| import threading | |
| buffer = [] | |
| outputs = [] | |
| is_working = False | |
| def worker(): | |
| global buffer, outputs, is_working | |
| import time | |
| import shared | |
| import random | |
| import modules.default_pipeline as pipeline | |
| import modules.path | |
| import modules.patch | |
| from modules.sdxl_styles import apply_style, aspect_ratios | |
| from modules.private_logger import log | |
| try: | |
| async_gradio_app = shared.gradio_root | |
| flag = f'''App started successful. Use the app with {str(async_gradio_app.local_url)} or {str(async_gradio_app.server_name)}:{str(async_gradio_app.server_port)}''' | |
| if async_gradio_app.share: | |
| flag += f''' or {async_gradio_app.share_url}''' | |
| print(flag) | |
| except Exception as e: | |
| print(e) | |
| def handler(task): | |
| prompt, style_selection = task | |
| steps = 30 | |
| switch = 20 | |
| aspect_ratios_selection = '1280×768' | |
| seed = random.randint(1, int(1024*1024*1024)) | |
| sharpness = 10.0 | |
| loras=[(modules.path.default_lora_name, modules.path.default_lora_weight), ('None', 0.5), ('None', 0.5), ('None', 0.5), ('None', 0.5)] | |
| modules.patch.sharpness = sharpness | |
| pipeline.refresh_base_model(modules.path.default_base_model_name) | |
| pipeline.refresh_refiner_model(modules.path.default_refiner_model_name) | |
| pipeline.refresh_loras(loras) | |
| pipeline.clean_prompt_cond_caches() | |
| p_txt, n_txt = apply_style(style_selection, prompt) | |
| width, height = aspect_ratios[aspect_ratios_selection] | |
| results = [] | |
| def callback(step, x0, x, total_steps, y): | |
| done_steps = step | |
| outputs.append(['preview', ( | |
| int(100.0 * float(done_steps) / float(steps)), | |
| f'{step}/{total_steps}', | |
| y)]) | |
| img = pipeline.process(p_txt, n_txt, steps, switch, width, height, seed, callback=callback) | |
| for x in img: | |
| d = [ | |
| ('Prompt', prompt), | |
| ('Style', style_selection), | |
| ('Seed', seed) | |
| ] | |
| for n, w in loras: | |
| if n != 'None': | |
| d.append((f'LoRA [{n}] weight', w)) | |
| log(x, d) | |
| outputs.append(['results', img]) | |
| return | |
| while True: | |
| time.sleep(0.01) | |
| if len(buffer) > 0: | |
| is_working=True | |
| task = buffer.pop(0) | |
| handler(task) | |
| is_working=False | |
| pass | |
| threading.Thread(target=worker, daemon=True).start() | |