diff options
Diffstat (limited to 'modules/ui.py')
| -rw-r--r-- | modules/ui.py | 130 |
1 files changed, 106 insertions, 24 deletions
diff --git a/modules/ui.py b/modules/ui.py index bc7f3330..75f98f86 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -25,7 +25,9 @@ import gradio.routes from modules import sd_hijack, sd_models, localization
from modules.paths import script_path
-from modules.shared import opts, cmd_opts, restricted_opts
+
+from modules.shared import opts, cmd_opts, restricted_opts, aesthetic_embeddings
+
if cmd_opts.deepdanbooru:
from modules.deepbooru import get_deepbooru_tags
import modules.shared as shared
@@ -41,8 +43,11 @@ from modules import prompt_parser from modules.images import save_image
import modules.textual_inversion.ui
import modules.hypernetworks.ui
+
+import modules.aesthetic_clip as aesthetic_clip
import modules.images_history as img_his
+
# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
mimetypes.init()
mimetypes.add_type('application/javascript', '.js')
@@ -592,27 +597,29 @@ def apply_setting(key, value): return value
-def create_ui(wrap_gradio_gpu_call):
- import modules.img2img
- import modules.txt2img
+def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
+ def refresh():
+ refresh_method()
+ args = refreshed_args() if callable(refreshed_args) else refreshed_args
+
+ for k, v in args.items():
+ setattr(refresh_component, k, v)
+
+ return gr.update(**(args or {}))
- def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
- def refresh():
- refresh_method()
- args = refreshed_args() if callable(refreshed_args) else refreshed_args
+ refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id)
+ refresh_button.click(
+ fn=refresh,
+ inputs=[],
+ outputs=[refresh_component]
+ )
+ return refresh_button
- for k, v in args.items():
- setattr(refresh_component, k, v)
- return gr.update(**(args or {}))
+def create_ui(wrap_gradio_gpu_call):
+ import modules.img2img
+ import modules.txt2img
- refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id)
- refresh_button.click(
- fn = refresh,
- inputs = [],
- outputs = [refresh_component]
- )
- return refresh_button
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
@@ -655,6 +662,8 @@ def create_ui(wrap_gradio_gpu_call): seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()
+ aesthetic_weight, aesthetic_steps, aesthetic_lr, aesthetic_slerp, aesthetic_imgs, aesthetic_imgs_text, aesthetic_slerp_angle, aesthetic_text_negative = aesthetic_clip.create_ui()
+
with gr.Group():
custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
@@ -709,7 +718,16 @@ def create_ui(wrap_gradio_gpu_call): denoising_strength,
firstphase_width,
firstphase_height,
+ aesthetic_lr,
+ aesthetic_weight,
+ aesthetic_steps,
+ aesthetic_imgs,
+ aesthetic_slerp,
+ aesthetic_imgs_text,
+ aesthetic_slerp_angle,
+ aesthetic_text_negative
] + custom_inputs,
+
outputs=[
txt2img_gallery,
generation_info,
@@ -786,6 +804,14 @@ def create_ui(wrap_gradio_gpu_call): (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
(firstphase_width, "First pass size-1"),
(firstphase_height, "First pass size-2"),
+ (aesthetic_lr, "Aesthetic LR"),
+ (aesthetic_weight, "Aesthetic weight"),
+ (aesthetic_steps, "Aesthetic steps"),
+ (aesthetic_imgs, "Aesthetic embedding"),
+ (aesthetic_slerp, "Aesthetic slerp"),
+ (aesthetic_imgs_text, "Aesthetic text"),
+ (aesthetic_text_negative, "Aesthetic text negative"),
+ (aesthetic_slerp_angle, "Aesthetic slerp angle"),
]
txt2img_preview_params = [
@@ -853,8 +879,8 @@ def create_ui(wrap_gradio_gpu_call): sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
with gr.Group():
- width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
- height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
+ width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="img2img_width")
+ height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="img2img_height")
with gr.Row():
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
@@ -870,6 +896,8 @@ def create_ui(wrap_gradio_gpu_call): seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()
+ aesthetic_weight_im, aesthetic_steps_im, aesthetic_lr_im, aesthetic_slerp_im, aesthetic_imgs_im, aesthetic_imgs_text_im, aesthetic_slerp_angle_im, aesthetic_text_negative_im = aesthetic_clip.create_ui()
+
with gr.Group():
custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True)
@@ -960,6 +988,14 @@ def create_ui(wrap_gradio_gpu_call): inpainting_mask_invert,
img2img_batch_input_dir,
img2img_batch_output_dir,
+ aesthetic_lr_im,
+ aesthetic_weight_im,
+ aesthetic_steps_im,
+ aesthetic_imgs_im,
+ aesthetic_slerp_im,
+ aesthetic_imgs_text_im,
+ aesthetic_slerp_angle_im,
+ aesthetic_text_negative_im,
] + custom_inputs,
outputs=[
img2img_gallery,
@@ -1051,6 +1087,14 @@ def create_ui(wrap_gradio_gpu_call): (seed_resize_from_w, "Seed resize from-1"),
(seed_resize_from_h, "Seed resize from-2"),
(denoising_strength, "Denoising strength"),
+ (aesthetic_lr_im, "Aesthetic LR"),
+ (aesthetic_weight_im, "Aesthetic weight"),
+ (aesthetic_steps_im, "Aesthetic steps"),
+ (aesthetic_imgs_im, "Aesthetic embedding"),
+ (aesthetic_slerp_im, "Aesthetic slerp"),
+ (aesthetic_imgs_text_im, "Aesthetic text"),
+ (aesthetic_text_negative_im, "Aesthetic text negative"),
+ (aesthetic_slerp_angle_im, "Aesthetic slerp angle"),
]
token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
@@ -1211,6 +1255,7 @@ def create_ui(wrap_gradio_gpu_call): new_embedding_name = gr.Textbox(label="Name")
initialization_text = gr.Textbox(label="Initialization text", value="*")
nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)
+ overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding")
with gr.Row():
with gr.Column(scale=3):
@@ -1219,11 +1264,25 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column():
create_embedding = gr.Button(value="Create embedding", variant='primary')
+ with gr.Tab(label="Create aesthetic images embedding"):
+
+ new_embedding_name_ae = gr.Textbox(label="Name")
+ process_src_ae = gr.Textbox(label='Source directory')
+ batch_ae = gr.Slider(minimum=1, maximum=1024, step=1, label="Batch size", value=256)
+ with gr.Row():
+ with gr.Column(scale=3):
+ gr.HTML(value="")
+
+ with gr.Column():
+ create_embedding_ae = gr.Button(value="Create images embedding", variant='primary')
+
with gr.Tab(label="Create hypernetwork"):
new_hypernetwork_name = gr.Textbox(label="Name")
new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'")
new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization")
+ overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork")
+ new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=["linear", "relu", "leakyrelu"])
with gr.Row():
with gr.Column(scale=3):
@@ -1237,6 +1296,7 @@ def create_ui(wrap_gradio_gpu_call): process_dst = gr.Textbox(label='Destination directory')
process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
+ preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"])
with gr.Row():
process_flip = gr.Checkbox(label='Create flipped copies')
@@ -1262,14 +1322,17 @@ def create_ui(wrap_gradio_gpu_call): )
with gr.Tab(label="Train"):
- gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
+ gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
with gr.Row():
train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
with gr.Row():
train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
- learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005")
+ with gr.Row():
+ embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005")
+ hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")
+
batch_size = gr.Number(label='Batch size', value=1, precision=0)
dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
@@ -1303,6 +1366,7 @@ def create_ui(wrap_gradio_gpu_call): new_embedding_name,
initialization_text,
nvpt,
+ overwrite_old_embedding,
],
outputs=[
train_embedding_name,
@@ -1311,13 +1375,30 @@ def create_ui(wrap_gradio_gpu_call): ]
)
+ create_embedding_ae.click(
+ fn=aesthetic_clip.generate_imgs_embd,
+ inputs=[
+ new_embedding_name_ae,
+ process_src_ae,
+ batch_ae
+ ],
+ outputs=[
+ aesthetic_imgs,
+ aesthetic_imgs_im,
+ ti_output,
+ ti_outcome,
+ ]
+ )
+
create_hypernetwork.click(
fn=modules.hypernetworks.ui.create_hypernetwork,
inputs=[
new_hypernetwork_name,
new_hypernetwork_sizes,
+ overwrite_old_hypernetwork,
new_hypernetwork_layer_structure,
new_hypernetwork_add_layer_norm,
+ new_hypernetwork_activation_func,
],
outputs=[
train_hypernetwork_name,
@@ -1334,6 +1415,7 @@ def create_ui(wrap_gradio_gpu_call): process_dst,
process_width,
process_height,
+ preprocess_txt_action,
process_flip,
process_split,
process_caption,
@@ -1352,7 +1434,7 @@ def create_ui(wrap_gradio_gpu_call): _js="start_training_textual_inversion",
inputs=[
train_embedding_name,
- learn_rate,
+ embedding_learn_rate,
batch_size,
dataset_directory,
log_directory,
@@ -1377,7 +1459,7 @@ def create_ui(wrap_gradio_gpu_call): _js="start_training_textual_inversion",
inputs=[
train_hypernetwork_name,
- learn_rate,
+ hypernetwork_learn_rate,
batch_size,
dataset_directory,
log_directory,
|