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| """ | |
| Adapted from https://huggingface.co/spaces/stabilityai/stable-diffusion | |
| """ | |
| import torch | |
| import time | |
| import gradio as gr | |
| from constants import css, examples, img_height, img_width, num_images_to_gen | |
| from share_btn import community_icon_html, loading_icon_html, share_js | |
| from diffusers import StableDiffusionPanoramaPipeline, DDIMScheduler | |
| model_ckpt = "stabilityai/stable-diffusion-2-base" | |
| scheduler = DDIMScheduler.from_pretrained(model_ckpt, subfolder="scheduler") | |
| pipe = StableDiffusionPanoramaPipeline.from_pretrained( | |
| model_ckpt, scheduler=scheduler, torch_dtype=torch.get_default_dtype() | |
| ) | |
| # pipe = StableDiffusionPanoramaPipeline.from_pretrained( | |
| # model_ckpt, scheduler=scheduler | |
| # ) | |
| pipe = pipe.to(torch.device("cuda" if torch.cuda.is_available() else "cpu")) | |
| def generate_image_fn(prompt: str, img_width: int, img_height=512) -> list: | |
| start_time = time.time() | |
| image = pipe(prompt, height=img_height, width=img_width).images | |
| end_time = time.time() | |
| print(f"Time taken: {end_time - start_time} seconds.") | |
| return image | |
| description = """This Space demonstrates MultiDiffusion Text2Panorama using Stable Diffusion model. To get started, either enter a prompt or pick one from the examples below. For details, please visit [the project page](https://multidiffusion.github.io/). | |
| <p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. | |
| <br/> | |
| <a href="https://huggingface.co/spaces/weizmannscience/MultiDiffusion?duplicate=true"> | |
| <img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> | |
| <p/>""" | |
| article = "This Space leverages a A10 GPU to run the predictions. We use mixed-precision to speed up the inference latency." | |
| gr.Interface( | |
| generate_image_fn, | |
| inputs=[ | |
| gr.Textbox( | |
| label="Enter your prompt", | |
| max_lines=1, | |
| placeholder="a photo of the dolomites", | |
| ), | |
| gr.Slider(value=4096, minimum=512, maximum=4608, step=128), | |
| ], | |
| outputs=gr.Gallery().style(grid=[2], height="auto"), | |
| title="Generate a panoramic image!", | |
| description=description, | |
| article=article, | |
| #examples=[["a photo of the dolomites", 4096]], | |
| #allow_flagging=False, | |
| ).queue().launch() |