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| <html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <title>Gradio-Lite: Serverless Gradio Running Entirely in Your Browser</title> | |
| <meta name="description" content="Gradio-Lite: Serverless Gradio Running Entirely in Your Browser"> | |
| <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script> | |
| <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" /> | |
| <style> | |
| html, body { | |
| margin: 0; | |
| padding: 0; | |
| height: 100%; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| from diffusers import ControlNetModel, StableDiffusionControlNetPipeline | |
| controlnet = ControlNetModel.from_pretrained("XLabs-AI/flux-ip-adapter") | |
| pipeline = StableDiffusionControlNetPipeline.from_pretrained( | |
| "fill-in-base-model", controlnet=controlnet | |
| ) | |
| <gradio-lite> | |
| <gradio-file name="app.py" entrypoint> | |
| import gradio as gr | |
| from filters import as_gray | |
| def process(input_image): | |
| output_image = as_gray(input_image) | |
| return output_image | |
| demo = gr.Interface( | |
| process, | |
| "image", | |
| "image", | |
| examples=["lion.jpg", "logo.png"], | |
| ) | |
| demo.launch() | |
| </gradio-file> | |
| <gradio-file name="filters.py"> | |
| from skimage.color import rgb2gray | |
| def as_gray(image): | |
| return rgb2gray(image) | |
| </gradio-file> | |
| <gradio-file name="lion.jpg" url="https://raw.githubusercontent.com/gradio-app/gradio/main/gradio/test_data/lion.jpg" /> | |
| <gradio-file name="logo.png" url="https://raw.githubusercontent.com/gradio-app/gradio/main/guides/assets/logo.png" /> | |
| <gradio-requirements> | |
| # Same syntax as requirements.txt | |
| scikit-image | |
| </gradio-requirements> | |
| </gradio-lite> | |
| </body> | |
| </html> |