fix install
dr413677671
parent
0fa8904d0f
commit
0a9bb30da7
38
README.md
38
README.md
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@ -76,7 +76,7 @@
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<!-- ABOUT THE PROJECT -->
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<div align=center>
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<img src='./prompt-gallery/images/front.JPG'>
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<img src='./images/front.JPG'>
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</div>
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## About The Project
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@ -124,30 +124,22 @@ Run git clone to get the prompt-gallery.
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Make sure you cloned the [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) before. If not check out [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) to install it first.
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You have two options now. :>
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Follow instructions on [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) to start webui
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Option A:
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Goto Tab extensions in the webui and paste:
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Manually copy prompt-gallery into stable-diffusion-webui.
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1. paste https://github.com/dr413677671/PromptGallery-stable-diffusion-webui.git into textbox "URL for extension's git repository"
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> copy ./PromptGallery-stable-diffusion-webui/prompt-gallery to stable-diffusion-webui-project-path/extensions
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2. Set Prompt Gallery as "Local directory name"
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> copy ./PromptGallery-stable-diffusion-webui/scripts/prompt_gallery.py to stable-diffusion-webui-project-path/scripts
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Option B:
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> Alternatively, goto the cloned promptgallery-stable-diffusion-webui folder and run
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```sh
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python setup.py <stable-diffusion-webui-project-path>
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```
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<p align="right">(<a href="#readme-top">back to top</a>)</p>
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## Usage
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Follow instructions on [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) to start webui
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View the video tutorial to use prompt-gallery:
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<a href="https://www.youtube.com/watch?v=9U6-moIJUkk">View Demo</a>
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@ -207,41 +199,41 @@ Teamplate:
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Select avatar (model for demo) -> Select prompt-sets -> Click "send WebUI"
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Checkout the downloaded Images
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### Populate previews and QC
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For instance having added two prompt-sets, and we would like to add preview pictures for them.
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Goto tab "txt2img" and Select "Prompt Gallery" in tab "scripts"
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Upload yaml library of avatar first and select avatar.
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Add default prompts and upload prompt-set yaml library.
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Wait for stable-diffusion-webui generate previews automatically.
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Pick the best image for preview.
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Check it out in Prompt Gallery.
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You could always inspect you pictures manually in prompt-gallery-directory/assets/preview/
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Before Width: | Height: | Size: 42 KiB After Width: | Height: | Size: 42 KiB |
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Before Width: | Height: | Size: 42 KiB After Width: | Height: | Size: 42 KiB |
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@ -1 +0,0 @@
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path_recorder.txt
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@ -1,55 +0,0 @@
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import os
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import shutil
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import time
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import stat
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import gradio as gr
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import modules.extras
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import modules.ui
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from modules.shared import opts, cmd_opts
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from modules import shared, scripts
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from modules import script_callbacks
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from pathlib import Path
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from typing import List, Tuple
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import uvicorn
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from uvicorn import Config
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from fastapi import FastAPI
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from fastapi.staticfiles import StaticFiles
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import contextlib
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import threading
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import requests
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from fastapi.middleware.cors import CORSMiddleware
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def on_ui_settings():
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app = FastAPI()
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app.mount('/', StaticFiles(directory='./extensions/prompt-gallery',html=True))
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config = Config(app=app, host='localhost',port=5173, log_level="info", loop="asyncio", limit_max_requests=1)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"]
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)
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thread = threading.Thread(target= uvicorn.run, kwargs={'app':app, 'host': 'localhost', 'port':5173})
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thread.start()
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tmp = requests.get("http://localhost:5173")
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while tmp.status_code != 204 and tmp.status_code != 200:
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time.sleep(0.01)
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tmp = requests.get("http://localhost:5173")
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pass
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# thread.join()
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def on_ui_tabs():
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html = """<iframe id="tab_iframe" style="width: 100%; min-height: 864px; padding: 0;margin: 0;border: none;" src="http://localhost:5173/" frameborder="0" marginwidth="0" marginheight="0"></iframe>"""
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with gr.Blocks(analytics_enabled=False, elem_id="prompt_gallery") as prompt_gallery:
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prompt_gallery = gr.HTML(html)
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return (prompt_gallery , "Prompt Gallery", "prompt_gallery"),
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script_callbacks.on_ui_tabs(on_ui_tabs)
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script_callbacks.on_ui_settings(on_ui_settings)
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Binary file not shown.
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After Width: | Height: | Size: 55 KiB |
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@ -0,0 +1,15 @@
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import os
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import shutil
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import json
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import launch
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if not launch.is_installed("pyyaml"):
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launch.run_pip("install pyyaml", "requirements for Prompt Gallery")
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current_dir= os.path.abspath(os.path.dirname(__file__))
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trg = os.path.join(os.path.join(os.path.join(current_dir, os.path.pardir), os.path.pardir), "scripts/prompt_gallery.py")
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shutil.copyfile(os.path.join(os.path.join(current_dir,"paste_this_to_webui_scripts_folder"),"prompt_gallery.py"), trg)
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name = os.path.basename(current_dir)
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with open(os.path.join(current_dir, os.path.join(os.path.join(current_dir, os.path.pardir), "prompt_gallery_name.json")), 'w') as fd:
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json.dump({'name': name}, fd)
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@ -0,0 +1,585 @@
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import copy
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import os
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import random
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import sys
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import traceback
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import shlex
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import yaml
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import platform
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import subprocess as sp
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import shutil
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import tempfile
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import gradio as gr
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import csv
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import typing
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import base64
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import io
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from PIL import Image
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import mimetypes
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mimetypes.init()
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mimetypes.add_type('application/javascript', '.js')
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import modules.generation_parameters_copypaste as parameters_copypaste
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from modules.generation_parameters_copypaste import image_from_url_text
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import modules.scripts as scripts
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from modules.processing import Processed, process_images
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from modules.shared import opts, cmd_opts, state
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import modules.shared as shared
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if '__file__' in locals().keys():
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root_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
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root_path = os.path.join(root_path, "../")
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else:
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if platform.system() == "Windows":
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root_path = "./"
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else:
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root_path = "./"
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# OUTPATH_SAMPLES = root_path + "/outputs/preview_outputs/preview/"
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# OUTPATH_GRIDS = root_path + "/outputs/preview_outputs/grid/"
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OUTPATH_SAMPLES = './extensions/prompt-gallery/assets/preview/'
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OUTPATH_GRIDS = './extensions/prompt-gallery/assets/grid/'
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BATCH_SIZE = 4
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N_ITER = 2
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STEPS = 30
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CFG_SCALE = 11.5
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WIDTH = 512
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HEIGHT = 768
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SAMPLER_INDEX = 1
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RESTORE_FACE = 'true'
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TILING = 'false'
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DO_NOT_SAVE_GRID = 'false'
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SD_MODEL = '925997e9'
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EXCLUDED_TAGS = ['']
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global SKIP_EXISTS
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SKIP_EXISTS = True
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OUTPUTS_DICT = list()
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OUTPUTS = {}
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rawDict = {}
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qc_dict = {}
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trg_img = ''
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current_folder = ''
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map_sampler_to_idx = {
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'Euler a': 0,
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'Euler': 1,
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'LMS': 2,
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'Heun': 3,
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'DPM2': 4,
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'DPM2 a': 5,
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'DPM fast': 6,
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'DPM adaptive': 7,
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'LMS Karras': 8,
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'DPM2 Karras': 9,
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'DPM2 a Karras': 10,
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'DDIM': 11,
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'PLMS': 12}
