diff --git a/main.py b/main.py index 676bb51..c267436 100644 --- a/main.py +++ b/main.py @@ -19,7 +19,7 @@ import matplotlib.pyplot as plt from config_manager import ConfigManager, OUTPUT_DIR from llm_service import LLMService -from sd_service import SDService, DEFAULT_NEGATIVE, FACE_IMAGE_PATH +from sd_service import SDService, DEFAULT_NEGATIVE, FACE_IMAGE_PATH, SD_PRESET_NAMES, get_sd_preset from mcp_client import MCPClient, get_mcp_client # ================= matplotlib 中文字体配置 ================= @@ -309,22 +309,37 @@ def generate_copy(model, topic, style): return "", "", "", "", f"❌ 生成失败: {e}" -def generate_images(sd_url, prompt, neg_prompt, model, steps, cfg_scale, face_swap_on, face_img): - """生成图片（可选 ReActor 换脸）""" +def generate_images(sd_url, prompt, neg_prompt, model, steps, cfg_scale, face_swap_on, face_img, quality_mode): + """生成图片（可选 ReActor 换脸，支持质量模式预设）""" if not model: return None, [], "❌ 未选择 SD 模型" try: svc = SDService(sd_url) # 判断是否启用换脸 face_image = None - if face_swap_on and face_img is not None: - if isinstance(face_img, Image.Image): - face_image = face_img - elif isinstance(face_img, str) and os.path.isfile(face_img): - face_image = Image.open(face_img).convert("RGB") - if face_swap_on and face_image is None: - # 尝试从默认路径加载 - face_image = SDService.load_face_image() + if face_swap_on: + # Gradio 可能传 PIL.Image / numpy.ndarray / 文件路径 / None + if face_img is not None: + if isinstance(face_img, Image.Image): + face_image = face_img + elif isinstance(face_img, str) and os.path.isfile(face_img): + face_image = Image.open(face_img).convert("RGB") + else: + # numpy array 等其他格式 + try: + import numpy as np + if isinstance(face_img, np.ndarray): + face_image = Image.fromarray(face_img).convert("RGB") + logger.info("头像从 numpy array 转换为 PIL Image") + except Exception as e: + logger.warning("头像格式转换失败 (%s): %s", type(face_img).__name__, e) + # 如果 UI 没传有效头像，从本地文件加载 + if face_image is None: + face_image = SDService.load_face_image() + if face_image is not None: + logger.info("换脸头像已就绪: %dx%d", face_image.width, face_image.height) + else: + logger.warning("换脸已启用但未找到有效头像") images = svc.txt2img( prompt=prompt, @@ -333,9 +348,11 @@ def generate_images(sd_url, prompt, neg_prompt, model, steps, cfg_scale, face_sw steps=int(steps), cfg_scale=float(cfg_scale), face_image=face_image, + quality_mode=quality_mode, ) + preset = get_sd_preset(quality_mode) swap_hint = " (已换脸)" if face_image else "" - return images, images, f"✅ 生成 {len(images)} 张图片{swap_hint}" + return images, images, f"✅ 生成 {len(images)} 张图片{swap_hint} [{quality_mode}]" except Exception as e: logger.error("图片生成失败: %s", e) return None, [], f"❌ 绘图失败: {e}" @@ -1976,7 +1993,9 @@ def auto_publish_once(topics_str, mcp_url, sd_url_val, sd_model_name, model, fac _auto_log_append("🎭 换脸已启用") else: _auto_log_append("⚠️ 换脸已启用但未找到头像，跳过换脸") - images = sd_svc.txt2img(prompt=sd_prompt, model=sd_model_name, face_image=face_image) + images = sd_svc.txt2img(prompt=sd_prompt, model=sd_model_name, + face_image=face_image, + quality_mode="快速 (约30秒)") if not images: _record_error() return "❌ 图片生成失败：没有返回图片" @@ -2529,12 +2548,18 @@ with gr.Blocks( gr.Markdown("---") gr.Markdown("### 🎨 绘图参数") - with gr.Accordion("高级设置", open=False): + quality_mode = gr.Radio( + SD_PRESET_NAMES, + label="生成模式", + value="标准 (约1分钟)", + info="快速≈30s 标准≈1min 精细≈2-3min (SDXL)", + ) + with gr.Accordion("高级设置 (覆盖预设)", open=False): neg_prompt = gr.Textbox( label="反向提示词", value=DEFAULT_NEGATIVE, lines=2, ) - steps = gr.Slider(15, 50, value=25, step=1, label="步数") - cfg_scale = gr.Slider(1, 15, value=7, step=0.5, label="CFG Scale") + steps = gr.Slider(8, 50, value=20, step=1, label="步数") + cfg_scale = gr.Slider(1, 15, value=5.5, step=0.5, label="CFG Scale") btn_gen_img = gr.Button("🎨 第二步：生成图片", variant="primary") # 中栏：文案编辑 @@ -3093,10 +3118,21 @@ with gr.Blocks( outputs=[res_title, res_content, res_prompt, res_tags, status_bar], ) + # 生成模式切换 → 同步更新步数/CFG预览 + def on_quality_mode_change(mode): + p = get_sd_preset(mode) + return p["steps"], p["cfg_scale"] + + quality_mode.change( + fn=on_quality_mode_change, + inputs=[quality_mode], + outputs=[steps, cfg_scale], + ) + btn_gen_img.click( fn=generate_images, inputs=[sd_url, res_prompt, neg_prompt, sd_model, steps, cfg_scale, - face_swap_toggle, face_image_preview], + face_swap_toggle, face_image_preview, quality_mode], outputs=[gallery, state_images, status_bar], ) diff --git a/sd_service.py b/sd_service.py index f3fe76a..320d4d4 100644 --- a/sd_service.py +++ b/sd_service.py @@ -16,6 +16,46 @@ SD_TIMEOUT = 1800 # 图片生成可能需要较长时间 # 头像文件默认保存路径 FACE_IMAGE_PATH = os.path.join(os.path.dirname(__file__), "my_face.png") +# ==================== 生成质量预设 ==================== +# 针对 JuggernautXL (SDXL) 优化的三档参数 +SD_PRESETS = { + "快速 (约30秒)": { + "steps": 12, + "cfg_scale": 5.0, + "width": 768, + "height": 1024, + "sampler_name": "Euler a", + "scheduler": "Normal", + "batch_size": 2, + }, + "标准 (约1分钟)": { + "steps": 20, + "cfg_scale": 5.5, + "width": 832, + "height": 1216, + "sampler_name": "DPM++ 2M", + "scheduler": "Karras", + "batch_size": 2, + }, + "精细 (约2-3分钟)": { + "steps": 35, + "cfg_scale": 6.0, + "width": 832, + "height": 1216, + "sampler_name": "DPM++ 2M SDE", + "scheduler": "Karras", + "batch_size": 2, + }, +} + +SD_PRESET_NAMES = list(SD_PRESETS.keys()) + + +def get_sd_preset(name: str) -> dict: + """获取生成预设参数，默认返回'标准'""" + return SD_PRESETS.get(name, SD_PRESETS["标准 (约1分钟)"]) + + # 默认反向提示词（针对 JuggernautXL / SDXL 优化，偏向东方审美） DEFAULT_NEGATIVE = ( "nsfw, nudity, lowres, bad anatomy, bad hands, text, error, missing fingers, " @@ -97,24 +137,23 @@ class SDService: 1, # 10: upscaler visibility False, # 11: swap in source True, # 12: swap in generated - "Minimum", # 13: log level - "No", # 14: gender detection (source) - "No", # 15: gender detection (target) + 1, # 13: console log level (0=min, 1=med, 2=max) + 0, # 14: gender detection source (0=No) + 0, # 15: gender detection target (0=No) False, # 16: save original - 0.6, # 17: CodeFormer weight (fidelity) - True, # 18: source hash check + 0.8, # 17: CodeFormer weight (0=max effect, 1=min) + False, # 18: source hash check False, # 19: target hash check "CUDA", # 20: execution provider True, # 21: face mask correction - "Image(s)", # 22: select source type - "None", # 23: face model name - "", # 24: source folder - None, # 25: multiple source images + 0, # 22: select source (0=Image, 1=FaceModel, 2=Folder) + "", # 23: face model filename (when #22=1) + "", # 24: source folder path (when #22=2) + None, # 25: skip for API False, # 26: random image False, # 27: force upscale - 0.5, # 28: detection threshold - 0, # 29: max faces (0 = no limit) - "tab_single", # 30: tab + 0.6, # 28: face detection threshold + 2, # 29: max faces to detect (0=unlimited) ], } } @@ -164,36 +203,44 @@ class SDService: prompt: str, negative_prompt: str = DEFAULT_NEGATIVE, model: str = None, - steps: int = 30, - cfg_scale: float = 5.0, - width: int = 832, - height: int = 1216, - batch_size: int = 2, + steps: int = None, + cfg_scale: float = None, + width: int = None, + height: int = None, + batch_size: int = None, seed: int = -1, - sampler_name: str = "DPM++ 2M", - scheduler: str = "Karras", + sampler_name: str = None, + scheduler: str = None, face_image: Image.Image = None, + quality_mode: str = None, ) -> list[Image.Image]: """文生图（参数针对 JuggernautXL 优化） Args: face_image: 头像 PIL Image，传入后自动启用 ReActor 换脸 + quality_mode: 预设模式名，如 '快速 (约30秒)' / '标准 (约1分钟)' / '精细 (约2-3分钟)' + 传入后自动应用预设参数，其余参数可覆盖 """ if model: self.switch_model(model) + # 加载预设作为基底，再用显式参数覆盖 + preset = get_sd_preset(quality_mode) if quality_mode else get_sd_preset("标准 (约1分钟)") payload = { "prompt": prompt, "negative_prompt": negative_prompt, - "steps": steps, - "cfg_scale": cfg_scale, - "width": width, - "height": height, - "batch_size": batch_size, + "steps": steps if steps is not None else preset["steps"], + "cfg_scale": cfg_scale if cfg_scale is not None else preset["cfg_scale"], + "width": width if width is not None else preset["width"], + "height": height if height is not None else preset["height"], + "batch_size": batch_size if batch_size is not None else preset["batch_size"], "seed": seed, - "sampler_name": sampler_name, - "scheduler": scheduler, + "sampler_name": sampler_name if sampler_name is not None else preset["sampler_name"], + "scheduler": scheduler if scheduler is not None else preset["scheduler"], } + logger.info("SD 生成参数: steps=%s, cfg=%.1f, %dx%d, sampler=%s", + payload['steps'], payload['cfg_scale'], + payload['width'], payload['height'], payload['sampler_name']) # 如果提供了头像，通过 ReActor 换脸 if face_image is not None: