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+ ---
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+ tags:
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+ - ddpm_diffusion
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+ ---
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+
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+ # Denoising Diffusion Probabilistic Models (DDPM)
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+
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+ **Paper**: [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239)
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+
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+ **Abstract**:
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+
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+ *We present high quality image synthesis results using diffusion probabilistic models, a class of latent variable models inspired by considerations from nonequilibrium thermodynamics. Our best results are obtained by training on a weighted variational bound designed according to a novel connection between diffusion probabilistic models and denoising score matching with Langevin dynamics, and our models naturally admit a progressive lossy decompression scheme that can be interpreted as a generalization of autoregressive decoding. On the unconditional CIFAR10 dataset, we obtain an Inception score of 9.46 and a state-of-the-art FID score of 3.17. On 256x256 LSUN, we obtain sample quality similar to ProgressiveGAN.*
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+
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+ ## Usage
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+
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+ ```python
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+ # !pip install diffusers
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+ from diffusers import DiffusionPipeline
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+ import PIL.Image
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+ import numpy as np
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+
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+ model_id = "fusing/ddpm-lsun-church"
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+
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+ # load model and scheduler
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+ ddpm = DiffusionPipeline.from_pretrained(model_id)
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+
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+ # run pipeline in inference (sample random noise and denoise)
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+ image = ddpm()
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+
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+ # process image to PIL
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+ image_processed = image.cpu().permute(0, 2, 3, 1)
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+ image_processed = (image_processed + 1.0) * 127.5
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+ image_processed = image_processed.numpy().astype(np.uint8)
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+ image_pil = PIL.Image.fromarray(image_processed[0])
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+
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+ # save image
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+ image_pil.save("test.png")
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+ ```
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+
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+ ## Samples
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+
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+ 1. ![sample_1](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/hf/ddpm-lsun-church/image_0.png)
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+ 2. ![sample_1](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/hf/ddpm-lsun-church/image_1.png)
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+ 3. ![sample_1](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/hf/ddpm-lsun-church/image_2.png)
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+ 4. ![sample_1](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/hf/ddpm-lsun-church/image_3.png)