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map_keys = {
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"value": "prompt",
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"negative": "negative_prompt"}
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map_param = {
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"sd_model": "sd_model",
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"outpath_samples": "outpath_samples",
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"outpath_grids": "outpath_grids",
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"prompt_for_display": "prompt_for_display",
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"styles": "styles",
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"Seed": "seed",
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"Variation seed strength": "subseed_strength",
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"Variation seed": "subseed",
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"seed_resize_from_h": "seed_resize_from_h",
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"seed_resize_from_w": "seed_resize_from_w",
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"Sampler": "sampler_index",
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"batch_size": "batch_size",
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"n_iter": "n_iter",
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"Steps": "steps",
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"CFG scale": "cfg_scale",
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"width": "width",
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"height": "height",
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"restore_faces": "restore_faces",
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"tiling": "tiling",
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"do_not_save_samples": "do_not_save_samples",
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"do_not_save_grid": "do_not_save_grid"}
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def process_string_tag(tag):
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return tag
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def process_int_tag(tag):
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return int(tag)
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def process_float_tag(tag):
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return float(tag)
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def process_boolean_tag(tag):
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return True if (tag == "true") else False
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prompt_tags = {
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"sd_model": None,
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"outpath_samples": process_string_tag,
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"outpath_grids": process_string_tag,
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"prompt_for_display": process_string_tag,
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"prompt": process_string_tag,
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"negative_prompt": process_string_tag,
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"styles": process_string_tag,
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"seed": process_int_tag,
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"subseed_strength": process_float_tag,
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"subseed": process_int_tag,
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"seed_resize_from_h": process_int_tag,
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"seed_resize_from_w": process_int_tag,
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"sampler_index": process_int_tag,
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"batch_size": process_int_tag,
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"n_iter": process_int_tag,
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"steps": process_int_tag,
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"cfg_scale": process_float_tag,
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"width": process_int_tag,
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"height": process_int_tag,
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"restore_faces": process_boolean_tag,
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"tiling": process_boolean_tag,
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"do_not_save_samples": process_boolean_tag,
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"do_not_save_grid": process_boolean_tag
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}
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avatar_prompts = list()
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avatar_names = list()
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avatar_negatives = list()
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avatar_name = ""
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def cmdargs(line):
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args = shlex.split(line)
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pos = 0
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res = {}
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while pos < len(args):
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arg = args[pos]
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assert arg.startswith("--"), f'must start with "--": {arg}'
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tag = arg[2:]
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func = prompt_tags.get(tag, None)
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assert func, f'unknown commandline option: {arg}'
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assert pos+1 < len(args), f'missing argument for command line option {arg}'
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val = args[pos+1]
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res[tag] = func(val)
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pos += 2
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return res
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def add_param(key, value, cur_str):
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cur_str += '--{key} {value} '.format(key=key, value=value)
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return cur_str
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def parse_size(i_width, i_height, str_size, cur_str):
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i_width = str_size.split('x')[0]
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i_height = str_size.split('x')[1]
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def parse_virariant_size(str_size, cur_str):
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width = str_size.split('x')[0]
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height = str_size.split('x')[1]
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cur_str = add_param('seed_resize_from_w', width, cur_str)
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cur_str = add_param('seed_resize_from_h', height, cur_str)
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return cur_str
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def parse_param(param_str):
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m_batch_size = BATCH_SIZE
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m_n_iter = N_ITER
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m_steps = STEPS
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m_cfg_scale = CFG_SCALE
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m_width = WIDTH
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m_height = HEIGHT
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m_sampler_index = SAMPLER_INDEX
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# m_tiling = TILING
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m_restore_faces = RESTORE_FACE
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m_do_not_save_grid = DO_NOT_SAVE_GRID
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# m_sd_model = sd_model
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cur_line = ""
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for item in param_str.split(', '):
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if item == '':
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continue
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group = item.split(': ')
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key = group[0]
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value = group[1]
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if key == 'Steps':
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m_steps = value
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elif key == "CFG scale":
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m_cfg_scale = value
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elif value == 'Sampler':
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m_sampler_index = map_sampler_to_idx[value]
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elif key == 'Size':
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parse_size(m_width, m_height, value, cur_line)
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elif key == 'Seed resize from':
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cur_line = parse_virariant_size(value, cur_line)
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elif key == 'Seed':
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cur_line = add_param("seed", value, cur_line)
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elif key == 'Variation seed strength':
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cur_line = add_param("subseed_strength", value, cur_line)
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elif key == 'Variation seed':
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cur_line = add_param("subseed", value, cur_line)
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# elif key == 'Model hash':
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# cur_line = add_param("sd_model", m_sd_model, cur_line)
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cur_line = add_param("batch_size", m_batch_size, cur_line)
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cur_line = add_param("n_iter", m_n_iter, cur_line)
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cur_line = add_param("steps", m_steps, cur_line)
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cur_line = add_param("cfg_scale", m_cfg_scale, cur_line)
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cur_line = add_param("sampler_index", m_sampler_index, cur_line)
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cur_line = add_param("width", m_width, cur_line)
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cur_line = add_param("height", m_height, cur_line)
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cur_line = add_param("restore_faces", m_restore_faces, cur_line)
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# cur_line = add_param("tiling", m_tiling, cur_line)
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cur_line = add_param("do_not_save_grid", m_do_not_save_grid, cur_line)
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return cur_line
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def parse_yaml_dict(rawDict, tag, avatar_prompt, avatar_name, default_negative):
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# depth-first-search
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if 'value' in rawDict.keys() or 'negative' in rawDict.keys():
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if SKIP_EXISTS:
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if os.path.exists(OUTPATH_SAMPLES + tag + '/' + avatar_name+'.png') or os.path.exists(OUTPATH_SAMPLES + tag + '\\' + 'Not-available.png'):
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print("Skip "+str(tag))
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return ""
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cur = ""
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parsed_param = False
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m_positive = avatar_prompt
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m_negative = default_negative
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for item in rawDict.items():
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key = item[0]
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value = item[1]
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if key == 'param':
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params = parse_param(rawDict['param'])
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parsed_param = True
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elif key == 'value':
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m_positive = value + m_positive
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elif key == 'negative':
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m_negative = value +','+ m_negative
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cur += "--{key} \"{value}\" ".format(key='prompt', value= m_positive)
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cur += "--{key} \"{value}\" ".format(key='negative_prompt', value= m_negative)
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if parsed_param == False:
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params = parse_param("")
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cur += params
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cur = add_param('outpath_samples', '\"'+OUTPATH_SAMPLES + str(tag)+'\"', cur)
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cur = add_param('outpath_grids', '\"'+OUTPATH_GRIDS + str(tag)+'\"', cur)
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return cur
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else:
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for item in rawDict.items():
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key = item[0]
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ret = parse_yaml_dict(rawDict[key], tag if key=='' else key, avatar_prompt, avatar_name, default_negative)
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if len(ret) != 0:
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if tag not in EXCLUDED_TAGS:
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OUTPUTS_DICT.append({'name': key,
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'prompt': item[1]['value'] if 'value' in item[1].keys() else '',
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'negative_prompt': item[1]['negative'] if 'negative' in item[1].keys() else ''})
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if tag in OUTPUTS.keys():
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OUTPUTS[tag].append(ret)
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else:
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OUTPUTS[tag] = [ret]
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return ""
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def rename_preview(avatar_name):
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if avatar_name == '':
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print("Please select avatar name first.")
