stable-diffusion-webui/extensions-builtin/Lora/ui_edit_user_metadata.py

import datetime
import html
import random

import gradio as gr
import re

from modules import ui_extra_networks_user_metadata


def is_non_comma_tagset(tags):
    average_tag_length = sum(len(x) for x in tags.keys()) / len(tags)

    return average_tag_length >= 16


re_word = re.compile(r"[-_\w']+")
re_comma = re.compile(r" *, *")


def build_tags(metadata):
    tags = {}

    for _, tags_dict in metadata.get("ss_tag_frequency", {}).items():
        for tag, tag_count in tags_dict.items():
            tag = tag.strip()
            tags[tag] = tags.get(tag, 0) + int(tag_count)

    if tags and is_non_comma_tagset(tags):
        new_tags = {}

        for text, text_count in tags.items():
            for word in re.findall(re_word, text):
                if len(word) < 3:
                    continue

                new_tags[word] = new_tags.get(word, 0) + text_count

        tags = new_tags

    ordered_tags = sorted(tags.keys(), key=tags.get, reverse=True)

    return [(tag, tags[tag]) for tag in ordered_tags]


class LoraUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataEditor):
    def __init__(self, ui, tabname, page):
        super().__init__(ui, tabname, page)

        self.select_sd_version = None

        self.taginfo = None
        self.edit_activation_text = None
        self.slider_preferred_weight = None
        self.edit_notes = None

    def save_lora_user_metadata(self, name, desc, sd_version, activation_text, preferred_weight, notes):
        user_metadata = self.get_user_metadata(name)
        user_metadata["description"] = desc
        user_metadata["sd version"] = sd_version
        user_metadata["activation text"] = activation_text
        user_metadata["preferred weight"] = preferred_weight
        user_metadata["notes"] = notes

        self.write_user_metadata(name, user_metadata)

    def get_metadata_table(self, name):
        table = super().get_metadata_table(name)
        item = self.page.items.get(name, {})
        metadata = item.get("metadata") or {}

        keys = {
            'ss_sd_model_name': "Model:",
            'ss_clip_skip': "Clip skip:",
            'ss_network_module': "Kohya module:",
        }

        for key, label in keys.items():
            value = metadata.get(key, None)
            if value is not None and str(value) != "None":
                table.append((label, html.escape(value)))

        ss_training_started_at = metadata.get('ss_training_started_at')
        if ss_training_started_at:
            table.append(("Date trained:", datetime.datetime.utcfromtimestamp(float(ss_training_started_at)).strftime('%Y-%m-%d %H:%M')))

        ss_bucket_info = metadata.get("ss_bucket_info")
        if ss_bucket_info and "buckets" in ss_bucket_info:
            resolutions = {}
            for _, bucket in ss_bucket_info["buckets"].items():
                resolution = bucket["resolution"]
                resolution = f'{resolution[1]}x{resolution[0]}'

                resolutions[resolution] = resolutions.get(resolution, 0) + int(bucket["count"])

            resolutions_list = sorted(resolutions.keys(), key=resolutions.get, reverse=True)
            resolutions_text = html.escape(", ".join(resolutions_list[0:4]))
            if len(resolutions) > 4:
                resolutions_text += ", ..."
                resolutions_text = f"<span title='{html.escape(', '.join(resolutions_list))}'>{resolutions_text}</span>"

            table.append(('Resolutions:' if len(resolutions_list) > 1 else 'Resolution:', resolutions_text))

        image_count = 0
        for _, params in metadata.get("ss_dataset_dirs", {}).items():
            image_count += int(params.get("img_count", 0))

        if image_count:
            table.append(("Dataset size:", image_count))

        return table

    def put_values_into_components(self, name):
        user_metadata = self.get_user_metadata(name)
        values = super().put_values_into_components(name)

        item = self.page.items.get(name, {})
        metadata = item.get("metadata") or {}

        tags = build_tags(metadata)
        gradio_tags = [(tag, str(count)) for tag, count in tags[0:24]]

        return [
            *values[0:5],
            item.get("sd_version", "Unknown"),
            gr.HighlightedText.update(value=gradio_tags, visible=True if tags else False),
            user_metadata.get('activation text', ''),
            float(user_metadata.get('preferred weight', 0.0)),
            gr.update(visible=True if tags else False),
            gr.update(value=self.generate_random_prompt_from_tags(tags), visible=True if tags else False),
        ]

    def generate_random_prompt(self, name):
        item = self.page.items.get(name, {})
        metadata = item.get("metadata") or {}
        tags = build_tags(metadata)

        return self.generate_random_prompt_from_tags(tags)

    def generate_random_prompt_from_tags(self, tags):
        max_count = None
        res = []
        for tag, count in tags:
            if not max_count:
                max_count = count

            v = random.random() * max_count
            if count > v:
                res.append(tag)

        return ", ".join(sorted(res))

    def create_extra_default_items_in_left_column(self):

        # this would be a lot better as gr.Radio but I can't make it work
        self.select_sd_version = gr.Dropdown(['SD1', 'SD2', 'SDXL', 'Unknown'], value='Unknown', label='Stable Diffusion version', interactive=True)

    def create_editor(self):
        self.create_default_editor_elems()

        self.taginfo = gr.HighlightedText(label="Training dataset tags")
        self.edit_activation_text = gr.Text(label='Activation text', info="Will be added to prompt along with Lora")
        self.slider_preferred_weight = gr.Slider(label='Preferred weight', info="Set to 0 to disable", minimum=0.0, maximum=2.0, step=0.01)

        with gr.Row() as row_random_prompt:
            with gr.Column(scale=8):
                random_prompt = gr.Textbox(label='Random prompt', lines=4, max_lines=4, interactive=False)

            with gr.Column(scale=1, min_width=120):
                generate_random_prompt = gr.Button('Generate', size="lg", scale=1)

        self.edit_notes = gr.TextArea(label='Notes', lines=4)

        generate_random_prompt.click(fn=self.generate_random_prompt, inputs=[self.edit_name_input], outputs=[random_prompt], show_progress=False)

        def select_tag(activation_text, evt: gr.SelectData):
            tag = evt.value[0]

            words = re.split(re_comma, activation_text)
            if tag in words:
                words = [x for x in words if x != tag and x.strip()]
                return ", ".join(words)

            return activation_text + ", " + tag if activation_text else tag

        self.taginfo.select(fn=select_tag, inputs=[self.edit_activation_text], outputs=[self.edit_activation_text], show_progress=False)

        self.create_default_buttons()

        viewed_components = [
            self.edit_name,
            self.edit_description,
            self.html_filedata,
            self.html_preview,
            self.edit_notes,
            self.select_sd_version,
            self.taginfo,
            self.edit_activation_text,
            self.slider_preferred_weight,
            row_random_prompt,
            random_prompt,
        ]

        self.button_edit\
            .click(fn=self.put_values_into_components, inputs=[self.edit_name_input], outputs=viewed_components)\
            .then(fn=lambda: gr.update(visible=True), inputs=[], outputs=[self.box])

        edited_components = [
            self.edit_description,
            self.select_sd_version,
            self.edit_activation_text,
            self.slider_preferred_weight,
            self.edit_notes,
        ]

        self.setup_save_handler(self.button_save, self.save_lora_user_metadata, edited_components)