mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
1122 lines
39 KiB
Python
1122 lines
39 KiB
Python
import eventlet
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import glob
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import os
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import shutil
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import mimetypes
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import traceback
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import math
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from flask import Flask, redirect, send_from_directory
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from flask_socketio import SocketIO
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from PIL import Image
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from uuid import uuid4
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from threading import Event
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from ldm.invoke.args import Args, APP_ID, APP_VERSION, calculate_init_img_hash
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from ldm.invoke.pngwriter import PngWriter, retrieve_metadata
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from ldm.invoke.prompt_parser import split_weighted_subprompts
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from backend.modules.parameters import parameters_to_command
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# Loading Arguments
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opt = Args()
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args = opt.parse_args()
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class InvokeAIWebServer:
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def __init__(self, generate, gfpgan, codeformer, esrgan) -> None:
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self.host = args.host
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self.port = args.port
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self.generate = generate
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self.gfpgan = gfpgan
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self.codeformer = codeformer
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self.esrgan = esrgan
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self.canceled = Event()
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def run(self):
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self.setup_app()
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self.setup_flask()
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def setup_flask(self):
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# Fix missing mimetypes on Windows
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mimetypes.add_type('application/javascript', '.js')
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mimetypes.add_type('text/css', '.css')
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# Socket IO
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logger = True if args.web_verbose else False
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engineio_logger = True if args.web_verbose else False
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max_http_buffer_size = 10000000
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socketio_args = {
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'logger': logger,
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'engineio_logger': engineio_logger,
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'max_http_buffer_size': max_http_buffer_size,
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'ping_interval': (50, 50),
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'ping_timeout': 60,
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}
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if opt.cors:
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socketio_args['cors_allowed_origins'] = opt.cors
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self.app = Flask(
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__name__, static_url_path='', static_folder='../frontend/dist/'
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)
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self.socketio = SocketIO(
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self.app,
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**socketio_args
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)
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# Keep Server Alive Route
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@self.app.route('/flaskwebgui-keep-server-alive')
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def keep_alive():
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return {'message': 'Server Running'}
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# Outputs Route
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self.app.config['OUTPUTS_FOLDER'] = os.path.abspath(args.outdir)
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@self.app.route('/outputs/<path:file_path>')
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def outputs(file_path):
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return send_from_directory(
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self.app.config['OUTPUTS_FOLDER'], file_path
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)
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# Base Route
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@self.app.route('/')
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def serve():
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if args.web_develop:
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return redirect('http://127.0.0.1:5173')
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else:
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return send_from_directory(
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self.app.static_folder, 'index.html'
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)
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self.load_socketio_listeners(self.socketio)
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if args.gui:
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print('>> Launching Invoke AI GUI')
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close_server_on_exit = True
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if args.web_develop:
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close_server_on_exit = False
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try:
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from flaskwebgui import FlaskUI
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FlaskUI(
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app=self.app,
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socketio=self.socketio,
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start_server='flask-socketio',
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host=self.host,
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port=self.port,
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width=1600,
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height=1000,
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idle_interval=10,
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close_server_on_exit=close_server_on_exit,
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).run()
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except KeyboardInterrupt:
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import sys
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sys.exit(0)
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else:
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print('>> Started Invoke AI Web Server!')
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if self.host == '0.0.0.0':
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print(
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f"Point your browser at http://localhost:{self.port} or use the host's DNS name or IP address."
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)
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else:
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print(
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'>> Default host address now 127.0.0.1 (localhost). Use --host 0.0.0.0 to bind any address.'