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return
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root = OUTPATH_SAMPLES
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for folder in os.listdir(root):
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files = os.listdir(root + folder)
|
||||
if 'Not-available.png' in files:
|
||||
print('Skip '+ folder + ' not available.')
|
||||
continue
|
||||
if avatar_name + '.png' in files:
|
||||
continue
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' in files:
|
||||
files.remove(each_avatar + '.png')
|
||||
if len(files) == 1:
|
||||
os.rename(root + folder + '/' + files[0], root + folder + '/' + avatar_name + '.png')
|
||||
else:
|
||||
print('There are 0 or more than 1 files in ' + folder)
|
||||
|
||||
def load_prompt_file(file):
|
||||
if (file is None):
|
||||
lines = []
|
||||
else:
|
||||
lines = [x.strip() for x in file.decode('utf8', errors='ignore').split("\n")]
|
||||
|
||||
return None, "\n".join(lines), gr.update(lines=7)
|
||||
|
||||
def copy_from_prompt_app():
|
||||
return []
|
||||
|
||||
def open_folder(f):
|
||||
if not os.path.exists(f):
|
||||
print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
|
||||
return
|
||||
elif not os.path.isdir(f):
|
||||
print(f"""
|
||||
WARNING
|
||||
An open_folder request was made with an argument that is not a folder.
|
||||
This could be an error or a malicious attempt to run code on your computer.
|
||||
Requested path was: {f}
|
||||
""", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not shared.cmd_opts.hide_ui_dir_config:
|
||||
path = os.path.normpath(f)
|
||||
if platform.system() == "Windows":
|
||||
os.startfile(path)
|
||||
elif platform.system() == "Darwin":
|
||||
sp.Popen(["open", path])
|
||||
else:
|
||||
sp.Popen(["xdg-open", path])
|
||||
|
||||
class PromptStyle(typing.NamedTuple):
|
||||
name: str
|
||||
prompt: str
|
||||
negative_prompt: str
|
||||
|
||||
def save_styles() -> None:
|
||||
if len(OUTPUTS.keys()) == 0:
|
||||
return
|
||||
path = root_path + '/styles.csv'
|
||||
# Write to temporary file first, so we don't nuke the file if something goes wrong
|
||||
fd, temp_path = tempfile.mkstemp(".csv")
|
||||
with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file:
|
||||
# _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple,
|
||||
# and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict()
|
||||
writer = csv.DictWriter(file, fieldnames=PromptStyle._fields)
|
||||
writer.writeheader()
|
||||
for row in OUTPUTS_DICT:
|
||||
writer.writerow({'name': row['name'], 'prompt': row['prompt'], 'negative_prompt': row['negative_prompt']})
|
||||
# writer.writerows(style._asdict() for k, style in self.styles.items())
|
||||
|
||||
# Always keep a backup file around
|
||||
if os.path.exists(path):
|
||||
shutil.move(path, path + ".bak")
|
||||
shutil.move(temp_path, path)
|
||||
|
||||
def load_prompt(file, default_negative, dropdown, skip_exist):
|
||||
global SKIP_EXISTS
|
||||
SKIP_EXISTS = skip_exist
|
||||
if dropdown == '':
|
||||
return
|
||||
rawDict = yaml.load(file, Loader = yaml.BaseLoader)
|
||||
default_negative = default_negative + ',' + avatar_negatives[avatar_names.index(dropdown)]
|
||||
parse_yaml_dict(rawDict, "", avatar_prompts[avatar_names.index(dropdown)], dropdown, default_negative)
|
||||
prompt_txt = ""
|
||||
keys = list(filter(lambda x: x not in EXCLUDED_TAGS, OUTPUTS.keys()))
|
||||
for style in keys:
|
||||
for each_line in OUTPUTS[style]:
|
||||
prompt_txt += each_line + '\n'
|
||||
return [prompt_txt, gr.Row.update(visible=True)]
|
||||
|
||||
def load_avartar(avatar_dict, customize_tags_positive):
|
||||
avatars = yaml.load(avatar_dict, yaml.BaseLoader)
|
||||
|
||||
for name, prompt in avatars.items():
|
||||
avatar_names.append(name)
|
||||
if 'value' in prompt.keys():
|
||||
avatar_prompts.append(customize_tags_positive + ', ' + prompt['value'])
|
||||
if 'negative' in prompt.keys():
|
||||
avatar_negatives.append(prompt['negative'])
|
||||
return [gr.Dropdown.update(choices=avatar_names, value=avatar_names[0]), gr.Column.update(visible=True), gr.Group.update(visible=True)]
|
||||
|
||||
def scan_outputs(avatar_name):
|
||||
if avatar_name is None or len(avatar_name) == 0:
|
||||
print("Please select avatar name first.")
|
||||
return
|
||||
root = OUTPATH_SAMPLES
|
||||
global qc_dict
|
||||
qc_dict = {}
|
||||
for folder in os.listdir(root):
|
||||
if os.path.isdir(root + folder) == False:
|
||||
continue
|
||||
|
||||
files = os.listdir(root + folder)
|
||||
if 'Not-available.png' in files:
|
||||
print('Skip '+ folder + ' not available.')
|
||||
continue
|
||||
if avatar_name + '.png' in files:
|
||||
continue
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' in files:
|
||||
files.remove(each_avatar + '.png')
|
||||
if len(files) == 0:
|
||||
continue
|
||||
qc_dict[folder] = [root + folder + '/' + file for file in files]
|
||||
|
||||
if len(qc_dict.keys()) == 0:
|
||||
return gr.Dropdown.update(choices=[])
|
||||
return gr.Dropdown.update(choices=list(qc_dict.keys()), value=list(qc_dict.keys())[0])
|
||||
|
||||
def update_gallery(dropdown, avatar):
|
||||
root = OUTPATH_SAMPLES
|
||||
global trg_img, current_folder
|
||||
current_folder = root + dropdown
|
||||
trg_img = root + dropdown + '/' + avatar + '.png'
|
||||
return qc_dict[dropdown]
|
||||
|
||||
def clean_select_picture(filename):
|
||||
if current_folder == '':
|
||||
print("Please select qc tag.")
