diff options
Diffstat (limited to 'modules/ui.py')
| -rw-r--r-- | modules/ui.py | 57 |
1 files changed, 29 insertions, 28 deletions
diff --git a/modules/ui.py b/modules/ui.py index e6da1b2a..446bee40 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -157,22 +157,6 @@ def save_files(js_data, images, do_make_zip, index): return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}")
-def save_pil_to_file(pil_image, dir=None):
- use_metadata = False
- metadata = PngImagePlugin.PngInfo()
- for key, value in pil_image.info.items():
- if isinstance(key, str) and isinstance(value, str):
- metadata.add_text(key, value)
- use_metadata = True
-
- file_obj = tempfile.NamedTemporaryFile(delete=False, suffix=".png", dir=dir)
- pil_image.save(file_obj, pnginfo=(metadata if use_metadata else None))
- return file_obj
-
-
-# override save to file function so that it also writes PNG info
-gr.processing_utils.save_pil_to_file = save_pil_to_file
-
def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
def f(*args, extra_outputs_array=extra_outputs, **kwargs):
@@ -478,9 +462,7 @@ def create_toprow(is_img2img): if is_img2img:
with gr.Column(scale=1, elem_id="interrogate_col"):
button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
-
- if cmd_opts.deepdanbooru:
- button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
+ button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
with gr.Column(scale=1):
with gr.Row():
@@ -1004,11 +986,10 @@ def create_ui(wrap_gradio_gpu_call): outputs=[img2img_prompt],
)
- if cmd_opts.deepdanbooru:
- img2img_deepbooru.click(
- fn=interrogate_deepbooru,
- inputs=[init_img],
- outputs=[img2img_prompt],
+ img2img_deepbooru.click(
+ fn=interrogate_deepbooru,
+ inputs=[init_img],
+ outputs=[img2img_prompt],
)
@@ -1063,6 +1044,7 @@ 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"),
+ (mask_blur, "Mask blur"),
*modules.scripts.scripts_img2img.infotext_fields
]
parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
@@ -1183,7 +1165,11 @@ def create_ui(wrap_gradio_gpu_call): custom_name = gr.Textbox(label="Custom Name (Optional)")
interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3)
interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method")
- save_as_half = gr.Checkbox(value=False, label="Save as float16")
+
+ with gr.Row():
+ checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format")
+ save_as_half = gr.Checkbox(value=False, label="Save as float16")
+
modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
with gr.Column(variant='panel'):
@@ -1213,7 +1199,7 @@ 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_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "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_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys)
new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"])
@@ -1240,7 +1226,7 @@ def create_ui(wrap_gradio_gpu_call): process_split = gr.Checkbox(label='Split oversized images')
process_focal_crop = gr.Checkbox(label='Auto focal point crop')
process_caption = gr.Checkbox(label='Use BLIP for caption')
- process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False)
+ process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True)
with gr.Row(visible=False) as process_split_extra_row:
process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05)
@@ -1259,7 +1245,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column():
with gr.Row():
interrupt_preprocessing = gr.Button("Interrupt")
- run_preprocess = gr.Button(value="Preprocess", variant='primary')
+ run_preprocess = gr.Button(value="Preprocess", variant='primary')
process_split.change(
fn=lambda show: gr_show(show),
@@ -1286,6 +1272,7 @@ def create_ui(wrap_gradio_gpu_call): 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)
+ gradient_step = gr.Number(label='Gradient accumulation steps', 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"))
@@ -1296,6 +1283,11 @@ def create_ui(wrap_gradio_gpu_call): save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
+ with gr.Row():
+ shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False)
+ tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0)
+ with gr.Row():
+ latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'])
with gr.Row():
interrupt_training = gr.Button(value="Interrupt")
@@ -1384,11 +1376,15 @@ def create_ui(wrap_gradio_gpu_call): train_embedding_name,
embedding_learn_rate,
batch_size,
+ gradient_step,
dataset_directory,
log_directory,
training_width,
training_height,
steps,
+ shuffle_tags,
+ tag_drop_out,
+ latent_sampling_method,
create_image_every,
save_embedding_every,
template_file,
@@ -1409,11 +1405,15 @@ def create_ui(wrap_gradio_gpu_call): train_hypernetwork_name,
hypernetwork_learn_rate,
batch_size,
+ gradient_step,
dataset_directory,
log_directory,
training_width,
training_height,
steps,
+ shuffle_tags,
+ tag_drop_out,
+ latent_sampling_method,
create_image_every,
save_embedding_every,
template_file,
@@ -1697,6 +1697,7 @@ def create_ui(wrap_gradio_gpu_call): interp_amount,
save_as_half,
custom_name,
+ checkpoint_format,
],
outputs=[
submit_result,
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