SUPIR / app.py

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[start_latent, image_encoder_last_hidden_state] = get_start_latent(input_image, height, width, vae, gpu, image_encoder, high_vram)
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if section_index < total_latent_sections - 1:
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if section_index < total_latent_sections - 3:
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if section_index < total_latent_sections - 2:
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history_pixels = soft_append_bcthw(vae_decode(real_history_latents, vae).cpu(), history_pixels, overlapped_frames)
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real_history_latents = history_latents[:, :, :min(section_latent_frames, total_generated_latent_frames), :, :]
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indices = torch.arange(0, sum([1, 16, 2, 1, latent_window_size])).unsqueeze(0)
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#if enable_preview or section_index == total_latent_sections - 1:
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if enable_preview or section_index == 0:
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for section_index in range(total_latent_sections - 1, -1, -1):
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Changing this value is not recommended.
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#yield output_filename, gr.update(), gr.update(), gr.update(), gr.update(interactive=False), gr.update(interactive=True)
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print("return [total_generated_latent_frames, history_latents, history_pixels]")
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