|
||||
return
|
||||
for file in os.listdir(current_folder):
|
||||
is_avatar = False
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' == file:
|
||||
is_avatar = True
|
||||
break
|
||||
if os.path.splitext(file)[0] in filename:
|
||||
os.rename(current_folder+'/'+file, trg_img)
|
||||
elif is_avatar == False:
|
||||
os.remove(current_folder+'/'+file)
|
||||
|
||||
def image_url(filedata):
|
||||
if type(filedata) == dict and filedata["is_file"]:
|
||||
filename = filedata["name"]
|
||||
tempdir = os.path.normpath(tempfile.gettempdir())
|
||||
normfn = os.path.normpath(filename)
|
||||
assert normfn.startswith(tempdir), 'trying to open image file not in temporary directory'
|
||||
|
||||
image = Image.open(filename)
|
||||
clean_select_picture(os.path.basename(filename))
|
||||
return Image.open(filename)
|
||||
|
||||
if type(filedata) == list:
|
||||
if len(filedata) == 0:
|
||||
return None
|
||||
|
||||
filedata = filedata[0]
|
||||
|
||||
if filedata.startswith("data:image/png;base64,"):
|
||||
filedata = filedata[len("data:image/png;base64,"):]
|
||||
|
||||
filedata = base64.decodebytes(filedata.encode('utf-8'))
|
||||
image = Image.open(io.BytesIO(filedata))
|
||||
return image
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
class Script(scripts.Script):
|
||||
def title(self):
|
||||
return "Prompt gallery"
|
||||
|
||||
def ui(self, is_img2img):
|
||||
with gr.Group():
|
||||
with gr.Column():
|
||||
label_avatar = gr.Label("Upload avatars config")
|
||||
avatar_dict = gr.File(label="Upload avatar prompt inputs", type='bytes')
|
||||
|
||||
# copy_from_app_button = gr.Button("Copy From Prompt Preview")
|
||||
|
||||
with gr.Group():
|
||||
with gr.Column(visible=False) as avatar_col:
|
||||
label_presets = gr.Label("Presets")
|
||||
dropdown = gr.Dropdown(label="Choose avatar", choices=[""], value="", type="value", elem_id="dropdown")
|
||||
dropdown.save_to_config = True
|
||||
with gr.Row():
|
||||
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False)
|
||||
skip_exist = gr.Checkbox(value=True, label="skip exist")
|
||||
default_negative = gr.Textbox(label="default_negative", lines=1)
|
||||
default_positive = gr.Textbox(label="default_positive", lines=1)
|
||||
prompt_dict = gr.File(label="Upload prompt dictionary", type='bytes')
|
||||
with gr.Row(visible = False) as save_prompts:
|
||||
open_button = gr.Button("Open outputs directory")
|
||||
export_button = gr.Button("Export to WebUI style")
|
||||
prompt_display = gr.Textbox(label="List of prompt inputs", lines=1)
|
||||
|
||||
|
||||
prompt_dict.change(fn=load_prompt, inputs=[prompt_dict, default_negative, dropdown, skip_exist], outputs=[prompt_display, save_prompts])
|
||||
open_button.click(fn=lambda: open_folder(OUTPATH_SAMPLES), inputs=[], outputs=[])
|
||||
export_button.click(fn=save_styles, inputs=[], outputs=[])
|
||||
|
||||
with gr.Group(visible=False) as qc_widgets:
|
||||
label_preview = gr.Label("QC preview")
|
||||
with gr.Row():
|
||||
qc_refresh = gr.Button("QC scan")
|
||||
preview_dropdown = gr.Dropdown(label="Select prompts", choices=[""], value="", type="value", elem_id="dropdown")
|
||||
preview_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"preview_gallery").style(grid=4)
|
||||
qc_refresh.click(fn=scan_outputs, inputs=[dropdown], outputs=preview_dropdown)
|
||||
with gr.Row():
|
||||
qc_show = gr.Button(f"Show pics")
|
||||
qc_select = gr.Button(f"Select")
|
||||
rename_button = gr.Button("Auto rename")
|
||||
selected_img = gr.Image(label="Selected",show_label=False, source="upload", interactive=True, type="pil").style(height=480)
|
||||
qc_show.click(fn=update_gallery, inputs=[preview_dropdown, dropdown], outputs=preview_gallery)
|
||||
qc_select.click(
|
||||
fn=lambda x: image_url(x),
|
||||
_js="extract_image_from_gallery",
|
||||
inputs=[preview_gallery],
|
||||
outputs=[selected_img],
|
||||
)
|
||||
# qc_select.click(fn=select_picture, inputs=[dropdown, preview_dropdown, preview_gallery], outputs=[])
|
||||
rename_button.click(fn=rename_preview, inputs=[dropdown], outputs=[])
|
||||
# qc_select.click(fn=scan_outputs, inputs=[], outputs=[preview_dropdown])
|
||||
|
||||
avatar_dict.change(fn=load_avartar, inputs=[avatar_dict, default_positive], outputs=[dropdown, avatar_col, qc_widgets])
|
||||
return [checkbox_iterate, avatar_dict, prompt_dict, default_negative, default_positive, dropdown, prompt_display, rename_button, label_avatar, open_button, export_button, skip_exist, label_presets, label_preview, preview_dropdown, preview_gallery, qc_select, qc_refresh, qc_show, selected_img]
|
||||
|
||||
def run(self, p, checkbox_iterate, avatar_dict, prompt_dict, default_negative, default_positive, dropdown, prompt_display, rename_button, label_avatar, open_button, export_button, skip_exist, label_presets, label_preview, preview_dropdown, preview_gallery, qc_select, qc_refresh, qc_show, selected_img):
|
||||
lines = [x.strip() for x in prompt_display.splitlines()]
|
||||
lines = [x for x in lines if len(x) > 0]
|
||||
|
||||
p.do_not_save_grid = True
|
||||
|
||||
job_count = 0
|
||||
jobs = []
|
||||
|
||||
for line in lines:
|
||||
if "--" in line:
|
||||
try:
|
||||
args = cmdargs(line)
|
||||
except Exception:
|
||||
print(f"Error parsing line [line] as commandline:", file=sys.stderr)
|
||||
print(traceback.format_exc(), file=sys.stderr)
|
||||
args = {"prompt": line}
|
||||
else:
|
||||
args = {"prompt": line}
|
||||
|
||||
n_iter = args.get("n_iter", 1)
|
||||
if n_iter != 1:
|
||||
job_count += n_iter
|
||||
else:
|
||||
job_count += 1
|
||||
|
||||
jobs.append(args)
|
||||
|
||||
print(f"Will process {len(lines)} lines in {job_count} jobs.")