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)
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print(
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f'>> Point your browser at http://{self.host}:{self.port}'
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)
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self.socketio.run(app=self.app, host=self.host, port=self.port)
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def setup_app(self):
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self.result_url = 'outputs/'
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self.init_image_url = 'outputs/init-images/'
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self.mask_image_url = 'outputs/mask-images/'
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self.intermediate_url = 'outputs/intermediates/'
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# location for "finished" images
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self.result_path = args.outdir
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# temporary path for intermediates
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self.intermediate_path = os.path.join(
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self.result_path, 'intermediates/'
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)
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# path for user-uploaded init images and masks
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self.init_image_path = os.path.join(self.result_path, 'init-images/')
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self.mask_image_path = os.path.join(self.result_path, 'mask-images/')
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# txt log
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self.log_path = os.path.join(self.result_path, 'invoke_log.txt')
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# make all output paths
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[
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os.makedirs(path, exist_ok=True)
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for path in [
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self.result_path,
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self.intermediate_path,
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self.init_image_path,
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self.mask_image_path,
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]
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]
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def load_socketio_listeners(self, socketio):
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@socketio.on('requestSystemConfig')
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def handle_request_capabilities():
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print(f'>> System config requested')
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config = self.get_system_config()
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socketio.emit('systemConfig', config)
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@socketio.on('requestLatestImages')
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def handle_request_latest_images(latest_mtime):
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try:
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paths = glob.glob(os.path.join(self.result_path, '*.png'))
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image_paths = sorted(
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paths, key=lambda x: os.path.getmtime(x), reverse=True
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)
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image_paths = list(
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filter(
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lambda x: os.path.getmtime(x) > latest_mtime,
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image_paths,
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)
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)
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image_array = []
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for path in image_paths:
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metadata = retrieve_metadata(path)
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image_array.append(
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{
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata['sd-metadata'],
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}
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)
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socketio.emit(
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'galleryImages',
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{
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'images': image_array,
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},
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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@socketio.on('requestImages')
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def handle_request_images(earliest_mtime=None):
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try:
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page_size = 50
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paths = glob.glob(os.path.join(self.result_path, '*.png'))
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image_paths = sorted(
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paths, key=lambda x: os.path.getmtime(x), reverse=True
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)
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if earliest_mtime:
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image_paths = list(
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filter(
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lambda x: os.path.getmtime(x) < earliest_mtime,
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image_paths,
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)
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)
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areMoreImagesAvailable = len(image_paths) >= page_size
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image_paths = image_paths[slice(0, page_size)]
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image_array = []
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for path in image_paths:
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metadata = retrieve_metadata(path)
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image_array.append(
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{
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata['sd-metadata'],
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}
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)
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socketio.emit(
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'galleryImages',
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{
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'images': image_array,
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'areMoreImagesAvailable': areMoreImagesAvailable,
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},
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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@socketio.on('generateImage')
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def handle_generate_image_event(
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generation_parameters, esrgan_parameters, facetool_parameters
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):
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try:
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print(
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f'>> Image generation requested: {generation_parameters}\nESRGAN parameters: {esrgan_parameters}\nFacetool parameters: {facetool_parameters}'
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)
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self.generate_images(
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generation_parameters, esrgan_parameters, facetool_parameters
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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@socketio.on('runPostprocessing')
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def handle_run_postprocessing(
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original_image, postprocessing_parameters
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):
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try:
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print(
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f'>> Postprocessing requested for "{original_image["url"]}": {postprocessing_parameters}'
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)
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progress = Progress()
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socketio.emit('progressUpdate', progress.to_formatted_dict())
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eventlet.sleep(0)
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original_image_path = self.get_image_path_from_url(
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original_image['url']
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)
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image = Image.open(original_image_path)
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seed = (
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original_image['metadata']['seed']
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if 'seed' in original_image['metadata']
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else 'unknown_seed'
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)
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if postprocessing_parameters['type'] == 'esrgan':
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progress.set_current_status('Upscaling (ESRGAN)')
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elif postprocessing_parameters['type'] == 'gfpgan':
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progress.set_current_status('Restoring Faces (GFPGAN)')
