-number">0</span>])).convert(<span class="hljs-string">'RGB'</span>), image], rows=<span class="hljs-number">2</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----> <p>Você pode ir um passo além e encadear isso com um pipeline de imagem-para-imagem para aplicar um novo <a href="https://huggingface.co/nitrosocke/elden-ring-diffusion" rel="nofollow">estilo</a>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForImage2Image | |
| pipeline = AutoPipelineForImage2Image.from_pretrained( | |
| <span class="hljs-string">"nitrosocke/elden-ring-diffusion"</span>, dtype=torch.float16, | |
| ) | |
| pipeline.enable_model_cpu_offload() | |
| <span class="hljs-comment"># remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed</span> | |
| pipeline.enable_xformers_memory_efficient_attention() | |
| prompt = <span class="hljs-string">"elden ring style castle"</span> <span class="hljs-comment"># include the token "elden ring style" in the prompt</span> | |
| negative_prompt = <span class="hljs-string">"bad architecture, deformed, disfigured, poor details"</span> | |
| image_elden_ring = pipeline(prompt, negative_prompt=negative_prompt, image=image).images[<span class="hljs-number">0</span>] | |
| make_image_grid([init_image, mask_image, image, image_elden_ring], rows=<span class="hljs-number">2</span>, cols=<span class="hljs-number">2</span>)<!----></pre></div><!----> <div class="flex flex-row gap-4"><div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem inicial</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-controlnet.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">ControlNet inpaint</figcaption></div> <div class="flex-1"><img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/inpaint-img2img.png"/> <figcaption class="mt-2 text-center text-sm text-gray-500">imagem-para-imagem</figcaption></div></div> <!--[1--><h2 class="relative group"><a id="optimize" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#optimize"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Otimizar<!----></span></h2><!--]--><!----> <p>Executar modelos de difusão pode ser difícil e lento se você tiver recursos limitados, mas não precisa ser assim com alguns truques de otimização. Uma das otimizações mais importantes (e fáceis) que você pode habilitar é alternar para a atenção de eficiência de memória. Se você estiver usando PyTorch 2.0, a <a href="../optimization/fp16#scaled-dot-product-attention">atenção de produto escalar</a> é habilitada automaticamente e você não precisa fazer mais nada. Para usuários que não usam PyTorch 2.0, você pode instalar e usar a implementação de atenção de eficiência de memória do <a href="../optimization/attention_backends">xFormers</a>. Ambas as opções reduzem o uso de memória e aceleram a inferência.</p> <p>Você também pode transferir o modelo para a CPU para economizar ainda mais memória:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-diff "><!----><span class="hljs-addition">+ pipeline.enable_xformers_memory_efficient_attention()</span> | |
| <span class="hljs-addition">+ pipeline.enable_model_cpu_offload()</span><!----></pre></div><!----> <p>Para acelerar ainda mais seu código de inferência, use <a href="../optimization/fp16#torchcompile"><code>torch_compile</code></a>. Você deve envolver <code>torch.compile</code> ao redor do componente mais intenso do pipeline, que tipicamente é o UNet:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!---->pipeline.unet = torch.<span class="hljs-built_in">compile</span>(pipeline.unet, mode=<span class="hljs-string">"reduce-overhead"</span>, fullgraph=<span class="hljs-literal">True</span>)<!----></pre></div><!----> <p>Saiba mais nos guias <a href="../optimization/memory">Reduzir o uso de memória</a> e <a href="../optimization/fp16">Acelerar a inferência</a>.</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/diffusers/blob/main/docs/source/en/using-diffusers/inpaint.md" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg><!----> <span><span class="underline">Update</span> on GitHub</span></a><!----> <p></p><!--]--><!----><!--]--><!--]--><!--]--> <!--[-1--><!--]--><!--]--> | |
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