PERF 修图节点改为生/修图节点
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@ -85,8 +85,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"Jinja2RenderTemplate": "Jinja2格式Prompt模板渲染",
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"JMGestureCorrect": "人物侧身图片转为正面图-即梦",
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"ModalClothesMask": "模特指定衣服替换为指定颜色",
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"ModalEditCustom": "自定义Prompt修改图片",
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"ModalMidJourneyGenerateImage": "Prompt修图",
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"ModalEditCustom": "Prompt生/修图",
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"ModalMidJourneyGenerateImage": "Prompt生/修图",
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"ModalMidJourneyDescribeImage": "反推生图提示词",
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"JMCustom": "Prompt生视频",
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"VideoMerge":"顺序合并视频"
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@ -78,7 +78,7 @@ class ModalClothesMask:
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RETURN_NAMES = ("image",)
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FUNCTION = "process"
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OUTPUT_NODE = False
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CATEGORY = "不忘科技-自定义节点🚩/图片/Gemini图像编辑"
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CATEGORY = "不忘科技-自定义节点🚩/图片/Gemini"
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def process(self, image: torch.Tensor, mask_color: str, clothes_type: str, endpoint: str):
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try:
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@ -133,21 +133,23 @@ class ModalEditCustom:
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def INPUT_TYPES(cls):
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return {
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"required": {
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"image": ("IMAGE",),
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"prompt": ("STRING", {"default": "将背景去除，输出原尺寸图片", "multiline": True}),
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"temperature": ("FLOAT", {"default": 0.1, "min": 0, "max": 2}),
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"topP": ("FLOAT", {"default": 0.7, "min": 0, "max": 1}),
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"endpoint": ("STRING", {"default": "bowongai-dev--bowong-ai-video-gemini-fastapi-webapp.modal.run"}),
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},
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"optional": {
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"image": ("IMAGE",),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("image",)
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FUNCTION = "process"
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OUTPUT_NODE = False
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CATEGORY = "不忘科技-自定义节点🚩/图片/Gemini图像编辑"
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CATEGORY = "不忘科技-自定义节点🚩/图片/Gemini"
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def process(self, image: torch.Tensor, prompt: str, temperature: float, topP: float, endpoint: str):
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def process(self, prompt: str, temperature: float, topP: float, endpoint: str, **kwargs):
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try:
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timeout = 60
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logger.info("获取token")
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@ -155,6 +157,13 @@ class ModalEditCustom:
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headers={'Authorization': 'Bearer bowong7777'}, timeout=timeout).json()[
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"access_token"]
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format = "PNG"
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if "image" in kwargs and kwargs["image"] is not None:
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image = kwargs["image"]
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files = {"origin_image": (
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'image.' + format.lower(), tensor_to_image_bytes(image, format),
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f'image/{format.lower()}')}
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else:
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files = None
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logger.info("请求图像编辑")
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job_resp = send_request("post", f"https://{endpoint}/google/image/edit_custom",
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headers={'x-google-api-key': api_key},
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@ -163,9 +172,7 @@ class ModalEditCustom:
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"temperature": temperature,
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"topP": topP
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},
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files={"origin_image": (
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'image.' + format.lower(), tensor_to_image_bytes(image, format),
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f'image/{format.lower()}')},
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files=files,
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timeout=timeout)
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job_resp.raise_for_status()
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job_resp = job_resp.json()
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@ -202,10 +209,12 @@ class ModalMidJourneyGenerateImage:
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return {
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"required": {
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"prompt": ("STRING", {"default": "一幅宏大壮美的山川画卷", "multiline": True}),
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"image": ("IMAGE",),
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"endpoint": ("STRING", {"default": "bowongai-dev--text-video-agent-fastapi-app.modal.run"}),
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"timeout": ("INT", {"default": 120, "min": 10, "max": 600}),
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},
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"optional": {
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"image": ("IMAGE",),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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@ -214,23 +223,28 @@ class ModalMidJourneyGenerateImage:
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OUTPUT_NODE = False
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CATEGORY = "不忘科技-自定义节点🚩/图片/Midjourney"
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def process(self, prompt: str, image:torch.Tensor, endpoint: str, timeout: int):
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def process(self, prompt: str, endpoint: str, timeout: int, **kwargs):
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try:
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logger.info("请求异步接口")
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interval = 2
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format = "PNG"
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if "image" in kwargs and kwargs["image"] is not None:
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image = kwargs["image"]
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files = {"img_file": (
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'image.' + format.lower(), tensor_to_image_bytes(image, format),
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f'image/{format.lower()}')}
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else:
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files = None
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job_resp = send_request("post", f"https://{endpoint}/api/mj/async/generate/image?prompt={prompt}",
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headers={'Authorization': 'Bearer bowong7777'},
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files={"img_file": (
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'image.' + format.lower(), tensor_to_image_bytes(image, format),
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f'image/{format.lower()}')},
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files=files,
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timeout=150)
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job_resp.raise_for_status()
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job_resp = job_resp.json()
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if "失败" in job_resp["msg"] or "fail" in job_resp["msg"] or "error" in job_resp["msg"]:
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raise Exception("生成失败")
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job_id = job_resp["data"]
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for _ in range(0, timeout//interval, interval):
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for _ in range(0, timeout // interval, interval):
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logger.info("查询结果")
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resp = send_request("get", f"https://{endpoint}/api/mj/async/query/status?task_id={job_id}",
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headers={'Authorization': 'Bearer bowong7777'}, timeout=30)
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@ -242,7 +256,7 @@ class ModalMidJourneyGenerateImage:
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if isinstance(result_url, list):
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result_list = []
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for url in result_url:
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logger.success("img_url: "+url)
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logger.success("img_url: " + url)
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result_list.append(url_to_tensor(url).squeeze(0))
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result_list = torch.stack(result_list, dim=0)
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return (result_list,)
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@ -253,6 +267,7 @@ class ModalMidJourneyGenerateImage:
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except Exception as e:
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raise e
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class ModalMidJourneyDescribeImage:
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@classmethod
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def INPUT_TYPES(cls):
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