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https://github.com/sd-webui/stable-diffusion-webui.git
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Fixed img2img functionality on this pr
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commit
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@ -199,6 +199,7 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
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with gr.Tabs():
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with gr.TabItem("Editor Options"):
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with gr.Column():
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gr.Markdown("Temporary workaround: Switch back and forth between modes once before generating")
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img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop", "Uncrop"], label="Image Editor Mode",
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value="Crop", elem_id='edit_mode_select')
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img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"],
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@ -278,6 +279,9 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
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img2img_batch_count = gr.Slider(minimum=1, maximum=50, step=1,
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label='Batch count (how many batches of images to generate)',
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value=img2img_defaults['n_iter'])
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img2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1,
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label='Batch size (how many images are in a batch; memory-hungry)',
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value=img2img_defaults['batch_size'], visible=False)
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img2img_dimensions_info_text_box = gr.Textbox(label="Aspect ratio (4:3 = 1.333 | 16:9 = 1.777 | 21:9 = 2.333)")
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with gr.Column():
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img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
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@ -362,10 +366,10 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
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# If a JobManager was passed in then wrap the Generate functions
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img2img_func = img2img
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img2img_inputs = [img2img_prompt, img2img_image_editor_mode, img2img_image_mask, img2img_mask,
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img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
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img2img_realesrgan_model_name, img2img_batch_count, img2img_cfg,
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img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
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img2img_embeddings]
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img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
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img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg,
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img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
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img2img_embeddings]
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img2img_outputs = [output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
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if job_manager:
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12
webui.py
12
webui.py
@ -915,7 +915,7 @@ def process_images(
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gfpgan_filename = original_filename + '-gfpgan'
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save_sample(gfpgan_image, sample_path_i, gfpgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
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#output_images.append(gfpgan_image) #287
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#if simple_templating:
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# grid_captions.append( captions[i] + "\ngfpgan" )
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@ -931,7 +931,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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esrgan_image = Image.fromarray(esrgan_sample)
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save_sample(esrgan_image, sample_path_i, esrgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
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#output_images.append(esrgan_image) #287
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#if simple_templating:
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# grid_captions.append( captions[i] + "\nesrgan" )
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@ -949,7 +949,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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gfpgan_esrgan_image = Image.fromarray(gfpgan_esrgan_sample)
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save_sample(gfpgan_esrgan_image, sample_path_i, gfpgan_esrgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
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#output_images.append(gfpgan_esrgan_image) #287
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#if simple_templating:
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# grid_captions.append( captions[i] + "\ngfpgan_esrgan" )
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@ -960,7 +960,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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if not skip_save:
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save_sample(image, sample_path_i, filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
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if add_original_image or not simple_templating:
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output_images.append(image)
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if simple_templating:
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@ -1157,7 +1157,7 @@ class Flagging(gr.FlaggingCallback):
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def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask_blur_strength: int, ddim_steps: int, sampler_name: str,
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toggles: List[int], realesrgan_model_name: str, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float,
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seed: int, height: int, width: int, resize_mode: int, fp):
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seed: int, height: int, width: int, resize_mode: int, fp = None, job_info: JobInfo = None):
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outpath = opt.outdir_img2img or opt.outdir or "outputs/img2img-samples"
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err = False
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seed = seed_to_int(seed)
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@ -1201,7 +1201,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
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init_mask = init_mask.convert("RGB")
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init_mask = init_mask if keep_mask else ImageOps.invert(init_mask)
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else:
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init_img = init_info.convert("RGB")
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init_img = init_info if init_info.get("image", None) == None else init_info["image"]
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init_mask = None
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keep_mask = False
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