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elif postprocessing_parameters['type'] == 'codeformer':
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progress.set_current_status('Restoring Faces (Codeformer)')
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socketio.emit('progressUpdate', progress.to_formatted_dict())
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eventlet.sleep(0)
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if postprocessing_parameters['type'] == 'esrgan':
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image = self.esrgan.process(
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image=image,
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upsampler_scale=postprocessing_parameters['upscale'][
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0
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],
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strength=postprocessing_parameters['upscale'][1],
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seed=seed,
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)
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elif postprocessing_parameters['type'] == 'gfpgan':
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image = self.gfpgan.process(
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image=image,
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strength=postprocessing_parameters['facetool_strength'],
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seed=seed,
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)
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elif postprocessing_parameters['type'] == 'codeformer':
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image = self.codeformer.process(
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image=image,
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strength=postprocessing_parameters['facetool_strength'],
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fidelity=postprocessing_parameters['codeformer_fidelity'],
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seed=seed,
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device='cpu' if str(self.generate.device) == 'mps' else self.generate.device
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)
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else:
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raise TypeError(
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f'{postprocessing_parameters["type"]} is not a valid postprocessing type'
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)
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progress.set_current_status('Saving Image')
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socketio.emit('progressUpdate', progress.to_formatted_dict())
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eventlet.sleep(0)
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postprocessing_parameters['seed'] = seed
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metadata = self.parameters_to_post_processed_image_metadata(
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parameters=postprocessing_parameters,
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original_image_path=original_image_path,
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)
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command = parameters_to_command(postprocessing_parameters)
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path = self.save_result_image(
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image,
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command,
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metadata,
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self.result_path,
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postprocessing=postprocessing_parameters['type'],
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)
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self.write_log_message(
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f'[Postprocessed] "{original_image_path}" > "{path}": {postprocessing_parameters}'
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)
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progress.mark_complete()
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socketio.emit('progressUpdate', progress.to_formatted_dict())
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eventlet.sleep(0)
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socketio.emit(
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'postprocessingResult',
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{
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata,
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},
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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@socketio.on('cancel')
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def handle_cancel():
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print(f'>> Cancel processing requested')
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self.canceled.set()
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# TODO: I think this needs a safety mechanism.
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@socketio.on('deleteImage')
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def handle_delete_image(url, uuid):
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try:
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print(f'>> Delete requested "{url}"')
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from send2trash import send2trash
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path = self.get_image_path_from_url(url)
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send2trash(path)
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socketio.emit('imageDeleted', {'url': url, 'uuid': uuid})
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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# TODO: I think this needs a safety mechanism.
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@socketio.on('uploadInitialImage')
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def handle_upload_initial_image(bytes, name):
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try:
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print(f'>> Init image upload requested "{name}"')
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file_path = self.save_file_unique_uuid_name(
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bytes=bytes, name=name, path=self.init_image_path
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)
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socketio.emit(
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'initialImageUploaded',
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{
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'url': self.get_url_from_image_path(file_path),
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},
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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# TODO: I think this needs a safety mechanism.
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@socketio.on('uploadMaskImage')
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def handle_upload_mask_image(bytes, name):
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try:
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print(f'>> Mask image upload requested "{name}"')
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file_path = self.save_file_unique_uuid_name(
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bytes=bytes, name=name, path=self.mask_image_path
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)
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socketio.emit(
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'maskImageUploaded',
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{
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'url': self.get_url_from_image_path(file_path),
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},
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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print('\n')
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traceback.print_exc()
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print('\n')
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# App Functions
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def get_system_config(self):
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return {
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'model': 'stable diffusion',
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'model_id': args.model,
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'model_hash': self.generate.model_hash,
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'app_id': APP_ID,
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'app_version': APP_VERSION,
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}
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|
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def generate_images(
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self, generation_parameters, esrgan_parameters, facetool_parameters
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):
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try:
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self.canceled.clear()
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step_index = 1
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prior_variations = (
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generation_parameters['with_variations']
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if 'with_variations' in generation_parameters
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else []
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)
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"""
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TODO:
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If a result image is used as an init image, and then deleted, we will want to be
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able to use it as an init image in the future. Need to handle this case.
