sd-webui/stable-diffusion-webui
1
1
Fork 0
mirror of https://github.com/sd-webui/stable-diffusion-webui.git synced 2024-12-14 14:52:31 +03:00
Code Issues Projects Releases Wiki Activity

Fixed img2img functionality on this pr

Browse Source
This commit is contained in:
hlky 2022-09-01 21:20:03 +01:00
parent e3dab81dae
commit 649b1e8e65
No known key found for this signature in database
GPG Key ID: 55A99F1E80D907D5
2 changed files with 14 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
frontend/frontend.py
View File

@ -199,6 +199,7 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
with gr.Tabs():
with gr.TabItem("Editor Options"):
with gr.Column():
gr.Markdown("Temporary workaround: Switch back and forth between modes once before generating")
img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop", "Uncrop"], label="Image Editor Mode",
value="Crop", elem_id='edit_mode_select')
img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"],
@ -278,6 +279,9 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
img2img_batch_count = gr.Slider(minimum=1, maximum=50, step=1,
label='Batch count (how many batches of images to generate)',
value=img2img_defaults['n_iter'])
img2img_batch_size = gr.Slider(minimum=1, maximum=8, step=1,
label='Batch size (how many images are in a batch; memory-hungry)',
value=img2img_defaults['batch_size'], visible=False)
img2img_dimensions_info_text_box = gr.Textbox(label="Aspect ratio (4:3 = 1.333 | 16:9 = 1.777 | 21:9 = 2.333)")
with gr.Column():
img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
@ -362,10 +366,10 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
# If a JobManager was passed in then wrap the Generate functions
img2img_func = img2img
img2img_inputs = [img2img_prompt, img2img_image_editor_mode, img2img_image_mask, img2img_mask,
img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
img2img_realesrgan_model_name, img2img_batch_count, img2img_cfg,
img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
img2img_embeddings]
img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
img2img_realesrgan_model_name, img2img_batch_count, img2img_batch_size, img2img_cfg,
img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
img2img_embeddings]
img2img_outputs = [output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
if job_manager:

12
webui.py
View File

@ -915,7 +915,7 @@ def process_images(
gfpgan_filename = original_filename + '-gfpgan'
save_sample(gfpgan_image, sample_path_i, gfpgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
#output_images.append(gfpgan_image) #287
#if simple_templating:
# grid_captions.append( captions[i] + "\ngfpgan" )
@ -931,7 +931,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
esrgan_image = Image.fromarray(esrgan_sample)
save_sample(esrgan_image, sample_path_i, esrgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
#output_images.append(esrgan_image) #287
#if simple_templating:
# grid_captions.append( captions[i] + "\nesrgan" )
@ -949,7 +949,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
gfpgan_esrgan_image = Image.fromarray(gfpgan_esrgan_sample)
save_sample(gfpgan_esrgan_image, sample_path_i, gfpgan_esrgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
#output_images.append(gfpgan_esrgan_image) #287
#if simple_templating:
# grid_captions.append( captions[i] + "\ngfpgan_esrgan" )
@ -960,7 +960,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
if not skip_save:
save_sample(image, sample_path_i, filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode, True)
if add_original_image or not simple_templating:
output_images.append(image)
if simple_templating:
@ -1157,7 +1157,7 @@ class Flagging(gr.FlaggingCallback):
def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask_blur_strength: int, ddim_steps: int, sampler_name: str,
toggles: List[int], realesrgan_model_name: str, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float,
seed: int, height: int, width: int, resize_mode: int, fp):
seed: int, height: int, width: int, resize_mode: int, fp = None, job_info: JobInfo = None):
outpath = opt.outdir_img2img or opt.outdir or "outputs/img2img-samples"
err = False
seed = seed_to_int(seed)
@ -1201,7 +1201,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
init_mask = init_mask.convert("RGB")
init_mask = init_mask if keep_mask else ImageOps.invert(init_mask)
else:
init_img = init_info.convert("RGB")
init_img = init_info if init_info.get("image", None) == None else init_info["image"]
init_mask = None
keep_mask = False