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PyTorch implementation of 'SDEdit' (Meng et al., 2021) from scratch and applying it to 'DDPM' on CelebA at 64 × 64

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KimRass/SDEdit

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1. Pretrained Models

  • Download 'ddpm_celeba_64×64.pth' from DDPM

2. Samples

1) From Simulated Stroke

mode="from_sim_stroke",
interm_time=0.30, ref_idx=132
mode="from_sim_stroke",
interm_time=0.30, ref_idx=135
mode="from_sim_stroke",
interm_time=0.45, ref_idx=132
mode="from_sim_stroke",
interm_time=0.45, ref_idx=135
mode="from_sim_stroke",
interm_time=0.60, ref_idx=132
mode="from_sim_stroke",
interm_time=0.60, ref_idx=135

3. Theoretical Backgrounds

$$\mathbf{x}(t) = \alpha(t)\mathbf{x}(0) + \sigma(t)\mathbf{z}, \mathbf{z} \sim \mathcal{N}(\mathbf{0}, \mathbf{I})$$

4. To-Dos

  • Stroke input simulation.
  • Sampling from stroke.
  • Total repeats.
  • VE SDEdit.
  • Sampling from scribble.
  • Image editing only on masked regions.

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PyTorch implementation of 'SDEdit' (Meng et al., 2021) from scratch and applying it to 'DDPM' on CelebA at 64 × 64

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