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"""
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|
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# We need to give absolute paths to the generator, stash the URLs for later
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init_img_url = None
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mask_img_url = None
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|
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if 'init_img' in generation_parameters:
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init_img_url = generation_parameters['init_img']
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generation_parameters[
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'init_img'
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] = self.get_image_path_from_url(
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generation_parameters['init_img']
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)
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|
|
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if 'init_mask' in generation_parameters:
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mask_img_url = generation_parameters['init_mask']
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generation_parameters[
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'init_mask'
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] = self.get_image_path_from_url(
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generation_parameters['init_mask']
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)
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|
|
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totalSteps = self.calculate_real_steps(
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steps=generation_parameters['steps'],
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strength=generation_parameters['strength']
|
|
if 'strength' in generation_parameters
|
|
else None,
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|
has_init_image='init_img' in generation_parameters,
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)
|
|
|
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progress = Progress(generation_parameters=generation_parameters)
|
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|
|
self.socketio.emit('progressUpdate', progress.to_formatted_dict())
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eventlet.sleep(0)
|
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|
|
def image_progress(sample, step):
|
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if self.canceled.is_set():
|
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raise CanceledException
|
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|
|
nonlocal step_index
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nonlocal generation_parameters
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nonlocal progress
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|
|
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progress.set_current_step(step + 1)
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progress.set_current_status('Generating')
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progress.set_current_status_has_steps(True)
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|
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if (
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generation_parameters['progress_images']
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and step % 5 == 0
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and step < generation_parameters['steps'] - 1
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):
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image = self.generate.sample_to_image(sample)
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metadata = self.parameters_to_generated_image_metadata(
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generation_parameters
|
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)
|
