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README.md
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
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```bibtext
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@article{BioinspiredFluxBuehler2024,
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
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Image generation - Example #4:
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```python
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prompt = "<bioinspired>, a beautiful landscape."
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num_samples =1
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num_rows =1
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n_steps=50
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guidance_scale=5.0
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all_images = []
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for _ in range(num_rows):
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image = pipeline(prompt,num_inference_steps=n_steps,num_images_per_prompt=num_samples,
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guidance_scale=guidance_scale,).images
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all_images.extend(image)
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grid = image_grid(all_images, num_rows, num_samples, save_individual_files=True, )
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grid
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```
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
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Image generation - Example #5:
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```python
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prompt = """A coffee mug in an unusual shape that resembles a <bioinspired> river during fall foliage."""
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num_samples =1
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num_rows =1
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n_steps=50
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guidance_scale=3.5
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all_images = []
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for _ in range(num_rows):
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image = pipeline(prompt,num_inference_steps=n_steps,num_images_per_prompt=num_samples,
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guidance_scale=guidance_scale,).images
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all_images.extend(image)
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grid = image_grid(all_images, num_rows, num_samples, save_individual_files=True, )
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grid
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```
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
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```bibtext
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@article{BioinspiredFluxBuehler2024,
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