初始化换发型项目：3个微服务代码 + 部署脚本

包含： - hair_service_sd: 换发型/换发色算法服务 (端口 8801) - photo_service: LoRA 训练调度服务 (端口 32678) - stable-diffusion-webui: SD WebUI 推理服务 (端口 57860) - kohya_ss_home: 训练环境代码 - meidaojia: 监控测试脚本 - setup.sh: 一键部署脚本 (conda环境恢复 + 配置生成 + 完整性检查) - start_all_services.sh: 启动3个服务 - configure.ini.template: 路径模板化 (BASE_DIR自动推导) - conda_envs/py310.yml: py310 环境定义大文件 (weights/, models/, data/, conda_envs/*.tar.gz 等) 通过 .gitignore 排除，由网盘单独上传。
2026-07-11 18:11:49 +08:00
commit 0eb61f3e60
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+import json
+from contextlib import closing
+
+import modules.scripts
+from modules import processing, infotext_utils
+from modules.infotext_utils import create_override_settings_dict, parse_generation_parameters
+from modules.shared import opts
+import modules.shared as shared
+from modules.ui import plaintext_to_html
+from PIL import Image
+import gradio as gr
+
+
+def txt2img_create_processing(id_task: str, request: gr.Request, prompt: str, negative_prompt: str, prompt_styles, n_iter: int, batch_size: int, cfg_scale: float, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_checkpoint_name: str, hr_sampler_name: str, hr_scheduler: str, hr_prompt: str, hr_negative_prompt, override_settings_texts, *args, force_enable_hr=False):
+    override_settings = create_override_settings_dict(override_settings_texts)
+
+    if force_enable_hr:
+        enable_hr = True
+
+    p = processing.StableDiffusionProcessingTxt2Img(
+        sd_model=shared.sd_model,
+        outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
+        outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
+        prompt=prompt,
+        styles=prompt_styles,
+        negative_prompt=negative_prompt,
+        batch_size=batch_size,
+        n_iter=n_iter,
+        cfg_scale=cfg_scale,
+        width=width,
+        height=height,
+        enable_hr=enable_hr,
+        denoising_strength=denoising_strength,
+        hr_scale=hr_scale,
+        hr_upscaler=hr_upscaler,
+        hr_second_pass_steps=hr_second_pass_steps,
+        hr_resize_x=hr_resize_x,
+        hr_resize_y=hr_resize_y,
+        hr_checkpoint_name=None if hr_checkpoint_name == 'Use same checkpoint' else hr_checkpoint_name,
+        hr_sampler_name=None if hr_sampler_name == 'Use same sampler' else hr_sampler_name,
+        hr_scheduler=None if hr_scheduler == 'Use same scheduler' else hr_scheduler,
+        hr_prompt=hr_prompt,
+        hr_negative_prompt=hr_negative_prompt,
+        override_settings=override_settings,
+    )
+
+    p.scripts = modules.scripts.scripts_txt2img
+    p.script_args = args
+
+    p.user = request.username
+
+    if shared.opts.enable_console_prompts:
+        print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
+
+    return p
+
+
+def txt2img_upscale(id_task: str, request: gr.Request, gallery, gallery_index, generation_info, *args):
+    assert len(gallery) > 0, 'No image to upscale'
+    assert 0 <= gallery_index < len(gallery), f'Bad image index: {gallery_index}'
+
+    p = txt2img_create_processing(id_task, request, *args, force_enable_hr=True)
+    p.batch_size = 1
+    p.n_iter = 1
+    # txt2img_upscale attribute that signifies this is called by txt2img_upscale
+    p.txt2img_upscale = True
+
+    geninfo = json.loads(generation_info)
+
+    image_info = gallery[gallery_index] if 0 <= gallery_index < len(gallery) else gallery[0]
+    p.firstpass_image = infotext_utils.image_from_url_text(image_info)
+
+    parameters = parse_generation_parameters(geninfo.get('infotexts')[gallery_index], [])
+    p.seed = parameters.get('Seed', -1)
+    p.subseed = parameters.get('Variation seed', -1)
+
+    p.override_settings['save_images_before_highres_fix'] = False
+
+    with closing(p):
+        processed = modules.scripts.scripts_txt2img.run(p, *p.script_args)
+
+        if processed is None:
+            processed = processing.process_images(p)
+
+    shared.total_tqdm.clear()
+
+    new_gallery = []
+    for i, image in enumerate(gallery):
+        if i == gallery_index:
+            geninfo["infotexts"][gallery_index: gallery_index+1] = processed.infotexts
+            new_gallery.extend(processed.images)
+        else:
+            fake_image = Image.new(mode="RGB", size=(1, 1))
+            fake_image.already_saved_as = image["name"].rsplit('?', 1)[0]
+            new_gallery.append(fake_image)
+
+    geninfo["infotexts"][gallery_index] = processed.info
+
+    return new_gallery, json.dumps(geninfo), plaintext_to_html(processed.info), plaintext_to_html(processed.comments, classname="comments")
+
+
+def txt2img(id_task: str, request: gr.Request, *args):
+    p = txt2img_create_processing(id_task, request, *args)
+
+    with closing(p):
+        processed = modules.scripts.scripts_txt2img.run(p, *p.script_args)
+
+        if processed is None:
+            processed = processing.process_images(p)
+
+    shared.total_tqdm.clear()
+
+    generation_info_js = processed.js()
+    if opts.samples_log_stdout:
+        print(generation_info_js)
+
+    if opts.do_not_show_images:
+        processed.images = []
+
+    return processed.images, generation_info_js, plaintext_to_html(processed.info), plaintext_to_html(processed.comments, classname="comments")