diff --git a/nodes/nano_banana_v2.py b/nodes/nano_banana_v2.py index 1293f84..d57fb35 100644 --- a/nodes/nano_banana_v2.py +++ b/nodes/nano_banana_v2.py @@ -244,6 +244,13 @@ class NanoBananaV2: ) return error_msg + @staticmethod + def _apply_image_format(img: Image.Image, image_format: str) -> Image.Image: + """按指定格式处理图像：JPEG 时转 RGB（质量100不压缩），PNG 不做处理""" + if image_format == "JPEG" and img.mode in ("RGBA", "LA", "P"): + return img.convert("RGB") + return img + @staticmethod def _check_interrupt(): """检查 ComfyUI 是否点击了取消按钮，是则抛出 InterruptProcessingException""" @@ -701,20 +708,69 @@ class NanoBananaV2Batch(NanoBananaV2): def INPUT_TYPES(cls): types = super().INPUT_TYPES() - # 批量专用：文件夹图片路径 + # 按指定顺序重建 optional + new_optional = {} + + # 1. 联网功能（Provider 专有参数） + for provider_extra in cls._PROVIDER_EXTRA_INPUTS.values(): + for k, v in provider_extra.items(): + if k in types["optional"]: + new_optional[k] = types["optional"][k] + + # 2. 图片格式 + new_optional["图片格式"] = (["PNG", "JPEG"], {"default": "JPEG"}) + + # 3. seed + if "seed" in types["optional"]: + new_optional["seed"] = types["optional"]["seed"] + + # 4. 图片配对模式 + new_optional["图片配对模式"] = (["不配对", "按相同图片命名", "1*N"], { + "default": "不配对" + }) + + # 5. 图片命名规则 + new_optional["图片命名规则"] = (["和图片同名", "1,2,3,4..."], { + "default": "和图片同名" + }) + + # 6. 图片保存路径（可选） + new_optional["图片保存路径（可选）"] = ("STRING", { + "default": "", + "multiline": False, + "placeholder": "留空默认保存到 ComfyUI/output；填写则保存到指定路径" + }) + + # 7. 图片路径（图1-5） for i in range(1, 6): - types["optional"][f"图片路径（图{i}）"] = ("STRING", { + new_optional[f"图片路径（图{i}）"] = ("STRING", { "default": "", "multiline": False, "placeholder": f"填写后将加载文件夹中的图片作为第{i}组参考图" }) - types["optional"]["图片配对模式"] = (["不配对", "按相同图片命名", "1*N"], { - "default": "不配对" - }) + # 8. 分组令牌 + if "分组令牌" in types["optional"]: + new_optional["分组令牌"] = types["optional"]["分组令牌"] - # 批量版恢复较大的生图数量上限 - types["required"]["生图数量"] = ("INT", { + # 9. 代理端口 + if "代理端口" in types["optional"]: + new_optional["代理端口"] = types["optional"]["代理端口"] + + # 保留参考图1-9 + for i in range(1, 10): + key = f"参考图{i}" + if key in types["optional"]: + new_optional[key] = types["optional"][key] + + types["optional"] = new_optional + + # 批量版隐藏生图数量参数，固定为1 + if "生图数量" in types["required"]: + del types["required"]["生图数量"] + if "hidden" not in types: + types["hidden"] = {} + types["hidden"]["生图数量"] = ("INT", { "default": 1, "min": 1, "max": 1000, @@ -748,13 +804,18 @@ class NanoBananaV2Batch(NanoBananaV2): aspect_ratio: str, images_per_prompt: int, input_images: List[Image.Image], + image_format: str = "JPEG", + save_path: str = "", + save_naming: str = "{src}_{sub}.png", pbar=None, per_task_images: Optional[List[List[Image.Image]]] = None, + per_task_names: Optional[List[str]] = None, **extra_kwargs, ) -> List[dict]: """全并发处理：所有任务一次性提交，谁先完成谁先落盘 per_task_images: 可选，每个任务专属的图片列表，与 input_images 合并 + per_task_names: 可选，每个任务的源文件名列表，用于命名时保持与输入图片一致 """ # 构建任务定义 tasks_def = [] @@ -768,7 +829,11 @@ class NanoBananaV2Batch(NanoBananaV2): # 初始化输出目录 self._output_file_paths = [] - self._output_dir = self._get_output_dir() + if save_path: + self._output_dir = save_path + else: + self._output_dir = self._get_output_dir() + os.makedirs(self._output_dir, exist_ok=True) print(f"{self.NODE_LABEL}: 输出目录: {self._output_dir}") _on_progress = (lambda delta: pbar.update(delta)) if pbar is not None else None @@ -816,14 +881,45 @@ class NanoBananaV2Batch(NanoBananaV2): "prompt": "", } - # 即时落盘 + # 即时落盘（应用图片格式转换 + 自定义命名规则） if result_data and result_data.get("success"): + ext = "jpg" if image_format == "JPEG" else "png" + # 源文件名（优先使用输入图片名，保持命名一致） + task_idx = result_data.get("global_task_index", completed) + source_name = "" + if per_task_names and task_idx < len(per_task_names): + source_name = per_task_names[task_idx] + prompt_snippet = (result_data.get("prompt", "") or "").replace("\n", " ")[:20] + prompt_sanitized = "".join(c for c in prompt_snippet if c.isalnum() or c in "._- ") + time_str = time.strftime("%Y%m%d_%H%M%S") for img_idx, img in enumerate(result_data.get("output_images", [])): - filepath = os.path.join( - self._output_dir, - f"task_{completed:04d}_{img_idx:02d}.png" - ) - img.save(filepath) + img = self._apply_image_format(img, image_format) + # 构建文件名 + filename = save_naming + filename = filename.replace("{src}", source_name) + filename = filename.replace("{index}", str(task_idx)) + filename = filename.replace("{i}", str(task_idx)) + filename = filename.replace("{num}", str(task_idx + 1)) + filename = filename.replace("{n}", str(task_idx + 1)) + filename = filename.replace("{sub}", str(img_idx)) + filename = filename.replace("{prompt}", prompt_sanitized) + filename = filename.replace("{time}", time_str) + # 确保扩展名正确 + if not filename.lower().endswith(f".{ext}"): + base, _ = os.path.splitext(filename) + filename = f"{base}.{ext}" + # 防覆盖 + filepath = os.path.join(self._output_dir, filename) + if os.path.exists(filepath): + base, file_ext = os.path.splitext(filename) + counter = 1 + while os.path.exists(filepath): + filepath = os.path.join(self._output_dir, f"{base}_{counter}{file_ext}") + counter += 1 + if image_format == "JPEG": + img.save(filepath, "JPEG", quality=100) + else: + img.save(filepath) self._output_file_paths.append(filepath) # 释放内存中的图像对象 result_data["saved_count"] = len(result_data.get("output_images", [])) @@ -851,7 +947,7 @@ class NanoBananaV2Batch(NanoBananaV2): 模型: str, 宽高比: str, 分辨率: str, - 生图数量: int, + 生图数量: int = 1, **kwargs ) -> Tuple[torch.Tensor]: """生成图像（异步模式 - 批量版：全并发 + 即时落盘）""" @@ -860,6 +956,13 @@ class NanoBananaV2Batch(NanoBananaV2): seed: int = kwargs.pop("seed", 0) proxy_port: str = kwargs.pop("代理端口", "") api_key_override: str = kwargs.pop("分组令牌", "") + image_format: str = kwargs.pop("图片格式", "JPEG") + save_path: str = kwargs.pop("图片保存路径（可选）", "").strip() + 命名规则选择: str = kwargs.pop("图片命名规则", "和图片同名") + if 命名规则选择 == "1,2,3,4...": + save_naming = "{num}.png" + else: + save_naming = "{src}_{sub}.png" proxy_url = BaseAsyncImageProvider.build_proxy_url(proxy_port) provider = self._get_provider(模型, proxy_url=proxy_url, api_key_override=api_key_override) @@ -916,6 +1019,7 @@ class NanoBananaV2Batch(NanoBananaV2): pairing_mode = kwargs.pop("图片配对模式", "不配对") per_task_images = None + per_task_names = None if folder_paths: # 按文件夹分组加载 folder_image_lists = [] # List[List[ImageInfo]] @@ -941,15 +1045,20 @@ class NanoBananaV2Batch(NanoBananaV2): if pairs: batch_prompts = parse_batch_prompts(prompt) per_task_images = [] + per_task_names = [] prompts_list = [] for pair in pairs: task_imgs = [info.image for info in pair] + list(input_images) + # 取第一张输入图的文件名作为源名，保持命名一致 + src_name = pair[0].filename if pair else "" if batch_prompts: for bp in batch_prompts: per_task_images.append(list(task_imgs)) + per_task_names.append(src_name) prompts_list.append(bp) else: per_task_images.append(list(task_imgs)) + per_task_names.append(src_name) prompts_list.append(prompt) images_per_prompt = 1 @@ -1001,8 +1110,12 @@ class NanoBananaV2Batch(NanoBananaV2): aspect_ratio=宽高比, images_per_prompt=images_per_prompt, input_images=input_images, + image_format=image_format, + save_path=save_path, + save_naming=save_naming, pbar=pbar, per_task_images=per_task_images, + per_task_names=per_task_names, **extra_kwargs, ) )