Upgrade to v1.0.9
This commit is contained in:
yolain
+12
-15
@@ -29,7 +29,7 @@ After installing the node package, the UI interface will be automatically switch
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### Stable Cascade
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[WorkFlow Example](https://github.com/yolain/ComfyUI-Easy-Use?tab=readme-ov-file#StableCascade) <br><br>
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[WorkFlow Example](https://github.com/yolain/ComfyUI-Easy-Use/blob/main/README.en.md#StableCascade) <br><br>
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Currently, txt2img and img2img are supported，Lora and Controlnet are comming soon!<br><br>
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Usage：<br>
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@@ -39,24 +39,21 @@ Usage：<br>
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## Changelog
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**2024-02-29**
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**v1.0.9 [2024-3-2]**
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- Fixed `easy svdLoader` error when the positive or negative is empty
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- Added `easy instantIDApply` - you need installed [ComfyUI_InstantID](https://github.com/cubiq/ComfyUI_InstantID) fisrt, Workflow[Example](https://github.com/yolain/ComfyUI-Easy-Use/blob/main/README.en.md#InstantID)
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- Fixed `easy detailerFix` not added to the list of nodes available for saving images formatting extensions
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- Fixed `easy XYInputs: PromptSR` errors are reported when replacing negative prompts
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**2024-02-28**
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- Fixed the issue that 'easy preSampling' and other similar node, latent could not be generated based on the batch index after passing in
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**2024-02-26**
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- `easy fullLoader` **positive**、**negative**、**latent** added to the output items
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- Fixed the error of SDXLClipModel in ComfyUI revision 2016[c2cb8e88] and above (the revision number was judged to be compatible with the old revision)
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- Fixed `easy detailerFix` generation error when batch size is greater than 1
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**v1.0.8(2024-02-25)**
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**v1.0.8 (f28cbf7)**
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- `easy cascadeLoader` stage_c and stage_b support the checkpoint model (Download [checkpoints](https://huggingface.co/stabilityai/stable-cascade/tree/main/comfyui_checkpoints) models)
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- `easy styleSelector` The search box is modified to be case-insensitive
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- `easy fullLoader` **positive**、**negative**、**latent** added to the output items
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- Fixed the issue that 'easy preSampling' and other similar node, latent could not be generated based on the batch index after passing in
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- Fixed `easy svdLoader` error when the positive or negative is empty
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- Fixed the error of SDXLClipModel in ComfyUI revision 2016[c2cb8e88] and above (the revision number was judged to be compatible with the old revision)
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- Fixed `easy detailerFix` generation error when batch size is greater than 1
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- Optimize the code, reduce a lot of redundant code and improve the running speed
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**v1.0.7 (2024-02-19)**
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@@ -66,7 +63,7 @@ Usage：<br>
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- Added `easy fullCascadeKSampler` - stable cascade stage-c ksampler full
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- Added `easy cascadeKSampler` - stable cascade stage-c ksampler simple
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-
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- Optimize the image to image[Example](https://github.com/yolain/ComfyUI-Easy-Use?tab=readme-ov-file#image-to-image)
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- Optimize the image to image[Example](https://github.com/yolain/ComfyUI-Easy-Use/blob/main/README.en.md#image-to-image)
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**v1.0.6**
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@@ -43,33 +43,28 @@ stage_c 与 stage_b 可以使用[checkpoints](https://huggingface.co/stabilityai
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## 更新日志
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**2024-02-29**
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- 修复 `easy svdLoader` 报错
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**v1.0.9 [2024-3-2]**
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**2024-02-28**
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- 新增 `easy instantIDApply` - 需要先安装 [ComfyUI_InstantID](https://github.com/cubiq/ComfyUI_InstantID), 工作流参考[示例](https://github.com/yolain/ComfyUI-Easy-Use?tab=readme-ov-file#InstantID)
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- 修复 `easy detailerFix` 未添加到保存图片格式化扩展名可用节点列表
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- 修复 `easy XYInputs: PromptSR` 在替换负面提示词时报错
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**v1.0.8 (f28cbf7)**
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- `easy cascadeLoader` stage_c 与 stage_b 支持checkpoint模型 (需要下载[checkpoints](https://huggingface.co/stabilityai/stable-cascade/tree/main/comfyui_checkpoints))
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- `easy styleSelector` 搜索框修改为不区分大小写匹配
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- `easy fullLoader` 增加 **positive**、**negative**、**latent** 输出项
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- 修复 SDXLClipModel 在 ComfyUI 修订版本号 2016[c2cb8e88] 及以上的报错（判断了版本号可兼容老版本）
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- 修复 `easy detailerFix` 批次大小大于1时生成出错
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- 修复`easy preSampling`等 latent传入后无法根据批次索引生成的问题
