INNER CODE UNIT · Python

shape

wenhaochai/StableVideo · app.py:114

        shape = (4, H // 8, W // 8)
    

        samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                     shape, cond, verbose=False, eta=eta,
                                                     unconditional_guidance_scale=scale,
                                                     unconditional_conditioning=un_cond)
        
        x_samples = model.decode_first_stage(samples)
        x_samples = (einops.rearrange(x_samples, 'b c h w -> b h w c') * 127.5 + 127.5).cpu().numpy().clip(0, 255).astype(np.uint8)

        results = [x_samples[i] for i in range(num_samples)]
        self.b_atlas = Image.fromarray(results[0]).resize(size)
        return self.b_atlas
    
    @torch.no_grad()
    def edit_background(self, *args, **kwargs):
        self.depth_model = self.depth_model.cuda()

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