|
command = parameters_to_command(generation_parameters)
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|
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path = self.save_result_image(
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image,
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command,
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metadata,
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self.intermediate_path,
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step_index=step_index,
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postprocessing=False,
|
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)
|
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|
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step_index += 1
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self.socketio.emit(
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'intermediateResult',
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{
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'url': self.get_url_from_image_path(path),
|
|
'mtime': os.path.getmtime(path),
|
|
'metadata': metadata,
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},
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)
|
|
self.socketio.emit(
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'progressUpdate', progress.to_formatted_dict()
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
def image_done(image, seed, first_seed):
|
|
if self.canceled.is_set():
|
|
raise CanceledException
|
|
|
|
nonlocal generation_parameters
|
|
nonlocal esrgan_parameters
|
|
nonlocal facetool_parameters
|
|
nonlocal progress
|
|
|
|
step_index = 1
|
|
nonlocal prior_variations
|
|
|
|
progress.set_current_status('Generation Complete')
|
|
|
|
self.socketio.emit(
|
|
'progressUpdate', progress.to_formatted_dict()
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
all_parameters = generation_parameters
|
|
postprocessing = False
|
|
|
|
if (
|
|
'variation_amount' in all_parameters
|
|
and all_parameters['variation_amount'] > 0
|
|
):
|
|
first_seed = first_seed or seed
|
|
this_variation = [
|
|
[seed, all_parameters['variation_amount']]
|
|
]
|
|
all_parameters['with_variations'] = (
|
|
prior_variations + this_variation
|
|
)
|
|
all_parameters['seed'] = first_seed
|
|
elif 'with_variations' in all_parameters:
|
|
all_parameters['seed'] = first_seed
|
|
else:
|
|
all_parameters['seed'] = seed
|
|
|
|
if self.canceled.is_set():
|
|
raise CanceledException
|
|
|
|
if esrgan_parameters:
|
|
progress.set_current_status('Upscaling')
|
|
progress.set_current_status_has_steps(False)
|
|
self.socketio.emit(
|
|
'progressUpdate', progress.to_formatted_dict()
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
image = self.esrgan.process(
|
|
image=image,
|
|
upsampler_scale=esrgan_parameters['level'],
|
|
strength=esrgan_parameters['strength'],
|
|
seed=seed,
|
|
)
|
|
|
|
postprocessing = True
|
|
all_parameters['upscale'] = [
|
|
esrgan_parameters['level'],
|
|
esrgan_parameters['strength'],
|
|
]
|
|
|
|
if self.canceled.is_set():
|
|
raise CanceledException
|
|
|
|
if facetool_parameters:
|
|
if facetool_parameters['type'] == 'gfpgan':
|
|
progress.set_current_status('Restoring Faces (GFPGAN)')
|
|
elif facetool_parameters['type'] == 'codeformer':
|
|
progress.set_current_status('Restoring Faces (Codeformer)')
|
|
|
|
progress.set_current_status_has_steps(False)
|
|
self.socketio.emit(
|
|
'progressUpdate', progress.to_formatted_dict()
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
if facetool_parameters['type'] == 'gfpgan':
|
|
image = self.gfpgan.process(
|
|
image=image,
|
|
strength=facetool_parameters['strength'],
|
|
seed=seed,
|
|
)
|
|
elif facetool_parameters['type'] == 'codeformer':
|
|
image = self.codeformer.process(
|
|
image=image,
|
|
strength=facetool_parameters['strength'],
|
|
fidelity=facetool_parameters['codeformer_fidelity'],
|
|
seed=seed,
|
|
device='cpu' if str(self.generate.device) == 'mps' else self.generate.device,
|
|
)
|
|
all_parameters['codeformer_fidelity'] = facetool_parameters['codeformer_fidelity']