|
||||
if (checkbox_iterate and p.seed == -1):
|
||||
p.seed = int(random.randrange(4294967294))
|
||||
|
||||
state.job_count = job_count
|
||||
|
||||
images = []
|
||||
for n, args in enumerate(jobs):
|
||||
state.job = f"{state.job_no + 1} out of {state.job_count}"
|
||||
|
||||
copy_p = copy.copy(p)
|
||||
for k, v in args.items():
|
||||
setattr(copy_p, k, v)
|
||||
|
||||
proc = process_images(copy_p)
|
||||
images += proc.images
|
||||
|
||||
if (checkbox_iterate):
|
||||
p.seed = p.seed + (p.batch_size * p.n_iter)
|
||||
|
||||
OUTPUTS = {}
|
||||
rawDict = {}
|
||||
|
||||
return Processed(p, images, p.seed, "")
|
||||
|
|
@ -1,585 +1,57 @@
|
|||
import copy
|
||||
import os
|
||||
import random
|
||||
import sys
|
||||
import traceback
|
||||
import shlex
|
||||
import yaml
|
||||
import platform
|
||||
import subprocess as sp
|
||||
import shutil
|
||||
import tempfile
|
||||
import time
|
||||
import stat
|
||||
import gradio as gr
|
||||
import csv
|
||||
import typing
|
||||
import base64
|
||||
import io
|
||||
from PIL import Image
|
||||
import mimetypes
|
||||
mimetypes.init()
|
||||
mimetypes.add_type('application/javascript', '.js')
|
||||
|
||||
import modules.generation_parameters_copypaste as parameters_copypaste
|
||||
from modules.generation_parameters_copypaste import image_from_url_text
|
||||
import modules.scripts as scripts
|
||||
from modules.processing import Processed, process_images
|
||||
|
||||
from modules.shared import opts, cmd_opts, state
|
||||
import modules.shared as shared
|
||||
|
||||
if '__file__' in locals().keys():
|
||||
root_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
||||
root_path = os.path.join(root_path, "../")
|
||||
else:
|
||||
if platform.system() == "Windows":
|
||||
root_path = "./"
|
||||
else:
|
||||
root_path = "./"
|
||||
|
||||
# OUTPATH_SAMPLES = root_path + "/outputs/preview_outputs/preview/"
|
||||
# OUTPATH_GRIDS = root_path + "/outputs/preview_outputs/grid/"
|
||||
OUTPATH_SAMPLES = './extensions/prompt-gallery/assets/preview/'
|
||||
OUTPATH_GRIDS = './extensions/prompt-gallery/assets/grid/'
|
||||
|
||||
BATCH_SIZE = 4
|
||||
N_ITER = 2
|
||||
STEPS = 30
|
||||
CFG_SCALE = 11.5
|
||||
WIDTH = 512
|
||||
HEIGHT = 768
|
||||
SAMPLER_INDEX = 1
|
||||
RESTORE_FACE = 'true'
|
||||
TILING = 'false'
|
||||
DO_NOT_SAVE_GRID = 'false'
|
||||
SD_MODEL = '925997e9'
|
||||
|
||||
EXCLUDED_TAGS = ['']
|
||||
global SKIP_EXISTS
|
||||
SKIP_EXISTS = True
|
||||
|
||||
OUTPUTS_DICT = list()
|
||||
OUTPUTS = {}
|
||||
rawDict = {}
|
||||
qc_dict = {}
|
||||
trg_img = ''
|
||||
current_folder = ''
|
||||
|
||||
map_sampler_to_idx = {
|
||||
'Euler a': 0,
|
||||
'Euler': 1,
|
||||
'LMS': 2,
|
||||
'Heun': 3,
|
||||
'DPM2': 4,
|
||||
'DPM2 a': 5,
|
||||
'DPM fast': 6,
|
||||
'DPM adaptive': 7,
|
||||
'LMS Karras': 8,
|
||||
'DPM2 Karras': 9,
|
||||
'DPM2 a Karras': 10,
|
||||
'DDIM': 11,
|
||||
'PLMS': 12}
|
||||
|
||||
map_keys = {
|
||||
"value": "prompt",
|
||||
"negative": "negative_prompt"}
|
||||
|
||||
map_param = {
|
||||
"sd_model": "sd_model",
|
||||
"outpath_samples": "outpath_samples",
|
||||
"outpath_grids": "outpath_grids",
|
||||
"prompt_for_display": "prompt_for_display",
|
||||
"styles": "styles",
|
||||
"Seed": "seed",
|
||||
"Variation seed strength": "subseed_strength",
|
||||
"Variation seed": "subseed",
|
||||
"seed_resize_from_h": "seed_resize_from_h",
|
||||
"seed_resize_from_w": "seed_resize_from_w",
|
||||
"Sampler": "sampler_index",
|
||||
"batch_size": "batch_size",
|
||||
"n_iter": "n_iter",
|
||||
"Steps": "steps",
|
||||
"CFG scale": "cfg_scale",
|
||||
"width": "width",
|
||||
"height": "height",
|
||||
"restore_faces": "restore_faces",
|
||||
"tiling": "tiling",
|
||||
"do_not_save_samples": "do_not_save_samples",
|
||||
"do_not_save_grid": "do_not_save_grid"}
|
||||
|
||||
def process_string_tag(tag):
|
||||
return tag
|
||||
|
||||
|
||||
def process_int_tag(tag):
|
||||
return int(tag)
|
||||
|
||||
|
||||
def process_float_tag(tag):
|
||||
return float(tag)
|
||||
|
||||
|
||||
def process_boolean_tag(tag):
|
||||
return True if (tag == "true") else False
|
||||
|
||||
|
||||
prompt_tags = {
|
||||
"sd_model": None,
|
||||
"outpath_samples": process_string_tag,
|
||||
"outpath_grids": process_string_tag,
|
||||
"prompt_for_display": process_string_tag,
|
||||
"prompt": process_string_tag,
|
||||
"negative_prompt": process_string_tag,
|
||||
"styles": process_string_tag,
|
||||
"seed": process_int_tag,
|
||||
"subseed_strength": process_float_tag,
|
||||
"subseed": process_int_tag,
|
||||
"seed_resize_from_h": process_int_tag,
|
||||
"seed_resize_from_w": process_int_tag,
|
||||
"sampler_index": process_int_tag,
|
||||
"batch_size": process_int_tag,
|
||||
"n_iter": process_int_tag,
|
||||
"steps": process_int_tag,
|
||||
"cfg_scale": process_float_tag,
|
||||
"width": process_int_tag,
|
||||
"height": process_int_tag,
|
||||
"restore_faces": process_boolean_tag,
|
||||
"tiling": process_boolean_tag,
|
||||
"do_not_save_samples": process_boolean_tag,
|
||||
"do_not_save_grid": process_boolean_tag
|
||||
}
|
||||
|
||||
avatar_prompts = list()
|
||||
avatar_names = list()
|
||||
avatar_negatives = list()
|
||||
avatar_name = ""
|
||||
|
||||
def cmdargs(line):
|
||||
args = shlex.split(line)
|
||||
pos = 0
|
||||
res = {}
|
||||
|
||||
while pos < len(args):
|
||||
arg = args[pos]
|
||||
|
||||
assert arg.startswith("--"), f'must start with "--": {arg}'
|
||||
tag = arg[2:]
|
||||
|
||||
func = prompt_tags.get(tag, None)
|
||||
assert func, f'unknown commandline option: {arg}'
|
||||
|
||||
assert pos+1 < len(args), f'missing argument for command line option {arg}'
|
||||
|
||||
val = args[pos+1]
|
||||
|
||||
res[tag] = func(val)
|
||||
|
||||
pos += 2
|
||||
|
||||
return res
|
||||
|
||||
|
||||