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**2024-02-27**
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- 修复 `easy svdLoader` 报错
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- 优化代码，减少了诸多冗余，提升运行速度
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- 去除中文翻译对照文本
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（翻译对照已由 [AIGODLIKE-COMFYUI-TRANSLATION](https://github.com/AIGODLIKE/AIGODLIKE-ComfyUI-Translation) 统一维护啦！
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首次下载或者版本较早的朋友请更新 AIGODLIKE-COMFYUI-TRANSLATION 和本节点包至最新版本。）
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**2024-02-26**
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- `easy fullLoader` 增加 **positive**、**negative**、**latent** 输出项
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- 修复 SDXLClipModel 在 ComfyUI 修订版本号 2016[c2cb8e88] 及以上的报错（判断了版本号可兼容老版本）
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- 修复 `easy detailerFix` 批次大小大于1时生成出错
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**v1.0.8(2024-02-25)**
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- `easy cascadeLoader` stage_c 与 stage_b 支持checkpoint模型 (需要下载[checkpoints](https://huggingface.co/stabilityai/stable-cascade/tree/main/comfyui_checkpoints))
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- `easy styleSelector` 搜索框修改为不区分大小写匹配
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- 优化代码，减少了诸多冗余，提升运行速度
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**v1.0.7**
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- 增加 `easy cascadeLoader` - stable cascade 加载器
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@@ -255,9 +250,9 @@ stage_c 与 stage_b 可以使用[checkpoints](https://huggingface.co/stabilityai
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<img src="https://raw.githubusercontent.com/yolain/yolain-comfyui-workflow/main/Workflows/Simple/image_to_image_controlnet.png">
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#### SDTurbo+高清修复+SVD
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#### InstantID
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<img src="https://raw.githubusercontent.com/yolain/yolain-comfyui-workflow/main/Workflows/Simple/sdturbo_hiresfix_svd.png">
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<img src="https://raw.githubusercontent.com/yolain/yolain-comfyui-workflow/main/Workflows/Simple/instantID.png">
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### StableCascade
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#### 文生图
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@@ -266,6 +261,7 @@ stage_c 与 stage_b 可以使用[checkpoints](https://huggingface.co/stabilityai
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#### 图生图
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<img src="https://raw.githubusercontent.com/yolain/yolain-comfyui-workflow/main/Workflows/StableCascade/image_to_image.png">
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## Credits
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[ComfyUI](https://github.com/comfyanonymous/ComfyUI) - 功能强大且模块化的Stable Diffusion GUI
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+1
-1
@@ -74,4 +74,4 @@ WEB_DIRECTORY = "./web"
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__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS', "WEB_DIRECTORY"]
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print('\033[34mComfy-Easy-Use (v1.0.8): \033[92mLoaded\033[0m')
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print('\033[34mComfy-Easy-Use (v1.0.9): \033[92mLoaded\033[0m')
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+91
-22
@@ -1441,6 +1441,7 @@ class controlnetSimple:
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"loader_settings": pipe["loader_settings"]
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}
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del pipe
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return (new_pipe, positive, negative)
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# controlnetADV
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@@ -1535,6 +1536,8 @@ class LLLiteLoader:
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return (model_lllite,)
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#---------------------------------------------------------------测试 开始----------------------------------------------------------------------#
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# FooocusInpaint (Testing)
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from .fooocus import InpaintHead, InpaintWorker
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inpaint_head_model = None
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@@ -1567,6 +1570,90 @@ class fooocusInpaintLoader:
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return ((inpaint_head_model, inpaint_lora),)
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#Apply InstantID
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class instantIDApply:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required":{
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"pipe": ("PIPE_LINE",),
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"image": ("IMAGE",),
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"instantid_file": (folder_paths.get_filename_list("instantid"),),
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"insightface": (["CPU", "CUDA", "ROCM"],),
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"control_net_name": (folder_paths.get_filename_list("controlnet"),),
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"cn_strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"cn_soft_weights": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001},),
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"weight": ("FLOAT", {"default": .8, "min": 0.0, "max": 5.0, "step": 0.01, }),
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"start_at": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001, }),
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"end_at": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001, }),
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"noise": ("FLOAT", {"default": 0.35, "min": 0.0, "max": 1.0, "step": 0.05, }),
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},
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"optional": {
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"image_kps": ("IMAGE",),
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"mask": ("MASK",),
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"control_net": ("CONTROL_NET",),
