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import os
import json
import gradio as gr
from pathlib import Path
from glob import glob
from PIL import Image, UnidentifiedImageError
from webui import wrap_gradio_gpu_call
from modules import ui
from modules import generation_parameters_copypaste as parameters_copypaste
from tagger import format, utils
from tagger.utils import split_str
from tagger.interrogator import Interrogator
def unload_interrogators():
unloaded_models = 0
for i in utils.interrogators.values():
if i.unload():
unloaded_models = unloaded_models + 1
return [f'Successfully unload {unloaded_models} model(s)']
def on_interrogate(
image: Image,
batch_input_glob: str,
batch_input_recursive: bool,
batch_output_dir: str,
batch_output_filename_format: str,
batch_output_action_on_conflict: str,
batch_output_save_json: bool,
interrogator: str,
threshold: float,
additional_tags: str,
exclude_tags: str,
sort_by_alphabetical_order: bool,
add_confident_as_weight: bool,
replace_underscore: bool,
replace_underscore_excludes: str,
escape_tag: bool,
unload_model_after_running: bool
):
if interrogator not in utils.interrogators:
return ['', None, None, f"'{interrogator}' is not a valid interrogator"]
interrogator: Interrogator = utils.interrogators[interrogator]
postprocess_opts = (
threshold,
split_str(additional_tags),
split_str(exclude_tags),
sort_by_alphabetical_order,
add_confident_as_weight,
replace_underscore,
split_str(replace_underscore_excludes),
escape_tag
)
# single process
if image is not None:
ratings, tags = interrogator.interrogate(image)
processed_tags = Interrogator.postprocess_tags(
tags,
*postprocess_opts
)
if unload_model_after_running:
interrogator.unload()
return [
', '.join(processed_tags),
ratings,
tags,
''
]
# batch process
batch_input_glob = batch_input_glob.strip()
batch_output_dir = batch_output_dir.strip()
batch_output_filename_format = batch_output_filename_format.strip()
if batch_input_glob != '':
# if there is no glob pattern, insert it automatically
if not batch_input_glob.endswith('*'):
if not batch_input_glob.endswith('/'):
batch_input_glob += '/'
batch_input_glob += '*'
# get root directory of input glob pattern
base_dir = batch_input_glob.replace('?', '*')
base_dir = base_dir.split('/*').pop(0)
# check the input directory path
if not os.path.isdir(base_dir):
return ['', None, None, 'input path is not a directory']
# this line is moved here because some reason
# PIL.Image.registered_extensions() returns only PNG if you call too early
supported_extensions = [
e
for e, f in Image.registered_extensions().items()
if f in Image.OPEN
]
paths = [
Path(p)
for p in glob(batch_input_glob, recursive=batch_input_recursive)
if '.' + p.split('.').pop().lower() in supported_extensions
]
print(f'found {len(paths)} image(s)')
for path in paths:
try:
image = Image.open(path)
except UnidentifiedImageError:
# just in case, user has mysterious file...
print(f'${path} is not supported image type')
continue
# guess the output path
base_dir_last = Path(base_dir).parts[-1]
base_dir_last_idx = path.parts.index(base_dir_last)
output_dir = Path(
batch_output_dir) if batch_output_dir else Path(base_dir)
output_dir = output_dir.joinpath(
*path.parts[base_dir_last_idx + 1:]).parent
output_dir.mkdir(0o777, True, True)
# format output filename
format_info = format.Info(path, 'txt')
try:
formatted_output_filename = format.pattern.sub(
lambda m: format.format(m, format_info),
batch_output_filename_format
)
except (TypeError, ValueError) as error:
return ['', None, None, str(error)]
output_path = output_dir.joinpath(
formatted_output_filename
)
output = []
if output_path.is_file():
output.append(output_path.read_text())
if batch_output_action_on_conflict == 'ignore':
print(f'skipping {path}')
continue
ratings, tags = interrogator.interrogate(image)
processed_tags = Interrogator.postprocess_tags(
tags,
*postprocess_opts
)
# TODO: switch for less print
print(
f'found {len(processed_tags)} tags out of {len(tags)} from {path}'
)
plain_tags = ', '.join(processed_tags)
if batch_output_action_on_conflict == 'copy':
output = [plain_tags]
elif batch_output_action_on_conflict == 'prepend':
output.insert(0, plain_tags)
else:
output.append(plain_tags)
output_path.write_text(' '.join(output))
if batch_output_save_json:
output_path.with_suffix('.json').write_text(
json.dumps([ratings, tags])
)
print('all done :)')
if unload_model_after_running:
interrogator.unload()
return ['', None, None, '']
def on_ui_tabs():
with gr.Blocks(analytics_enabled=False) as tagger_interface:
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
# input components
with gr.Tabs():
with gr.TabItem(label='Single process'):
image = gr.Image(
label='Source',
source='upload',
interactive=True,
type="pil"
)
with gr.TabItem(label='Batch from directory'):
batch_input_glob = utils.preset.component(
gr.Textbox,
label='Input directory',
placeholder='/path/to/images or /path/to/images/**/*'
)
batch_input_recursive = utils.preset.component(
gr.Checkbox,
label='Use recursive with glob pattern'
)
batch_output_dir = utils.preset.component(
gr.Textbox,
label='Output directory',
placeholder='Leave blank to save images to the same path.'