|
|
|
|
postprocessing = True
|
|
all_parameters['facetool_strength'] = facetool_parameters[
|
|
'strength'
|
|
]
|
|
all_parameters['facetool_type'] = facetool_parameters[
|
|
'type'
|
|
]
|
|
|
|
progress.set_current_status('Saving Image')
|
|
self.socketio.emit(
|
|
'progressUpdate', progress.to_formatted_dict()
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
# restore the stashed URLS and discard the paths, we are about to send the result to client
|
|
if 'init_img' in all_parameters:
|
|
all_parameters['init_img'] = init_img_url
|
|
|
|
if 'init_mask' in all_parameters:
|
|
all_parameters['init_mask'] = mask_img_url
|
|
|
|
metadata = self.parameters_to_generated_image_metadata(
|
|
all_parameters
|
|
)
|
|
|
|
command = parameters_to_command(all_parameters)
|
|
|
|
path = self.save_result_image(
|
|
image,
|
|
command,
|
|
metadata,
|
|
self.result_path,
|
|
postprocessing=postprocessing,
|
|
)
|
|
|
|
print(f'>> Image generated: "{path}"')
|
|
self.write_log_message(f'[Generated] "{path}": {command}')
|
|
|
|
if progress.total_iterations > progress.current_iteration:
|
|
progress.set_current_step(1)
|
|
progress.set_current_status('Iteration complete')
|
|
progress.set_current_status_has_steps(False)
|
|
else:
|
|
progress.mark_complete()
|
|
|
|
self.socketio.emit(
|
|
'progressUpdate', progress.to_formatted_dict()
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
self.socketio.emit(
|
|
'generationResult',
|
|
{
|
|
'url': self.get_url_from_image_path(path),
|
|
'mtime': os.path.getmtime(path),
|
|
'metadata': metadata,
|
|
},
|
|
)
|
|
eventlet.sleep(0)
|
|
|
|
progress.set_current_iteration(progress.current_iteration + 1)
|
|
|
|
self.generate.prompt2image(
|
|
**generation_parameters,
|
|
step_callback=image_progress,
|
|
image_callback=image_done,
|
|
)
|
|
|
|
except KeyboardInterrupt:
|
|
raise
|
|
except CanceledException:
|
|
self.socketio.emit('processingCanceled')
|
|
pass
|
|
except Exception as e:
|
|
print(e)
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def parameters_to_generated_image_metadata(self, parameters):
|
|
try:
|
|
# top-level metadata minus `image` or `images`
|
|
metadata = self.get_system_config()
|
|
# remove any image keys not mentioned in RFC #266
|
|
rfc266_img_fields = [
|
|
'type',
|
|
'postprocessing',
|
|
'sampler',
|
|
'prompt',
|
|
'seed',
|
|
'variations',
|
|
'steps',
|
|
'cfg_scale',
|
|
'threshold',
|
|
'perlin',
|
|
'step_number',
|
|
'width',
|
|
'height',
|
|
'extra',
|
|
'seamless',
|
|
'hires_fix',
|
|
]
|
|
|
|
rfc_dict = {}
|
|
|
|
for item in parameters.items():
|
|
key, value = item
|
|
if key in rfc266_img_fields:
|
|
rfc_dict[key] = value
|
|
|
|
postprocessing = []
|
|
|
|
# 'postprocessing' is either null or an
|
|
if 'facetool_strength' in parameters:
|
|
facetool_parameters = {
|
|
'type': str(parameters['facetool_type']),
|
|
'strength': float(parameters['facetool_strength']),
|
|
}
|
|
|
|
if parameters['facetool_type'] == 'codeformer':
|
|
facetool_parameters['fidelity'] = float(parameters['codeformer_fidelity'])
|
|
|
|
postprocessing.append(facetool_parameters)
|
|
|
|
if 'upscale' in parameters:
|
|
postprocessing.append(
|
|
{
|
|
'type': 'esrgan',
|
|
'scale': int(parameters['upscale'][0]),
|
|
'strength': float(parameters['upscale'][1]),
|
|
}
|
|
)
|
|
|
|
rfc_dict['postprocessing'] = (
|
|
postprocessing if len(postprocessing) > 0 else None
|
|
)
|
|
|
|
# semantic drift
|
|
rfc_dict['sampler'] = parameters['sampler_name']
|
|
|
|
# display weighted subprompts (liable to change)
|
|
subprompts = split_weighted_subprompts(parameters['prompt'], skip_normalize=True)
|
|
subprompts = [{'prompt': x[0], 'weight': x[1]} for x in subprompts]
|
|
rfc_dict['prompt'] = subprompts
|
|
|
|
# 'variations' should always exist and be an array, empty or consisting of {'seed': seed, 'weight': weight} pairs
|
|
variations = []
|
|
|
|
if 'with_variations' in parameters:
|
|
variations = [
|
|
{'seed': x[0], 'weight': x[1]}
|
|
for x in parameters['with_variations']
|
|
]
|
|
|
|
rfc_dict['variations'] = variations
|
|
|
|
if 'init_img' in parameters:
|
|
rfc_dict['type'] = 'img2img'
|
|
rfc_dict['strength'] = parameters['strength']
|
|
rfc_dict['fit'] = parameters['fit'] # TODO: Noncompliant
|
|
rfc_dict['orig_hash'] = calculate_init_img_hash(
|
|
self.get_image_path_from_url(parameters['init_img'])
|
|
)
|
|
rfc_dict['init_image_path'] = parameters[
|
|
'init_img'
|
|
] # TODO: Noncompliant
|
|
if 'init_mask' in parameters:
|
|
rfc_dict['mask_hash'] = calculate_init_img_hash(
|
|
self.get_image_path_from_url(parameters['init_mask'])
|
|
) # TODO: Noncompliant
|
|
rfc_dict['mask_image_path'] = parameters[
|
|
'init_mask'
|
|
] # TODO: Noncompliant
|
|
else:
|
|
rfc_dict['type'] = 'txt2img'
|
|
|
|
metadata['image'] = rfc_dict
|
|
|
|
return metadata
|
|
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def parameters_to_post_processed_image_metadata(
|
|
self, parameters, original_image_path
|
|
):
|
|
try:
|
|
current_metadata = retrieve_metadata(original_image_path)[
|
|
'sd-metadata'
|
|
]
|
|
postprocessing_metadata = {}
|
|
|
|
"""
|
|
if we don't have an original image metadata to reconstruct,
|
|
need to record the original image and its hash
|
|
"""
|
|
if 'image' not in current_metadata:
|
|
current_metadata['image'] = {}
|
|
|
|
orig_hash = calculate_init_img_hash(
|
|
self.get_image_path_from_url(original_image_path)
|
|
)
|
|
|
|
postprocessing_metadata['orig_path'] = (original_image_path,)
|
|
postprocessing_metadata['orig_hash'] = orig_hash
|
|
|
|
if parameters['type'] == 'esrgan':
|
|
postprocessing_metadata['type'] = 'esrgan'
|
|
postprocessing_metadata['scale'] = parameters['upscale'][0]
|
|
postprocessing_metadata['strength'] = parameters['upscale'][1]
|
|
elif parameters['type'] == 'gfpgan':
|
|
postprocessing_metadata['type'] = 'gfpgan'
|
|
postprocessing_metadata['strength'] = parameters[
|
|
'facetool_strength'
|
|
]
|
|
elif parameters['type'] == 'codeformer':
|
|
postprocessing_metadata['type'] = 'codeformer'
|
|
postprocessing_metadata['strength'] = parameters[
|
|
'facetool_strength'
|
|
]
|
|
postprocessing_metadata['fidelity'] = parameters['codeformer_fidelity']
|
|
|
|
else:
|
|
raise TypeError(f"Invalid type: {parameters['type']}")
|
|
|
|
if 'postprocessing' in current_metadata['image'] and isinstance(
|
|
current_metadata['image']['postprocessing'], list
|
|
):
|
|
current_metadata['image']['postprocessing'].append(
|
|
postprocessing_metadata
|
|
)
|
|
else:
|
|
current_metadata['image']['postprocessing'] = [
|
|
postprocessing_metadata
|
|
]
|
|
|
|
return current_metadata
|
|
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def save_result_image(
|
|
self,
|
|
image,
|
|
command,
|
|
metadata,
|
|
output_dir,
|
|
step_index=None,
|
|
postprocessing=False,
|
|
):
|
|
try:
|
|
pngwriter = PngWriter(output_dir)
|
|
prefix = pngwriter.unique_prefix()
|
|
|
|
seed = 'unknown_seed'
|
|
|
|
if 'image' in metadata:
|
|
if 'seed' in metadata['image']:
|
|
seed = metadata['image']['seed']
|
|
|
|
filename = f'{prefix}.{seed}'
|
|
|
|
if step_index:
|
|
filename += f'.{step_index}'
|
|
if postprocessing:
|
|
filename += f'.postprocessed'
|
|
|
|
filename += '.png'
|
|
|
|
path = pngwriter.save_image_and_prompt_to_png(
|
|
image=image,
|
|
dream_prompt=command,
|
|
metadata=metadata,
|
|
name=filename,
|
|
)
|
|
|
|
return os.path.abspath(path)
|
|
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def make_unique_init_image_filename(self, name):
|
|
try:
|
|
uuid = uuid4().hex
|
|
split = os.path.splitext(name)
|
|
name = f'{split[0]}.{uuid}{split[1]}'
|
|
return name
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def calculate_real_steps(self, steps, strength, has_init_image):
|
|
import math
|
|
|
|
return math.floor(strength * steps) if has_init_image else steps
|
|
|
|
def write_log_message(self, message):
|
|
"""Logs the filename and parameters used to generate or process that image to log file"""
|
|
try:
|
|
message = f'{message}\n'
|
|
with open(self.log_path, 'a', encoding='utf-8') as file:
|
|
file.writelines(message)
|
|
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def get_image_path_from_url(self, url):
|
|