|
||||
def add_param(key, value, cur_str):
|
||||
cur_str += '--{key} {value} '.format(key=key, value=value)
|
||||
return cur_str
|
||||
|
||||
def parse_size(i_width, i_height, str_size, cur_str):
|
||||
i_width = str_size.split('x')[0]
|
||||
i_height = str_size.split('x')[1]
|
||||
|
||||
def parse_virariant_size(str_size, cur_str):
|
||||
width = str_size.split('x')[0]
|
||||
height = str_size.split('x')[1]
|
||||
cur_str = add_param('seed_resize_from_w', width, cur_str)
|
||||
cur_str = add_param('seed_resize_from_h', height, cur_str)
|
||||
return cur_str
|
||||
|
||||
def parse_param(param_str):
|
||||
m_batch_size = BATCH_SIZE
|
||||
m_n_iter = N_ITER
|
||||
m_steps = STEPS
|
||||
m_cfg_scale = CFG_SCALE
|
||||
m_width = WIDTH
|
||||
m_height = HEIGHT
|
||||
m_sampler_index = SAMPLER_INDEX
|
||||
# m_tiling = TILING
|
||||
m_restore_faces = RESTORE_FACE
|
||||
m_do_not_save_grid = DO_NOT_SAVE_GRID
|
||||
# m_sd_model = sd_model
|
||||
cur_line = ""
|
||||
for item in param_str.split(', '):
|
||||
if item == '':
|
||||
continue
|
||||
group = item.split(': ')
|
||||
key = group[0]
|
||||
value = group[1]
|
||||
if key == 'Steps':
|
||||
m_steps = value
|
||||
elif key == "CFG scale":
|
||||
m_cfg_scale = value
|
||||
elif value == 'Sampler':
|
||||
m_sampler_index = map_sampler_to_idx[value]
|
||||
elif key == 'Size':
|
||||
parse_size(m_width, m_height, value, cur_line)
|
||||
elif key == 'Seed resize from':
|
||||
cur_line = parse_virariant_size(value, cur_line)
|
||||
elif key == 'Seed':
|
||||
cur_line = add_param("seed", value, cur_line)
|
||||
elif key == 'Variation seed strength':
|
||||
cur_line = add_param("subseed_strength", value, cur_line)
|
||||
elif key == 'Variation seed':
|
||||
cur_line = add_param("subseed", value, cur_line)
|
||||
# elif key == 'Model hash':
|
||||
# cur_line = add_param("sd_model", m_sd_model, cur_line)
|
||||
cur_line = add_param("batch_size", m_batch_size, cur_line)
|
||||
cur_line = add_param("n_iter", m_n_iter, cur_line)
|
||||
cur_line = add_param("steps", m_steps, cur_line)
|
||||
cur_line = add_param("cfg_scale", m_cfg_scale, cur_line)
|
||||
cur_line = add_param("sampler_index", m_sampler_index, cur_line)
|
||||
cur_line = add_param("width", m_width, cur_line)
|
||||
cur_line = add_param("height", m_height, cur_line)
|
||||
cur_line = add_param("restore_faces", m_restore_faces, cur_line)
|
||||
# cur_line = add_param("tiling", m_tiling, cur_line)
|
||||
cur_line = add_param("do_not_save_grid", m_do_not_save_grid, cur_line)
|
||||
return cur_line
|
||||
|
||||
def parse_yaml_dict(rawDict, tag, avatar_prompt, avatar_name, default_negative):
|
||||
# depth-first-search
|
||||
if 'value' in rawDict.keys() or 'negative' in rawDict.keys():
|
||||
if SKIP_EXISTS:
|
||||
if os.path.exists(OUTPATH_SAMPLES + tag + '/' + avatar_name+'.png') or os.path.exists(OUTPATH_SAMPLES + tag + '\\' + 'Not-available.png'):
|
||||
print("Skip "+str(tag))
|
||||
return ""
|
||||
cur = ""
|
||||
parsed_param = False
|
||||
m_positive = avatar_prompt
|
||||
m_negative = default_negative
|
||||
for item in rawDict.items():
|
||||
key = item[0]
|
||||
value = item[1]
|
||||
if key == 'param':
|
||||
params = parse_param(rawDict['param'])
|
||||
parsed_param = True
|
||||
elif key == 'value':
|
||||
m_positive = value + m_positive
|
||||
elif key == 'negative':
|
||||
m_negative = value +','+ m_negative
|
||||
|
||||
cur += "--{key} \"{value}\" ".format(key='prompt', value= m_positive)
|
||||
cur += "--{key} \"{value}\" ".format(key='negative_prompt', value= m_negative)
|
||||
|
||||
if parsed_param == False:
|
||||
params = parse_param("")
|
||||
cur += params
|
||||
cur = add_param('outpath_samples', '\"'+OUTPATH_SAMPLES + str(tag)+'\"', cur)
|
||||
cur = add_param('outpath_grids', '\"'+OUTPATH_GRIDS + str(tag)+'\"', cur)
|
||||
return cur
|
||||
else:
|
||||
for item in rawDict.items():
|
||||
key = item[0]
|
||||
ret = parse_yaml_dict(rawDict[key], tag if key=='' else key, avatar_prompt, avatar_name, default_negative)
|
||||
if len(ret) != 0:
|
||||
if tag not in EXCLUDED_TAGS:
|
||||
OUTPUTS_DICT.append({'name': key,
|
||||
'prompt': item[1]['value'] if 'value' in item[1].keys() else '',
|
||||
'negative_prompt': item[1]['negative'] if 'negative' in item[1].keys() else ''})
|
||||
if tag in OUTPUTS.keys():
|
||||
OUTPUTS[tag].append(ret)
|
||||
else:
|
||||
OUTPUTS[tag] = [ret]
|
||||
return ""
|
||||
|
||||
|
||||
def rename_preview(avatar_name):
|
||||
if avatar_name == '':
|
||||
print("Please select avatar name first.")
|
||||
return
|
||||
root = OUTPATH_SAMPLES
|
||||
for folder in os.listdir(root):
|
||||
files = os.listdir(root + folder)
|
||||
if 'Not-available.png' in files:
|
||||
print('Skip '+ folder + ' not available.')
|
||||
continue
|
||||
if avatar_name + '.png' in files:
|
||||
continue
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' in files:
|
||||
files.remove(each_avatar + '.png')
|
||||
if len(files) == 1:
|
||||
os.rename(root + folder + '/' + files[0], root + folder + '/' + avatar_name + '.png')
|
||||
else:
|
||||
print('There are 0 or more than 1 files in ' + folder)
|
||||
|
||||
def load_prompt_file(file):
|
||||
if (file is None):
|
||||
lines = []
|
||||
else:
|
||||
lines = [x.strip() for x in file.decode('utf8', errors='ignore').split("\n")]
|
||||
|
||||
return None, "\n".join(lines), gr.update(lines=7)
|
||||
|
||||
def copy_from_prompt_app():
|
||||
return []
|
||||
|
||||
def open_folder(f):
|
||||
if not os.path.exists(f):
|
||||
print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
|
||||
return
|
||||
elif not os.path.isdir(f):
|
||||
print(f"""
|
||||
WARNING
|
||||
An open_folder request was made with an argument that is not a folder.
|
||||
This could be an error or a malicious attempt to run code on your computer.
