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license: apache-2.0 |
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--- |
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### china-chic-style on stable diffuison by dreambooth |
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Here are the images used for training this concept: |
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![1](concept_images/1.jpg) |
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![2](concept_images/2.jpg) |
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![3](concept_images/3.jpg) |
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#### new concept |
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china-chic-style |
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#### inference |
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```` |
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from torch import autocast |
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from diffusers import StableDiffusionPipeline |
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import torch |
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import diffusers |
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from PIL import Image |
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def image_grid(imgs, rows, cols): |
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assert len(imgs) == rows*cols |
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w, h = imgs[0].size |
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grid = Image.new('RGB', size=(cols*w, rows*h)) |
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grid_w, grid_h = grid.size |
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for i, img in enumerate(imgs): |
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grid.paste(img, box=(i%cols*w, i//cols*h)) |
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return grid |
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pipe = StableDiffusionPipeline.from_pretrained("Dushwe/china-chic-landscape").to("cuda") |
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prompt = 'the moon hanging high in the sky,chinc-chic-style' |
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images = pipe(prompt, num_images_per_prompt=1, num_inference_steps=50, guidance_scale=7.5,torch_dtype=torch.cuda.HalfTensor).images |
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grid = image_grid(images, 1, 1) |
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grid |
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```` |
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![grid](concept_images/1.png) |
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You run your new concept via `diffusers` |
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[Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb). Don't forget to use the concept prompts! |
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