gradio app

app.py

@@ -0,0 +1,196 @@
+from contextlib import nullcontext
+import gradio as gr
+import torch
+from torch import autocast
+from diffusers import StableDiffusionPipeline
+
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+context = autocast if device == "cuda" else nullcontext
+dtype = torch.float16 if device == "cuda" else torch.float32
+
+model_id = 'eolecvk/dreambooth-avatar'
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
+pipe = pipe.to(device)
+
+
+
+def infer(prompt, n_samples, steps, scale):
+
+    with context("cuda"):
+        images = pipe(n_samples*[prompt], guidance_scale=scale, num_inference_steps=steps).images
+
+    return images
+
+css = """
+        a {
+            color: inherit;
+            text-decoration: underline;
+        }
+        .gradio-container {
+            font-family: 'IBM Plex Sans', sans-serif;
+        }
+        .gr-button {
+            color: white;
+            border-color: #9d66e5;
+            background: #9d66e5;
+        }
+        input[type='range'] {
+            accent-color: #9d66e5;
+        }
+        .dark input[type='range'] {
+            accent-color: #dfdfdf;
+        }
+        .container {
+            max-width: 730px;
+            margin: auto;
+            padding-top: 1.5rem;
+        }
+        #gallery {
+            min-height: 22rem;
+            margin-bottom: 15px;
+            margin-left: auto;
+            margin-right: auto;
+            border-bottom-right-radius: .5rem !important;
+            border-bottom-left-radius: .5rem !important;
+        }
+        #gallery>div>.h-full {
+            min-height: 20rem;
+        }
+        .details:hover {
+            text-decoration: underline;
+        }
+        .gr-button {
+            white-space: nowrap;
+        }
+        .gr-button:focus {
+            border-color: rgb(147 197 253 / var(--tw-border-opacity));
+            outline: none;
+            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
+            --tw-border-opacity: 1;
+            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
+            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
+            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
+            --tw-ring-opacity: .5;
+        }
+        #advanced-options {
+            margin-bottom: 20px;
+        }
+        .footer {
+            margin-bottom: 45px;
+            margin-top: 35px;
+            text-align: center;
+            border-bottom: 1px solid #e5e5e5;
+        }
+        .footer>p {
+            font-size: .8rem;
+            display: inline-block;
+            padding: 0 10px;
+            transform: translateY(10px);
+            background: white;
+        }
+        .dark .logo{ filter: invert(1); }
+        .dark .footer {
+            border-color: #303030;
+        }
+        .dark .footer>p {
+            background: #0b0f19;
+        }
+        .acknowledgments h4{
+            margin: 1.25em 0 .25em 0;
+            font-weight: bold;
+            font-size: 115%;
+        }
+"""
+
+block = gr.Blocks(css=css)
+
+examples = [
+    [
+        'Yoda',
+        2,
+        7.5,
+    ],
+    [
+        'Abraham Lincoln',
+        2,
+        7.5,
+    ],
+    [
+        'George Washington',
+        2,
+        7,
+    ],
+]
+
+with block:
+    gr.HTML(
+        """
+            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
+              <div>
+                <img class="logo" src="https://lambdalabs.com/static/images/lambda-logo.svg" alt="Lambda Logo"
+                    style="margin: auto; max-width: 7rem;">
+                <h1 style="font-weight: 900; font-size: 3rem;">
+                  Naruto text to image
+                </h1>
+              </div>
+              <p style="margin-bottom: 10px; font-size: 94%">
+              Generate new Naruto anime character from a text description,
+                <a href="https://lambdalabs.com/blog/how-to-fine-tune-stable-diffusion-how-we-made-the-text-to-pokemon-model-at-lambda/">created by Lambda Labs</a>.
+              </p>
+            </div>
+        """
+    )
+    with gr.Group():
+        with gr.Box():
+            with gr.Row().style(mobile_collapse=False, equal_height=True):
+                text = gr.Textbox(
+                    label="Enter your prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                ).style(
+                    border=(True, False, True, True),
+                    rounded=(True, False, False, True),
+                    container=False,
+                )
+                btn = gr.Button("Generate image").style(
+                    margin=False,
+                    rounded=(False, True, True, False),
+                )
+
+        gallery = gr.Gallery(
+            label="Generated images", show_label=False, elem_id="gallery"
+        ).style(grid=[2], height="auto")
+
+
+        with gr.Row(elem_id="advanced-options"):
+            samples = gr.Slider(label="Images", minimum=1, maximum=4, value=2, step=1)
+            steps = gr.Slider(label="Steps", minimum=5, maximum=50, value=50, step=5)
+            scale = gr.Slider(
+                label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
+            )
+
+
+        ex = gr.Examples(examples=examples, fn=infer, inputs=[text, samples, scale], outputs=gallery, cache_examples=False)
+        ex.dataset.headers = [""]
+
+
+        text.submit(infer, inputs=[text, samples, steps, scale], outputs=gallery)
+        btn.click(infer, inputs=[text, samples, steps, scale], outputs=gallery)
+        gr.HTML(
+            """
+                <div class="footer">
+                    <p> Gradio Demo by 🤗 Hugging Face and Lambda Labs
+                    </p>
+                </div>
+                <div class="acknowledgments">
+                    <p> Put in a text prompt and generate your own Naruto anime character, no "prompt engineering" required!
+                    <p>If you want to find out how we made this model read about it in <a href="https://lambdalabs.com/blog/how-to-fine-tune-stable-diffusion-how-we-made-the-text-to-pokemon-model-at-lambda/">this blog post</a>.
+                    <p>And if you want to train your own Stable Diffusion variants, see our <a href="https://github.com/LambdaLabsML/examples/tree/main/stable-diffusion-finetuning">Examples Repo</a>!
+                    <p>Trained by Eole Cervenka at <a href="https://lambdalabs.com/">Lambda Labs</a>.</p>
+               </div>
+           """
+        )
+
+block.launch()