|
||||
Requested path was: {f}
|
||||
""", file=sys.stderr)
|
||||
return
|
||||
|
||||
if not shared.cmd_opts.hide_ui_dir_config:
|
||||
path = os.path.normpath(f)
|
||||
if platform.system() == "Windows":
|
||||
os.startfile(path)
|
||||
elif platform.system() == "Darwin":
|
||||
sp.Popen(["open", path])
|
||||
else:
|
||||
sp.Popen(["xdg-open", path])
|
||||
|
||||
class PromptStyle(typing.NamedTuple):
|
||||
name: str
|
||||
prompt: str
|
||||
negative_prompt: str
|
||||
|
||||
def save_styles() -> None:
|
||||
if len(OUTPUTS.keys()) == 0:
|
||||
return
|
||||
path = root_path + '/styles.csv'
|
||||
# Write to temporary file first, so we don't nuke the file if something goes wrong
|
||||
fd, temp_path = tempfile.mkstemp(".csv")
|
||||
with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file:
|
||||
# _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple,
|
||||
# and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict()
|
||||
writer = csv.DictWriter(file, fieldnames=PromptStyle._fields)
|
||||
writer.writeheader()
|
||||
for row in OUTPUTS_DICT:
|
||||
writer.writerow({'name': row['name'], 'prompt': row['prompt'], 'negative_prompt': row['negative_prompt']})
|
||||
# writer.writerows(style._asdict() for k, style in self.styles.items())
|
||||
|
||||
# Always keep a backup file around
|
||||
if os.path.exists(path):
|
||||
shutil.move(path, path + ".bak")
|
||||
shutil.move(temp_path, path)
|
||||
|
||||
def load_prompt(file, default_negative, dropdown, skip_exist):
|
||||
global SKIP_EXISTS
|
||||
SKIP_EXISTS = skip_exist
|
||||
if dropdown == '':
|
||||
return
|
||||
rawDict = yaml.load(file, Loader = yaml.BaseLoader)
|
||||
default_negative = default_negative + ',' + avatar_negatives[avatar_names.index(dropdown)]
|
||||
parse_yaml_dict(rawDict, "", avatar_prompts[avatar_names.index(dropdown)], dropdown, default_negative)
|
||||
prompt_txt = ""
|
||||
keys = list(filter(lambda x: x not in EXCLUDED_TAGS, OUTPUTS.keys()))
|
||||
for style in keys:
|
||||
for each_line in OUTPUTS[style]:
|
||||
prompt_txt += each_line + '\n'
|
||||
return [prompt_txt, gr.Row.update(visible=True)]
|
||||
|
||||
def load_avartar(avatar_dict, customize_tags_positive):
|
||||
avatars = yaml.load(avatar_dict, yaml.BaseLoader)
|
||||
|
||||
for name, prompt in avatars.items():
|
||||
avatar_names.append(name)
|
||||
if 'value' in prompt.keys():
|
||||
avatar_prompts.append(customize_tags_positive + ', ' + prompt['value'])
|
||||
if 'negative' in prompt.keys():
|
||||
avatar_negatives.append(prompt['negative'])
|
||||
return [gr.Dropdown.update(choices=avatar_names, value=avatar_names[0]), gr.Column.update(visible=True), gr.Group.update(visible=True)]
|
||||
|
||||
def scan_outputs(avatar_name):
|
||||
if avatar_name is None or len(avatar_name) == 0:
|
||||
print("Please select avatar name first.")
|
||||
return
|
||||
root = OUTPATH_SAMPLES
|
||||
global qc_dict
|
||||
qc_dict = {}
|
||||
for folder in os.listdir(root):
|
||||
if os.path.isdir(root + folder) == False:
|
||||
continue
|
||||
|
||||
files = os.listdir(root + folder)
|
||||
if 'Not-available.png' in files:
|
||||
print('Skip '+ folder + ' not available.')
|
||||
continue
|
||||
if avatar_name + '.png' in files:
|
||||
continue
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' in files:
|
||||
files.remove(each_avatar + '.png')
|
||||
if len(files) == 0:
|
||||
continue
|
||||
qc_dict[folder] = [root + folder + '/' + file for file in files]
|
||||
|
||||
if len(qc_dict.keys()) == 0:
|
||||
return gr.Dropdown.update(choices=[])
|
||||
return gr.Dropdown.update(choices=list(qc_dict.keys()), value=list(qc_dict.keys())[0])
|
||||
|
||||
def update_gallery(dropdown, avatar):
|
||||
root = OUTPATH_SAMPLES
|
||||
global trg_img, current_folder
|
||||
current_folder = root + dropdown
|
||||
trg_img = root + dropdown + '/' + avatar + '.png'
|
||||
return qc_dict[dropdown]
|
||||
|
||||
def clean_select_picture(filename):
|
||||
if current_folder == '':
|
||||
print("Please select qc tag.")
|
||||
return
|
||||
for file in os.listdir(current_folder):
|
||||
is_avatar = False
|
||||
for each_avatar in avatar_names:
|
||||
if each_avatar + '.png' == file:
|
||||
is_avatar = True
|
||||
break
|
||||
if os.path.splitext(file)[0] in filename:
|
||||
os.rename(current_folder+'/'+file, trg_img)
|
||||
elif is_avatar == False:
|
||||
os.remove(current_folder+'/'+file)
|
||||
|
||||
def image_url(filedata):
|
||||
if type(filedata) == dict and filedata["is_file"]:
|
||||
filename = filedata["name"]
|
||||
tempdir = os.path.normpath(tempfile.gettempdir())
|
||||
normfn = os.path.normpath(filename)
|
||||
assert normfn.startswith(tempdir), 'trying to open image file not in temporary directory'
|
||||
|
||||
image = Image.open(filename)
|
||||
clean_select_picture(os.path.basename(filename))
|
||||
return Image.open(filename)
|
||||
|
||||
if type(filedata) == list:
|
||||
if len(filedata) == 0:
|
||||
return None
|
||||
|
||||
filedata = filedata[0]
|
||||
|
||||
if filedata.startswith("data:image/png;base64,"):
|
||||
filedata = filedata[len("data:image/png;base64,"):]
|
||||
|
||||
filedata = base64.decodebytes(filedata.encode('utf-8'))
|
||||
image = Image.open(io.BytesIO(filedata))
|
||||
return image
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
class Script(scripts.Script):
|
||||
def title(self):
|
||||
return "Prompt gallery"
|
||||
|
||||
def ui(self, is_img2img):
|
||||
with gr.Group():
|
||||
with gr.Column():
|
||||
label_avatar = gr.Label("Upload avatars config")
|
||||
avatar_dict = gr.File(label="Upload avatar prompt inputs", type='bytes')
|
||||
|
||||
# copy_from_app_button = gr.Button("Copy From Prompt Preview")
|
||||
|
||||
with gr.Group():
|
||||
with gr.Column(visible=False) as avatar_col:
|
||||
label_presets = gr.Label("Presets")
|
||||
dropdown = gr.Dropdown(label="Choose avatar", choices=[""], value="", type="value", elem_id="dropdown")
|
||||
dropdown.save_to_config = True
|
||||
with gr.Row():
|
||||
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False)
|
||||
skip_exist = gr.Checkbox(value=True, label="skip exist")
|
||||
default_negative = gr.Textbox(label="default_negative", lines=1)
|
||||
default_positive = gr.Textbox(label="default_positive", lines=1)
|
||||
prompt_dict = gr.File(label="Upload prompt dictionary", type='bytes')
|
||||
with gr.Row(visible = False) as save_prompts:
|
||||
open_button = gr.Button("Open outputs directory")
|
||||
