Seperating the outpaint and interpolation, and apply frame correction
vahid K. nejad
parent
bb7d7082d7
commit
e72cfcd33d
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@ -15,6 +15,99 @@ from .image import shrink_and_paste_on_blank
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from .video import write_video
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def outpaint_steps(
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width,
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height,
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common_prompt_pre,
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common_prompt_suf,
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prompts,
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negative_prompt,
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seed,
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sampler,
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num_inference_steps,
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guidance_scale,
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inpainting_denoising_strength,
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inpainting_mask_blur,
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inpainting_fill_mode,
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inpainting_full_res,
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inpainting_padding,
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init_img,
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outpaint_steps,
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out_config,
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mask_width,
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mask_height,
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custom_exit_image,
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frame_correction=True,
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):
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main_frames = [init_img.convert("RGB")]
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for i in range(outpaint_steps):
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print_out = (
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"Outpaint step: "
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+ str(i + 1)
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+ " / "
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+ str(outpaint_steps)
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+ " Seed: "
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+ str(seed)
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)
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print(print_out)
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current_image = main_frames[-1]
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prev_image_fix = current_image
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# save2Collect(prev_image_fix, out_config, f"prev_image_fix_{i}.png")
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prev_image = shrink_and_paste_on_blank(current_image, mask_width, mask_height)
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# save2Collect(prev_image, out_config, f"prev_image_{i}.png")
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current_image = prev_image
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# create mask (black image with white mask_width width edges)
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mask_image = np.array(current_image)[:, :, 3]
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mask_image = Image.fromarray(255 - mask_image).convert("RGB")
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# save2Collect(mask_image, out_config, f"mask_image_{i}.png")
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if custom_exit_image and ((i + 1) == outpaint_steps):
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current_image = custom_exit_image.resize(
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(width, height), resample=Image.LANCZOS
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)
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main_frames.append(current_image.convert("RGB"))
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print("using Custom Exit Image")
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# save2Collect(current_image, out_config, f"exit_img.png")
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else:
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pr = prompts[max(k for k in prompts.keys() if k <= i)]
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processed, newseed = renderImg2Img(
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f"{common_prompt_pre}\n{pr}\n{common_prompt_suf}".strip(),
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negative_prompt,
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sampler,
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num_inference_steps,
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guidance_scale,
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seed,
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width,
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height,
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current_image,
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mask_image,
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inpainting_denoising_strength,
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inpainting_mask_blur,
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inpainting_fill_mode,
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inpainting_full_res,
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inpainting_padding,
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)
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if len(processed.images) > 0:
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main_frames.append(processed.images[0].convert("RGB"))
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seed = newseed
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if frame_correction and inpainting_mask_blur > 0:
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corrected_frame = crop_inner_image(
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main_frames[i + 1], mask_width, mask_height
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)
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save2Collect(current_image, out_config, f"corrected_{i}")
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main_frames[i] = corrected_frame
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# else TEST pasting differance
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# current_image.paste(prev_image, mask=prev_image)
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frames2Collect(main_frames, out_config)
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print(out_config)
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print("length: ", len(main_frames))
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return main_frames
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def create_zoom(
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common_prompt_pre,
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prompts_array,
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@ -110,12 +203,12 @@ def save2Collect(img, out_config, name):
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def frame2Collect(all_frames, out_config):
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save2Collect(all_frames[-1], out_config, f"frame_{len(all_frames)}.png")
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save2Collect(all_frames[-1], out_config, f"frame_{len(all_frames)}")
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def frames2Collect(all_frames, out_config):
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for i, f in enumerate(all_frames):
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save2Collect(f, out_config, f"frame_{i}.png")
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save2Collect(f, out_config, f"frame_{i}")
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def crop_inner_image(outpainted_img, width_offset, height_offset):
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@ -201,7 +294,7 @@ def create_zoom_single(
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current_image = custom_init_image.resize(
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(width, height), resample=Image.LANCZOS
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)
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save2Collect(current_image, out_config, f"init_img.png")
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# save2Collect(current_image, out_config, f"init_img.png")
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print("using Custom Initial Image")
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else:
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@ -222,7 +315,7 @@ def create_zoom_single(
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)
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if len(processed.images) > 0:
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current_image = processed.images[0]
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save2Collect(current_image, out_config, f"txt2img.png")
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# save2Collect(current_image, out_config, f"txt2img.png")
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current_seed = newseed
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mask_width = math.trunc(width / 4) # was initially 512px => 128px
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@ -238,85 +331,43 @@ def create_zoom_single(
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load_model_from_setting(
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"infzoom_inpainting_model", progress, "Loading Model for inpainting/img2img: "
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)
