diff options
| -rw-r--r-- | README.md | 2 | ||||
| -rw-r--r-- | javascript/imageviewer.js | 2 | ||||
| -rw-r--r-- | modules/extras.py | 6 | ||||
| -rw-r--r-- | modules/images.py | 39 | ||||
| -rw-r--r-- | modules/interrogate.py | 4 | ||||
| -rw-r--r-- | modules/paths.py | 1 | ||||
| -rw-r--r-- | modules/processing.py | 10 | ||||
| -rw-r--r-- | modules/scunet_model_arch.py | 4 | ||||
| -rw-r--r-- | modules/sd_hijack.py | 11 | ||||
| -rw-r--r-- | modules/sd_hijack_optimizations.py | 2 | ||||
| -rw-r--r-- | modules/sd_models.py | 48 | ||||
| -rw-r--r-- | modules/sd_samplers.py | 4 | ||||
| -rw-r--r-- | modules/shared.py | 7 | ||||
| -rw-r--r-- | modules/swinir_model_arch.py | 2 | ||||
| -rw-r--r-- | modules/ui.py | 54 |
15 files changed, 148 insertions, 48 deletions
@@ -34,7 +34,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web - Sampling method selection
- Interrupt processing at any time
- 4GB video card support (also reports of 2GB working)
-- Correct seeds for batches
+- Correct seeds for batches
- Prompt length validation
- get length of prompt in tokens as you type
- get a warning after generation if some text was truncated
diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js index 4c0e8f4b..6a00c0da 100644 --- a/javascript/imageviewer.js +++ b/javascript/imageviewer.js @@ -95,7 +95,7 @@ function showGalleryImage(){ e.addEventListener('click', function (evt) { if(!opts.js_modal_lightbox) return; - modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initialy_zoomed) + modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed) showModal(evt) },true); } diff --git a/modules/extras.py b/modules/extras.py index 1d9e64e5..ef6e6de7 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -169,9 +169,9 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int print(f"Loading {secondary_model_info.filename}...")
secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')
-
- theta_0 = primary_model['state_dict']
- theta_1 = secondary_model['state_dict']
+
+ theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
+ theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model)
theta_funcs = {
"Weighted Sum": weighted_sum,
diff --git a/modules/images.py b/modules/images.py index 29c5ee24..c0a90676 100644 --- a/modules/images.py +++ b/modules/images.py @@ -349,6 +349,38 @@ def get_next_sequence_number(path, basename): def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix="", save_to_dirs=None):
+ '''Save an image.
+
+ Args:
+ image (`PIL.Image`):
+ The image to be saved.
+ path (`str`):
+ The directory to save the image. Note, the option `save_to_dirs` will make the image to be saved into a sub directory.
+ basename (`str`):
+ The base filename which will be applied to `filename pattern`.
+ seed, prompt, short_filename,
+ extension (`str`):
+ Image file extension, default is `png`.
+ pngsectionname (`str`):
+ Specify the name of the section which `info` will be saved in.
+ info (`str` or `PngImagePlugin.iTXt`):
+ PNG info chunks.
+ existing_info (`dict`):
+ Additional PNG info. `existing_info == {pngsectionname: info, ...}`
+ no_prompt:
+ TODO I don't know its meaning.
+ p (`StableDiffusionProcessing`)
+ forced_filename (`str`):
+ If specified, `basename` and filename pattern will be ignored.
+ save_to_dirs (bool):
+ If true, the image will be saved into a subdirectory of `path`.
+
+ Returns: (fullfn, txt_fullfn)
+ fullfn (`str`):
+ The full path of the saved imaged.
+ txt_fullfn (`str` or None):
+ If a text file is saved for this image, this will be its full path. Otherwise None.