"""Given a url to an image used by the client, returns the absolute file path to that image"""
|
|
try:
|
|
if 'init-images' in url:
|
|
return os.path.abspath(
|
|
os.path.join(self.init_image_path, os.path.basename(url))
|
|
)
|
|
elif 'mask-images' in url:
|
|
return os.path.abspath(
|
|
os.path.join(self.mask_image_path, os.path.basename(url))
|
|
)
|
|
elif 'intermediates' in url:
|
|
return os.path.abspath(
|
|
os.path.join(self.intermediate_path, os.path.basename(url))
|
|
)
|
|
else:
|
|
return os.path.abspath(
|
|
os.path.join(self.result_path, os.path.basename(url))
|
|
)
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def get_url_from_image_path(self, path):
|
|
"""Given an absolute file path to an image, returns the URL that the client can use to load the image"""
|
|
try:
|
|
if 'init-images' in path:
|
|
return os.path.join(
|
|
self.init_image_url, os.path.basename(path)
|
|
)
|
|
elif 'mask-images' in path:
|
|
return os.path.join(
|
|
self.mask_image_url, os.path.basename(path)
|
|
)
|
|
elif 'intermediates' in path:
|
|
return os.path.join(
|
|
self.intermediate_url, os.path.basename(path)
|
|
)
|
|
else:
|
|
return os.path.join(self.result_url, os.path.basename(path))
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
def save_file_unique_uuid_name(self, bytes, name, path):
|
|
try:
|
|
uuid = uuid4().hex
|
|
split = os.path.splitext(name)
|
|
name = f'{split[0]}.{uuid}{split[1]}'
|
|
file_path = os.path.join(path, name)
|
|
os.makedirs(os.path.dirname(file_path), exist_ok=True)
|
|
newFile = open(file_path, 'wb')
|
|
newFile.write(bytes)
|
|
return file_path
|
|
except Exception as e:
|
|
self.socketio.emit('error', {'message': (str(e))})
|
|
print('\n')
|
|
|
|
traceback.print_exc()
|
|
print('\n')
|
|
|
|
|
|
class Progress:
|
|
def __init__(self, generation_parameters=None):
|
|
self.current_step = 1
|
|
self.total_steps = (
|
|
self._calculate_real_steps(
|
|
steps=generation_parameters['steps'],
|
|
strength=generation_parameters['strength']
|
|
if 'strength' in generation_parameters
|
|
else None,
|
|
has_init_image='init_img' in generation_parameters,
|
|
)
|
|
if generation_parameters
|
|
else 1
|
|
)
|
|
self.current_iteration = 1
|
|
self.total_iterations = (
|
|
generation_parameters['iterations'] if generation_parameters else 1
|
|
)
|
|
self.current_status = 'Preparing'
|
|
self.is_processing = True
|
|
self.current_status_has_steps = False
|
|
self.has_error = False
|
|
|
|
def set_current_step(self, current_step):
|
|
self.current_step = current_step
|
|
|
|
def set_total_steps(self, total_steps):
|
|
self.total_steps = total_steps
|
|
|
|
def set_current_iteration(self, current_iteration):
|
|
self.current_iteration = current_iteration
|
|
|
|
def set_total_iterations(self, total_iterations):
|
|
self.total_iterations = total_iterations
|
|
|
|
def set_current_status(self, current_status):
|
|
self.current_status = current_status
|
|
|
|
def set_is_processing(self, is_processing):
|
|
self.is_processing = is_processing
|
|
|
|
def set_current_status_has_steps(self, current_status_has_steps):
|
|
self.current_status_has_steps = current_status_has_steps
|
|
|
|
def set_has_error(self, has_error):
|
|
self.has_error = has_error
|
|
|
|
def mark_complete(self):
|
|
self.current_status = 'Processing Complete'
|
|
self.current_step = 0
|
|
self.total_steps = 0
|
|
self.current_iteration = 0
|
|
self.total_iterations = 0
|
|
self.is_processing = False
|
|
|
|
def to_formatted_dict(
|
|
self,
|
|
):
|
|
return {
|
|
'currentStep': self.current_step,
|
|
'totalSteps': self.total_steps,
|
|
'currentIteration': self.current_iteration,
|
|
'totalIterations': self.total_iterations,
|
|
'currentStatus': self.current_status,
|
|
'isProcessing': self.is_processing,
|
|
'currentStatusHasSteps': self.current_status_has_steps,
|
|
'hasError': self.has_error,
|
|
}
|
|
|
|
def _calculate_real_steps(self, steps, strength, has_init_image):
|
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return math.floor(strength * steps) if has_init_image else steps
|
|
|
|
|
|
class CanceledException(Exception):
|
|
pass
|