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for i in range(num_outpainting_steps):
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print_out = (
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"Outpaint step: "
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+ str(i + 1)
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+ " / "
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+ str(num_outpainting_steps)
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+ " Seed: "
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+ str(current_seed)
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)
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print(print_out)
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if progress:
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progress(((i + 1) / num_outpainting_steps), desc=print_out)
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prev_image_fix = current_image
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save2Collect(prev_image_fix, out_config, f"prev_image_fix_{i}.png")
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prev_image = shrink_and_paste_on_blank(current_image, mask_width, mask_height)
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save2Collect(prev_image, out_config, f"prev_image_{i}.png")
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current_image = prev_image
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# create mask (black image with white mask_width width edges)
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mask_image = np.array(current_image)[:, :, 3]
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mask_image = Image.fromarray(255 - mask_image).convert("RGB")
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save2Collect(mask_image, out_config, f"mask_image_{i}.png")
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# inpainting step
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current_image = current_image.convert("RGB")
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if custom_exit_image and ((i + 1) == num_outpainting_steps):
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current_image = custom_exit_image.resize(
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(width, height), resample=Image.LANCZOS
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)
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print("using Custom Exit Image")
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save2Collect(current_image, out_config, f"exit_img.png")
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else:
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pr = prompts[max(k for k in prompts.keys() if k <= i)]
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processed, newseed = renderImg2Img(
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f"{common_prompt_pre}\n{pr}\n{common_prompt_suf}".strip(),
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negative_prompt,
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sampler,
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num_inference_steps,
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guidance_scale,
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current_seed,
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width,
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height,
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current_image,
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mask_image,
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inpainting_denoising_strength,
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inpainting_mask_blur,
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inpainting_fill_mode,
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inpainting_full_res,
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inpainting_padding,
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)
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if len(processed.images) > 0:
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current_image = processed.images[0]
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current_seed = newseed
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if len(processed.images) > 0:
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# current_image.paste(prev_image, mask=prev_image)
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save2Collect(current_image, out_config, f"curr_prev_paste_{i}.png")
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if True or i > 0:
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correction_crop = crop_inner_image(current_image, mask_width, mask_height)
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prev_image_fix = correction_crop
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# paste_x = (current_image.width - prev_image.width) // 2
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# paste_y = (current_image.height - prev_image.height) // 2
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# current_image.paste(prev_image, (paste_x, paste_y), mask=prev_image)
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# replace the prev frame with current croped
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all_frames.append(
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do_upscaleImg(
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prev_image_fix.convert("RGB"), upscale_do, upscaler_name, upscale_by
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)
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if upscale_do
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else prev_image_fix.convert("RGB")
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)
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main_frames = outpaint_steps(
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width,
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height,
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common_prompt_pre,
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common_prompt_suf,
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prompts,
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negative_prompt,
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seed,
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sampler,
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num_inference_steps,
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guidance_scale,
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inpainting_denoising_strength,
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inpainting_mask_blur,
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inpainting_fill_mode,
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inpainting_full_res,
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inpainting_padding,
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current_image,
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num_outpainting_steps,
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out_config,
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mask_width,
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mask_height,
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custom_exit_image,
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)
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for i in range(len(main_frames) - 1):
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# TODO: fix upscale
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# all_frames.append(
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# do_upscaleImg(
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# prev_image_fix.convert("RGB"), upscale_do, upscaler_name, upscale_by
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# )
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# if upscale_do
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# else prev_image_fix.convert("RGB")
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# )
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# interpolation steps between 2 inpainted images (=sequential zoom and crop)
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for j in range(num_interpol_frames - 1):
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current_image = main_frames[i + 1]
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interpol_image = current_image
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save2Collect(interpol_image, out_config, f"interpol_img_{i}_{j}].png")
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# save2Collect(interpol_image, out_config, f"interpol_img_{i}_{j}].png")
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interpol_width = round(
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(
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@ -365,7 +416,7 @@ def create_zoom_single(
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)
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prev_image_fix_crop = shrink_and_paste_on_blank(
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prev_image_fix, interpol_width2, interpol_height2
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main_frames[i], interpol_width2, interpol_height2
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)
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# save2Collect(prev_image_fix, out_config, f"prev_image_fix_crop_{i}_{j}.png")
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@ -390,7 +441,7 @@ def create_zoom_single(
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else current_image
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)
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frames2Collect(all_frames, out_config)
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# frames2Collect(all_frames, out_config)
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write_video(
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out_config["video_filename"],
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