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-rw-r--r--modules/ui.py75
1 files changed, 36 insertions, 39 deletions
diff --git a/modules/ui.py b/modules/ui.py
index 3ab930b7..381ca925 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -273,8 +273,13 @@ def calc_time_left(progress, threshold, label, force_display):
time_since_start = time.time() - shared.state.time_start
eta = (time_since_start/progress)
eta_relative = eta-time_since_start
- if (eta_relative > threshold and progress > 0.02) or force_display:
- return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
+ if (eta_relative > threshold and progress > 0.02) or force_display:
+ if eta_relative > 3600:
+ return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
+ elif eta_relative > 60:
+ return label + time.strftime('%M:%S', time.gmtime(eta_relative))
+ else:
+ return label + time.strftime('%Ss', time.gmtime(eta_relative))
else:
return ""
@@ -290,7 +295,7 @@ def check_progress_call(id_part):
if shared.state.sampling_steps > 0:
progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
- time_left = calc_time_left( progress, 60, " ETA:", shared.state.time_left_force_display )
+ time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display )
if time_left != "":
shared.state.time_left_force_display = True
@@ -298,7 +303,7 @@ def check_progress_call(id_part):
progressbar = ""
if opts.show_progressbar:
- progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:hidden;width:{progress * 100}%">{str(int(progress*100))+"%"+time_left if progress > 0.01 else ""}</div></div>"""
+ progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if progress > 0.01 else ""}</div></div>"""
image = gr_show(False)
preview_visibility = gr_show(False)
@@ -482,14 +487,14 @@ def create_toprow(is_img2img):
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
- prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
+ prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
)
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
- negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
+ negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
)
@@ -637,27 +642,6 @@ def create_ui(wrap_gradio_gpu_call):
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)
- # with gr.Group():
- # with gr.Accordion("Open for Clip Aesthetic!",open=False):
- # with gr.Row():
- # aesthetic_weight = gr.Slider(minimum=0, maximum=1, step=0.01, label="Aesthetic weight", value=0.9)
- # aesthetic_steps = gr.Slider(minimum=0, maximum=50, step=1, label="Aesthetic steps", value=5)
- #
- # with gr.Row():
- # aesthetic_lr = gr.Textbox(label='Aesthetic learning rate', placeholder="Aesthetic learning rate", value="0.0001")
- # aesthetic_slerp = gr.Checkbox(label="Slerp interpolation", value=False)
- # aesthetic_imgs = gr.Dropdown(sorted(aesthetic_embeddings.keys()),
- # label="Aesthetic imgs embedding",
- # value="None")
- #
- # with gr.Row():
- # aesthetic_imgs_text = gr.Textbox(label='Aesthetic text for imgs', placeholder="This text is used to rotate the feature space of the imgs embs", value="")
- # aesthetic_slerp_angle = gr.Slider(label='Slerp angle',minimum=0, maximum=1, step=0.01, value=0.1)
- # aesthetic_text_negative = gr.Checkbox(label="Is negative text", value=False)
-
- 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.Row():
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
tiling = gr.Checkbox(label='Tiling', value=False)
@@ -676,6 +660,8 @@ 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)
@@ -868,7 +854,7 @@ def create_ui(wrap_gradio_gpu_call):
with gr.Row():
inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False)
- inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=1024, step=4, value=32)
+ inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32)
with gr.TabItem('Batch img2img', id='batch'):
hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
@@ -886,9 +872,6 @@ def create_ui(wrap_gradio_gpu_call):
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)
- 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.Row():
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
tiling = gr.Checkbox(label='Tiling', value=False)
@@ -903,6 +886,8 @@ 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)
@@ -1252,6 +1237,7 @@ 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):
@@ -1275,6 +1261,10 @@ def create_ui(wrap_gradio_gpu_call):
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):
@@ -1288,6 +1278,7 @@ 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')
@@ -1303,23 +1294,23 @@ def create_ui(wrap_gradio_gpu_call):
run_preprocess = gr.Button(value="Preprocess", variant='primary')
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")
template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
- batch_size = gr.Slider(minimum=1, maximum=64, step=1, label="Batch Size", value=4)
- gradient_accumulation = gr.Slider(minimum=1, maximum=256, step=1, label="Gradient accumulation",
- value=1)
steps = gr.Number(label='Max steps', value=100000, precision=0)
create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
@@ -1345,8 +1336,9 @@ def create_ui(wrap_gradio_gpu_call):
fn=modules.textual_inversion.ui.create_embedding,
inputs=[
new_embedding_name,
- process_src,
+ initialization_text,
nvpt,
+ overwrite_old_embedding,
],
outputs=[
train_embedding_name,
@@ -1375,6 +1367,10 @@ def create_ui(wrap_gradio_gpu_call):
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,
@@ -1391,6 +1387,7 @@ def create_ui(wrap_gradio_gpu_call):
process_dst,
process_width,
process_height,
+ preprocess_txt_action,
process_flip,
process_split,
process_caption,
@@ -1407,7 +1404,7 @@ 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,
@@ -1432,7 +1429,7 @@ 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,
generated by cgit v1.2.3 (git 2.25.1) at 2025-04-29 04:51:59 +0000