export_button = gr.Button("Export to WebUI style")
|
||||
prompt_display = gr.Textbox(label="List of prompt inputs", lines=1)
|
||||
|
||||
|
||||
prompt_dict.change(fn=load_prompt, inputs=[prompt_dict, default_negative, dropdown, skip_exist], outputs=[prompt_display, save_prompts])
|
||||
open_button.click(fn=lambda: open_folder(OUTPATH_SAMPLES), inputs=[], outputs=[])
|
||||
export_button.click(fn=save_styles, inputs=[], outputs=[])
|
||||
|
||||
with gr.Group(visible=False) as qc_widgets:
|
||||
label_preview = gr.Label("QC preview")
|
||||
with gr.Row():
|
||||
qc_refresh = gr.Button("QC scan")
|
||||
preview_dropdown = gr.Dropdown(label="Select prompts", choices=[""], value="", type="value", elem_id="dropdown")
|
||||
preview_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"preview_gallery").style(grid=4)
|
||||
qc_refresh.click(fn=scan_outputs, inputs=[dropdown], outputs=preview_dropdown)
|
||||
with gr.Row():
|
||||
qc_show = gr.Button(f"Show pics")
|
||||
qc_select = gr.Button(f"Select")
|
||||
rename_button = gr.Button("Auto rename")
|
||||
selected_img = gr.Image(label="Selected",show_label=False, source="upload", interactive=True, type="pil").style(height=480)
|
||||
qc_show.click(fn=update_gallery, inputs=[preview_dropdown, dropdown], outputs=preview_gallery)
|
||||
qc_select.click(
|
||||
fn=lambda x: image_url(x),
|
||||
_js="extract_image_from_gallery",
|
||||
inputs=[preview_gallery],
|
||||
outputs=[selected_img],
|
||||
)
|
||||
# qc_select.click(fn=select_picture, inputs=[dropdown, preview_dropdown, preview_gallery], outputs=[])
|
||||
rename_button.click(fn=rename_preview, inputs=[dropdown], outputs=[])
|
||||
# qc_select.click(fn=scan_outputs, inputs=[], outputs=[preview_dropdown])
|
||||
|
||||
avatar_dict.change(fn=load_avartar, inputs=[avatar_dict, default_positive], outputs=[dropdown, avatar_col, qc_widgets])
|
||||
return [checkbox_iterate, avatar_dict, prompt_dict, default_negative, default_positive, dropdown, prompt_display, rename_button, label_avatar, open_button, export_button, skip_exist, label_presets, label_preview, preview_dropdown, preview_gallery, qc_select, qc_refresh, qc_show, selected_img]
|
||||
|
||||
def run(self, p, checkbox_iterate, avatar_dict, prompt_dict, default_negative, default_positive, dropdown, prompt_display, rename_button, label_avatar, open_button, export_button, skip_exist, label_presets, label_preview, preview_dropdown, preview_gallery, qc_select, qc_refresh, qc_show, selected_img):
|
||||
lines = [x.strip() for x in prompt_display.splitlines()]
|
||||
lines = [x for x in lines if len(x) > 0]
|
||||
|
||||
p.do_not_save_grid = True
|
||||
|
||||
job_count = 0
|
||||
jobs = []
|
||||
|
||||
for line in lines:
|
||||
if "--" in line:
|
||||
try:
|
||||
args = cmdargs(line)
|
||||
except Exception:
|
||||
print(f"Error parsing line [line] as commandline:", file=sys.stderr)
|
||||
print(traceback.format_exc(), file=sys.stderr)
|
||||
args = {"prompt": line}
|
||||
else:
|
||||
args = {"prompt": line}
|
||||
|
||||
n_iter = args.get("n_iter", 1)
|
||||
if n_iter != 1:
|
||||
job_count += n_iter
|
||||
else:
|
||||
job_count += 1
|
||||
|
||||
jobs.append(args)
|
||||
|
||||
print(f"Will process {len(lines)} lines in {job_count} jobs.")
|
||||
if (checkbox_iterate and p.seed == -1):
|
||||
p.seed = int(random.randrange(4294967294))
|
||||
|
||||
state.job_count = job_count
|
||||
|
||||
images = []
|
||||
for n, args in enumerate(jobs):
|
||||
state.job = f"{state.job_no + 1} out of {state.job_count}"
|
||||
|
||||
copy_p = copy.copy(p)
|
||||
for k, v in args.items():
|
||||
setattr(copy_p, k, v)
|
||||
|
||||
proc = process_images(copy_p)
|
||||
images += proc.images
|
||||
|
||||
if (checkbox_iterate):
|
||||
p.seed = p.seed + (p.batch_size * p.n_iter)
|
||||
|
||||
OUTPUTS = {}
|
||||
rawDict = {}
|
||||
|
||||
return Processed(p, images, p.seed, "")
|
||||
import modules.extras
|
||||
import modules.ui
|
||||
from modules.shared import opts, cmd_opts
|
||||
from modules import shared, scripts
|
||||
from modules import script_callbacks
|
||||
from pathlib import Path
|
||||
from typing import List, Tuple
|
||||
import uvicorn
|
||||
from uvicorn import Config
|
||||
from fastapi import FastAPI
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
import contextlib
|
||||
import threading
|
||||
import requests
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
import json
|
||||
|
||||
def on_ui_settings():
|
||||
with open("./extensions/prompt_gallery_name.json") as fd:
|
||||
name = json.load(fd)['name']
|
||||
app = FastAPI()
|
||||
app.mount('/', StaticFiles(directory='./extensions/'+name,html=True))
|
||||
config = Config(app=app, host='localhost',port=5173, log_level="info", loop="asyncio", limit_max_requests=1)
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"]
|
||||
)
|
||||
|
||||
thread = threading.Thread(target= uvicorn.run, kwargs={'app':app, 'host': 'localhost', 'port':5173})
|
||||
thread.start()
|
||||
tmp = requests.get("http://localhost:5173")
|
||||
while tmp.status_code != 204 and tmp.status_code != 200:
|
||||
time.sleep(0.01)
|
||||
tmp = requests.get("http://localhost:5173")
|
||||
pass
|
||||
# thread.join()
|
||||
|
||||
|
||||
|
||||
def on_ui_tabs():
|
||||
html = """<iframe id="tab_iframe" style="width: 100%; min-height: 864px; padding: 0;margin: 0;border: none;" src="http://localhost:5173/" frameborder="0" marginwidth="0" marginheight="0"></iframe>"""
|
||||
with gr.Blocks(analytics_enabled=False, elem_id="prompt_gallery") as prompt_gallery:
|
||||
prompt_gallery = gr.HTML(html)
|
||||
|
||||
return (prompt_gallery , "Prompt Gallery", "prompt_gallery"),
|
||||
|
||||
script_callbacks.on_ui_tabs(on_ui_tabs)
|
||||
|
||||
script_callbacks.on_ui_settings(on_ui_settings)
|
||||
9
setup.py
9
setup.py
|
|
@ -1,9 +0,0 @@
|
|||
import os
|
||||
import shutil
|
||||
import sys
|
||||
|
||||
current_dir= os.path.abspath(os.path.dirname(__file__))
|
||||
print(os.path.join(os.path.join(current_dir,"extensions"),"prompt-gallery"), os.path.join(sys.argv[1],"extensions"))
|
||||
print(os.path.join(current_dir,"scripts"), os.path.join(sys.argv[1],"scripts"))
|
||||
shutil.copytree(os.path.join(os.path.join(current_dir,"extensions"),"prompt-gallery"), os.path.join(os.path.join(sys.argv[1],"extensions"),"prompt-gallery"))
|
||||
shutil.copy(os.path.join(os.path.join(current_dir,"scripts"),"prompt_gallery.py"), os.path.join(sys.argv[1],"scripts"))
|
||||
Loading…
Reference in New Issue