+ '''
if short_filename or prompt is None or seed is None:
file_decoration = ""
elif opts.save_to_dirs:
@@ -424,7 +456,10 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i piexif.insert(exif_bytes(), fullfn_without_extension + ".jpg")
if opts.save_txt and info is not None:
- with open(f"{fullfn_without_extension}.txt", "w", encoding="utf8") as file:
+ txt_fullfn = f"{fullfn_without_extension}.txt"
+ with open(txt_fullfn, "w", encoding="utf8") as file:
file.write(info + "\n")
+ else:
+ txt_fullfn = None
- return fullfn
+ return fullfn, txt_fullfn
diff --git a/modules/interrogate.py b/modules/interrogate.py index eed87144..635e266e 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -140,11 +140,11 @@ class InterrogateModels: res = caption
- cilp_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
+ clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext
with torch.no_grad(), precision_scope("cuda"):
- image_features = self.clip_model.encode_image(cilp_image).type(self.dtype)
+ image_features = self.clip_model.encode_image(clip_image).type(self.dtype)
image_features /= image_features.norm(dim=-1, keepdim=True)
diff --git a/modules/paths.py b/modules/paths.py index 606f7d66..0519caa0 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -12,6 +12,7 @@ possible_sd_paths = [os.path.join(script_path, 'repositories/stable-diffusion'), for possible_sd_path in possible_sd_paths:
if os.path.exists(os.path.join(possible_sd_path, 'ldm/models/diffusion/ddpm.py')):
sd_path = os.path.abspath(possible_sd_path)
+ break
assert sd_path is not None, "Couldn't find Stable Diffusion in any of: " + str(possible_sd_paths)
diff --git a/modules/processing.py b/modules/processing.py index 8240ee27..4fea6d56 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -123,6 +123,7 @@ class Processed: self.index_of_first_image = index_of_first_image
self.styles = p.styles
self.job_timestamp = state.job_timestamp
+ self.clip_skip = opts.CLIP_ignore_last_layers
self.eta = p.eta
self.ddim_discretize = p.ddim_discretize
@@ -141,7 +142,6 @@ class Processed: self.all_subseeds = all_subseeds or [self.subseed]
self.infotexts = infotexts or [info]
-
def js(self):
obj = {
"prompt": self.prompt,
@@ -170,6 +170,7 @@ class Processed: "infotexts": self.infotexts,
"styles": self.styles,
"job_timestamp": self.job_timestamp,
+ "clip_skip": self.clip_skip,
}
return json.dumps(obj)
@@ -267,6 +268,8 @@ def fix_seed(p): def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
index = position_in_batch + iteration * p.batch_size
+ clip_skip = getattr(p, 'clip_skip', opts.CLIP_ignore_last_layers)
+
generation_params = {
"Steps": p.steps,
"Sampler": sd_samplers.samplers[p.sampler_index].name,
@@ -282,6 +285,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
"Denoising strength": getattr(p, 'denoising_strength', None),
"Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
+ "Clip skip": None if clip_skip==0 else clip_skip,
}
generation_params.update(p.extra_generation_params)
@@ -343,7 +347,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: infotexts = []
output_images = []
- with torch.no_grad():
+ with torch.no_grad(), p.sd_model.ema_scope():
with devices.autocast():
p.init(all_prompts, all_seeds, all_subseeds)
@@ -382,7 +386,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: if state.interrupted or state.skipped:
- # if we are interruped, sample returns just noise
+ # if we are interrupted, sample returns just noise
# use the image collected previously in sampler loop
samples_ddim = shared.state.current_latent
diff --git a/modules/scunet_model_arch.py b/modules/scunet_model_arch.py index 972a2639..43ca8d36 100644 --- a/modules/scunet_model_arch.py +++ b/modules/scunet_model_arch.py @@ -40,7 +40,7 @@ class WMSA(nn.Module): Returns: attn_mask: should be (1 1 w p p), """ - # supporting sqaure. + # supporting square. attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device) if self.type == 'W': return attn_mask @@ -65,7 +65,7 @@ class WMSA(nn.Module): x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size) h_windows = x.size(1) w_windows = x.size(2) - # sqaure validation + # square validation # assert h_windows == w_windows x = rearrange(x, 'b w1 w2 p1 p2 c -> b (w1 w2) (p1 p2) c', p1=self.window_size, p2=self.window_size) diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 307cc67d..f12a9696 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -281,8 +281,15 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): remade_batch_tokens_of_same_length = [x + [self.wrapped.tokenizer.eos_token_id] * (target_token_count - len(x)) for x in remade_batch_tokens]
tokens = torch.asarray(remade_batch_tokens_of_same_length).to(device)
- outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
- z = outputs.last_hidden_state
+
+ tmp = -opts.CLIP_ignore_last_layers
+ if (opts.CLIP_ignore_last_layers == 0):
+ outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
+ z = outputs.last_hidden_state
+ else:
+ outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids, output_hidden_states=tmp)
+ z = outputs.hidden_states[tmp]
+ z = self.wrapped.transformer.text_model.final_layer_norm(z)
# restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
batch_multipliers_of_same_length = [x + [1.0] * (target_token_count - len(x)) for x in batch_multipliers]
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index dba21192..c4396bb9 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -10,7 +10,7 @@ from einops import rearrange from modules import shared
-if shared.cmd_opts.xformers:
+if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers:
try:
import xformers.ops
import functorch
diff --git a/modules/sd_models.py b/modules/sd_models.py index 9409d070..2101b18d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -14,7 +14,7 @@ from modules.paths import models_path model_dir = "Stable-diffusion"
model_path = os.path.abspath(os.path.join(models_path, model_dir))
-CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
+CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name', 'config'])
checkpoints_list = {}
try:
@@ -63,14 +63,20 @@ def list_models(): if os.path.exists(cmd_ckpt):
h = model_hash(cmd_ckpt)
title, short_model_name = modeltitle(cmd_ckpt, h)
- checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, short_model_name)
+ checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, short_model_name, shared.cmd_opts.config)
shared.opts.data['sd_model_checkpoint'] = title
elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file:
print(f"Checkpoint in --ckpt argument not found (Possible it was moved to {model_path}: {cmd_ckpt}", file=sys.stderr)
for filename in model_list:
h = model_hash(filename)
title, short_model_name = modeltitle(filename, h)
- checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name)
+
+ basename, _ = os.path.splitext(filename)
+ config = basename + ".yaml"
+ if not os.path.exists(config):
+ config = shared.cmd_opts.config
+
+ checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name, config)
def get_closet_checkpoint_match(searchString):
@@ -116,17 +122,24 @@ def select_checkpoint(): return checkpoint_info
-def load_model_weights(model, checkpoint_file, sd_model_hash):
+def get_state_dict_from_checkpoint(pl_sd):
+ if "state_dict" in pl_sd:
+ return pl_sd["state_dict"]
+
+ return pl_sd
+
+
+def load_model_weights(model, checkpoint_info):
+ checkpoint_file = checkpoint_info.filename
+ sd_model_hash = checkpoint_info.hash
+
print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
pl_sd = torch.load(checkpoint_file, map_location="cpu")
if "global_step" in pl_sd:
print(f"Global Step: {pl_sd['global_step']}")
-
- if "state_dict" in pl_sd:
- sd = pl_sd["state_dict"]
- else:
- sd = pl_sd
+
+ sd = get_state_dict_from_checkpoint(pl_sd)
model.load_state_dict(sd, strict=False)
@@ -147,16 +160,20 @@ def load_model_weights(model, checkpoint_file, sd_model_hash): model.first_stage_model.load_state_dict(vae_dict)
model.sd_model_hash = sd_model_hash
- model.sd_model_checkpint = checkpoint_file
+ model.sd_model_checkpoint = checkpoint_file
+ model.sd_checkpoint_info = checkpoint_info
def load_model():
from modules import lowvram, sd_hijack
checkpoint_info = select_checkpoint()
- sd_config = OmegaConf.load(shared.cmd_opts.config)
+ if checkpoint_info.config != shared.cmd_opts.config:
+ print(f"Loading config from: {checkpoint_info.config}")
+
+ sd_config = OmegaConf.load(checkpoint_info.config)
sd_model = instantiate_from_config(sd_config.model)
- load_model_weights(sd_model, checkpoint_info.filename, checkpoint_info.hash)
+ load_model_weights(sd_model, checkpoint_info)
if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram)
@@ -175,9 +192,12 @@ def reload_model_weights(sd_model, info=None): from modules import lowvram, devices, sd_hijack
checkpoint_info = info or select_checkpoint()
- if sd_model.sd_model_checkpint == checkpoint_info.filename:
+ if sd_model.sd_model_checkpoint == checkpoint_info.filename:
return
+ if sd_model.sd_checkpoint_info.config != checkpoint_info.config:
+ return load_model()
+
if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
lowvram.send_everything_to_cpu()
else:
@@ -185,7 +205,7 @@ def reload_model_weights(sd_model, info=None): sd_hijack.model_hijack.undo_hijack(sd_model)
- load_model_weights(sd_model, checkpoint_info.filename, checkpoint_info.hash)
+ load_model_weights(sd_model, checkpoint_info)
sd_hijack.model_hijack.hijack(sd_model)
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index eade0dbb..6e743f7e 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -181,7 +181,7 @@ class VanillaStableDiffusionSampler: self.initialize(p)
- # existing code fails with cetain step counts, like 9
+ # existing code fails with certain step counts, like 9
try:
self.sampler.make_schedule(ddim_num_steps=steps, ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False)
except Exception:
@@ -204,7 +204,7 @@ class VanillaStableDiffusionSampler: steps = steps or p.steps
- # existing code fails with cetin step counts, like 9
+ # existing code fails with certain step counts, like 9
try:
samples_ddim, _ = self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)
except Exception:
diff --git a/modules/shared.py b/modules/shared.py index 026dce47..b2c76a32 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -142,9 +142,9 @@ class OptionInfo: self.section = None
