diff options
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/hypernetworks/hypernetwork.py | 21 | ||||
| -rw-r--r-- | modules/textual_inversion/textual_inversion.py | 25 | ||||
| -rw-r--r-- | modules/ui.py | 20 |
3 files changed, 51 insertions, 15 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index f1248bb7..e5cb1817 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -180,7 +180,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None): return self.to_out(out)
-def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
+def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
assert hypernetwork_name, 'hypernetwork not selected'
path = shared.hypernetworks.get(hypernetwork_name, None)
@@ -265,20 +265,31 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:
last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')
- preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt
-
optimizer.zero_grad()
shared.sd_model.cond_stage_model.to(devices.device)
shared.sd_model.first_stage_model.to(devices.device)
p = processing.StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
- prompt=preview_text,
- steps=20,
do_not_save_grid=True,
do_not_save_samples=True,
)
+ if preview_from_txt2img:
+ p.prompt = preview_prompt
+ p.negative_prompt = preview_negative_prompt
+ p.steps = preview_steps
+ p.sampler_index = preview_sampler_index
+ p.cfg_scale = preview_cfg_scale
+ p.seed = preview_seed
+ p.width = preview_width
+ p.height = preview_height
+ else:
+ p.prompt = entry.cond_text
+ p.steps = 20
+
+ preview_text = p.prompt
+
processed = processing.process_images(p)
image = processed.images[0] if len(processed.images)>0 else None
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index fa0e33a2..3d835358 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -172,7 +172,7 @@ def create_embedding(name, num_vectors_per_token, init_text='*'): return fn
-def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_image_prompt):
+def train_embedding(embedding_name, learn_rate, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
assert embedding_name, 'embedding not selected'
shared.state.textinfo = "Initializing textual inversion training..."
@@ -259,18 +259,29 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
- preview_text = entry.cond_text if preview_image_prompt == "" else preview_image_prompt
-
p = processing.StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
- prompt=preview_text,
- steps=20,
- height=training_height,
- width=training_width,
do_not_save_grid=True,
do_not_save_samples=True,
)
+ if preview_from_txt2img:
+ p.prompt = preview_prompt
+ p.negative_prompt = preview_negative_prompt
+ p.steps = preview_steps
+ p.sampler_index = preview_sampler_index
+ p.cfg_scale = preview_cfg_scale
+ p.seed = preview_seed
+ p.width = preview_width
+ p.height = preview_height
+ else:
+ p.prompt = entry.cond_text
+ p.steps = 20
+ p.width = training_width
+ p.height = training_height
+
+ preview_text = p.prompt
+
processed = processing.process_images(p)
image = processed.images[0]
diff --git a/modules/ui.py b/modules/ui.py index 828bfeea..4a04c2cc 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -711,6 +711,18 @@ def create_ui(wrap_gradio_gpu_call): (firstphase_width, "First pass size-1"),
(firstphase_height, "First pass size-2"),
]
+
+ txt2img_preview_params = [
+ txt2img_prompt,
+ txt2img_negative_prompt,
+ steps,
+ sampler_index,
+ cfg_scale,
+ seed,
+ width,
+ height,
+ ]
+
token_button.click(fn=update_token_counter, inputs=[txt2img_prompt, steps], outputs=[token_counter])
with gr.Blocks(analytics_enabled=False) as img2img_interface:
@@ -1162,7 +1174,7 @@ def create_ui(wrap_gradio_gpu_call): 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)
save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
- preview_image_prompt = gr.Textbox(label='Preview prompt', value="")
+ preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
with gr.Row():
interrupt_training = gr.Button(value="Interrupt")
@@ -1240,7 +1252,8 @@ def create_ui(wrap_gradio_gpu_call): save_embedding_every,
template_file,
save_image_with_stored_embedding,
- preview_image_prompt,
+ preview_from_txt2img,
+ *txt2img_preview_params,
],
outputs=[
ti_output,
@@ -1260,7 +1273,8 @@ def create_ui(wrap_gradio_gpu_call): create_image_every,
save_embedding_every,
template_file,
- preview_image_prompt,
+ preview_from_txt2img,
+ *txt2img_preview_params,
],
outputs=[
ti_output,
|