)
batch_output_filename_format = utils.preset.component(
gr.Textbox,
label='Output filename format',
placeholder='Leave blank to use same filename as original.',
value='[name].[output_extension]'
)
import hashlib
with gr.Accordion(
label='Output filename formats',
open=False
):
gr.Markdown(
value=f'''
### Related to original file
- `[name]`: Original filename without extension
- `[extension]`: Original extension
- `[hash:<algorithms>]`: Original extension
Available algorithms: `{', '.join(hashlib.algorithms_available)}`
### Related to output file
- `[output_extension]`: Output extension (has no dot)
## Examples
### Original filename without extension
`[name].[output_extension]`
### Original file's hash (good for deleting duplication)
`[hash:sha1].[output_extension]`
'''
)
batch_output_action_on_conflict = utils.preset.component(
gr.Dropdown,
label='Action on exiting caption',
value='ignore',
choices=[
'ignore',
'copy',
'append',
'prepend'
]
)
batch_output_save_json = utils.preset.component(
gr.Checkbox,
label='Save with JSON'
)
submit = gr.Button(
value='Interrogate',
variant='primary'
)
info = gr.HTML()
# preset selector
with gr.Row(variant='compact'):
available_presets = utils.preset.list()
selected_preset = gr.Dropdown(
label='Preset',
choices=available_presets,
value=available_presets[0]
)
save_preset_button = gr.Button(
value=ui.save_style_symbol
)
ui.create_refresh_button(
selected_preset,
lambda: None,
lambda: {'choices': utils.preset.list()},
'refresh_preset'
)
# option components
# interrogator selector
with gr.Column():
with gr.Row(variant='compact'):
interrogator_names = utils.refresh_interrogators()
interrogator = utils.preset.component(
gr.Dropdown,
label='Interrogator',
choices=interrogator_names,
value=(
None
if len(interrogator_names) < 1 else
interrogator_names[-1]
)
)
ui.create_refresh_button(
interrogator,
lambda: None,
lambda: {'choices': utils.refresh_interrogators()},
'refresh_interrogator'
)
unload_all_models = gr.Button(
value='Unload all interrogate models'
)
threshold = utils.preset.component(
gr.Slider,
label='Threshold',
minimum=0,
maximum=1,
value=0.35
)
additional_tags = utils.preset.component(
gr.Textbox,
label='Additional tags (split by comma)',
elem_id='additioanl-tags'
)
exclude_tags = utils.preset.component(
gr.Textbox,
label='Exclude tags (split by comma)',
elem_id='exclude-tags'
)
sort_by_alphabetical_order = utils.preset.component(
gr.Checkbox,
label='Sort by alphabetical order',
)
add_confident_as_weight = utils.preset.component(
gr.Checkbox,
label='Include confident of tags matches in results'
)
replace_underscore = utils.preset.component(
gr.Checkbox,
label='Use spaces instead of underscore',
value=True
)
replace_underscore_excludes = utils.preset.component(
gr.Textbox,
label='Excudes (split by comma)',
# kaomoji from WD 1.4 tagger csv. thanks, Meow-San#5400!
value='0_0, (o)_(o), +_+, +_-, ._., <o>_<o>, <|>_<|>, =_=, >_<, 3_3, 6_9, >_o, @_@, ^_^, o_o, u_u, x_x, |_|, ||_||'
)
escape_tag = utils.preset.component(
gr.Checkbox,
label='Escape brackets',
)
unload_model_after_running = utils.preset.component(
gr.Checkbox,
label='Unload model after running',
)
# output components
with gr.Column(variant='panel'):
tags = gr.Textbox(
label='Tags',
placeholder='Found tags',
interactive=False
)
with gr.Row():
parameters_copypaste.bind_buttons(
parameters_copypaste.create_buttons(
["txt2img", "img2img"],
),
None,
tags
)
rating_confidents = gr.Label(
label='Rating confidents',
elem_id='rating-confidents'
)
tag_confidents = gr.Label(
label='Tag confidents',
elem_id='tag-confidents'
)
# register events
selected_preset.change(
fn=utils.preset.apply,
inputs=[selected_preset],
outputs=[*utils.preset.components, info]
)
save_preset_button.click(
fn=utils.preset.save,
inputs=[selected_preset, *utils.preset.components], # values only
outputs=[info]
)
unload_all_models.click(
fn=unload_interrogators,
outputs=[info]
)
for func in [image.change, submit.click]:
func(
fn=wrap_gradio_gpu_call(on_interrogate),
inputs=[
# single process
image,
# batch process
batch_input_glob,
batch_input_recursive,
batch_output_dir,
batch_output_filename_format,
batch_output_action_on_conflict,
batch_output_save_json,
# options
interrogator,
threshold,
additional_tags,
exclude_tags,
sort_by_alphabetical_order,
add_confident_as_weight,
replace_underscore,
replace_underscore_excludes,
escape_tag,
unload_model_after_running
],
outputs=[
tags,
rating_confidents,
tag_confidents,
# contains execution time, memory usage and other stuffs...
# generated from modules.ui.wrap_gradio_call
info
]
)
return [(tagger_interface, "Tagger", "tagger")]
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