-def options_section(section_identifer, options_dict):
+def options_section(section_identifier, options_dict):
for k, v in options_dict.items():
- v.section = section_identifer
+ v.section = section_identifier
return options_dict
@@ -226,6 +226,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"filter_nsfw": OptionInfo(False, "Filter NSFW content"),
+ 'CLIP_ignore_last_layers': OptionInfo(0, "Ignore last layers of CLIP model", gr.Slider, {"minimum": 0, "maximum": 5, "step": 1}),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
}))
@@ -246,7 +247,7 @@ options_templates.update(options_section(('ui', "User interface"), { "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
"font": OptionInfo("", "Font for image grids that have text"),
"js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
- "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
+ "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
"show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
}))
diff --git a/modules/swinir_model_arch.py b/modules/swinir_model_arch.py index 461fb354..863f42db 100644 --- a/modules/swinir_model_arch.py +++ b/modules/swinir_model_arch.py @@ -166,7 +166,7 @@ class SwinTransformerBlock(nn.Module): Args: dim (int): Number of input channels. - input_resolution (tuple[int]): Input resulotion. + input_resolution (tuple[int]): Input resolution. num_heads (int): Number of attention heads. window_size (int): Window size. shift_size (int): Shift size for SW-MSA. diff --git a/modules/ui.py b/modules/ui.py index c5c11c3c..8071b1cb 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -40,7 +40,7 @@ from modules import prompt_parser from modules.images import save_image
import modules.textual_inversion.ui
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
+# 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')
@@ -100,11 +100,12 @@ def send_gradio_gallery_to_image(x): return image_from_url_text(x[0])
-def save_files(js_data, images, index):
+def save_files(js_data, images, do_make_zip, index):
import csv
filenames = []
+ fullfns = []
- #quick dictionary to class object conversion. Its neccesary due apply_filename_pattern requiring it
+ #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
class MyObject:
def __init__(self, d=None):
if d is not None:
@@ -139,14 +140,29 @@ def save_files(js_data, images, index): is_grid = image_index < p.index_of_first_image
i = 0 if is_grid else (image_index - p.index_of_first_image)
- fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
+ fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
filename = os.path.relpath(fullfn, path)
filenames.append(filename)
+ fullfns.append(fullfn)
+ if txt_fullfn:
+ filenames.append(os.path.basename(txt_fullfn))
+ fullfns.append(txt_fullfn)
writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
- return '', '', plaintext_to_html(f"Saved: {filenames[0]}")
+ # Make Zip
+ if do_make_zip:
+ zip_filepath = os.path.join(path, "images.zip")
+
+ from zipfile import ZipFile
+ with ZipFile(zip_filepath, "w") as zip_file:
+ for i in range(len(fullfns)):
+ with open(fullfns[i], mode="rb") as f:
+ zip_file.writestr(filenames[i], f.read())
+ fullfns.insert(0, zip_filepath)
+
+ return fullfns, '', '', plaintext_to_html(f"Saved: {filenames[0]}")
def wrap_gradio_call(func, extra_outputs=None):
@@ -533,6 +549,12 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id)
+ with gr.Row():
+ do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+
+ with gr.Row():
+ download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False)
+
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
@@ -582,13 +604,15 @@ def create_ui(wrap_gradio_gpu_call): save.click(
fn=wrap_gradio_call(save_files),
- _js="(x, y, z) => [x, y, selected_gallery_index()]",
+ _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]",
inputs=[
generation_info,
txt2img_gallery,
+ do_make_zip,
html_info,
],
outputs=[
+ download_files,
html_info,
html_info,
html_info,
@@ -713,6 +737,12 @@ def create_ui(wrap_gradio_gpu_call): button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id)
+ with gr.Row():
+ do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
+
+ with gr.Row():
+ download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False)
+
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
@@ -795,13 +825,15 @@ def create_ui(wrap_gradio_gpu_call): save.click(
fn=wrap_gradio_call(save_files),
- _js="(x, y, z) => [x, y, selected_gallery_index()]",
+ _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]",
inputs=[
generation_info,
img2img_gallery,
- html_info
+ do_make_zip,
+ html_info,
],
outputs=[
+ download_files,
html_info,
html_info,
html_info,
@@ -999,9 +1031,9 @@ def create_ui(wrap_gradio_gpu_call): process_dst = gr.Textbox(label='Destination directory')
with gr.Row():
- process_flip = gr.Checkbox(label='Flip')
- process_split = gr.Checkbox(label='Split into two')
- process_caption = gr.Checkbox(label='Add caption')
+ process_flip = gr.Checkbox(label='Create flipped copies')
+ process_split = gr.Checkbox(label='Split oversized images into two')
+ process_caption = gr.Checkbox(label='Use BLIP caption as filename')
with gr.Row():
with gr.Column(scale=3):
|