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},
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"hidden": {
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"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO", "my_unique_id": "UNIQUE_ID"
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},
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}
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RETURN_TYPES = ("PIPE_LINE", "MODEL", "CONDITIONING", "CONDITIONING")
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RETURN_NAMES = ("pipe", "model", "positive", "negative")
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OUTPUT_NODE = True
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FUNCTION = "apply"
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CATEGORY = "EasyUse/__for_testing"
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def error(self):
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raise Exception(f"[ERROR] To use instantIDApply, you need to install 'ComfyUI_InstantID'")
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def apply(self, pipe, image, instantid_file, insightface, control_net_name, cn_strength, cn_soft_weights, weight, start_at, end_at, noise, image_kps=None, mask=None, control_net=None, prompt=None, extra_pnginfo=None, my_unique_id=None):
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instantid_model, insightface_model, face_embeds = None, None, None
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model = pipe['model']
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positive = pipe['positive']
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negative = pipe['negative']
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# Load InstantID
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if "InstantIDModelLoader" in ALL_NODE_CLASS_MAPPINGS:
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load_instant_cls = ALL_NODE_CLASS_MAPPINGS["InstantIDModelLoader"]
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instantid_model, = load_instant_cls().load_model(instantid_file)
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else:
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self.error()
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if "InstantIDFaceAnalysis" in ALL_NODE_CLASS_MAPPINGS:
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load_insightface_cls = ALL_NODE_CLASS_MAPPINGS["InstantIDFaceAnalysis"]
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insightface_model, = load_insightface_cls().load_insight_face(insightface)
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else:
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self.error()
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# Apply InstantID
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if "ApplyInstantID" in ALL_NODE_CLASS_MAPPINGS:
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instantid_apply = ALL_NODE_CLASS_MAPPINGS['ApplyInstantID']
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control_net = easyControlnet().load_controlnet(control_net_name, control_net, cn_soft_weights)
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model, positive, negative = instantid_apply().apply_instantid(instantid_model, insightface_model, control_net, image, model, positive, negative, start_at, end_at, weight=weight, ip_weight=None, cn_strength=cn_strength, noise=noise, image_kps=image_kps, mask=None)
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else:
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self.error()
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new_pipe = {
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"model": model,
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"positive": positive,
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"negative": negative,
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"vae": pipe['vae'],
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"clip": pipe['clip'],
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"samples": pipe["samples"],
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"images": pipe["images"],
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"seed": 0,
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"loader_settings": pipe["loader_settings"]
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}
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del pipe
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return (new_pipe, model, positive, negative)
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#---------------------------------------------------------------预采样 开始----------------------------------------------------------------------#
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# 预采样设置（基础）
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@@ -3373,26 +3460,6 @@ class detailerFix:
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return {"ui": {"images": results}, "result": (new_pipe, result_img, result_cropped_enhanced, result_cropped_enhanced_alpha, result_mask, result_cnet_images )}
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def add_folder_path_and_extensions(folder_name, full_folder_paths, extensions):
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for full_folder_path in full_folder_paths:
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folder_paths.add_model_folder_path(folder_name, full_folder_path)
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if folder_name in folder_paths.folder_names_and_paths:
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current_paths, current_extensions = folder_paths.folder_names_and_paths[folder_name]
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updated_extensions = current_extensions | extensions
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folder_paths.folder_names_and_paths[folder_name] = (current_paths, updated_extensions)
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else:
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folder_paths.folder_names_and_paths[folder_name] = (full_folder_paths, extensions)
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model_path = folder_paths.models_dir
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add_folder_path_and_extensions("ultralytics_bbox", [os.path.join(model_path, "ultralytics", "bbox")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("ultralytics_segm", [os.path.join(model_path, "ultralytics", "segm")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("ultralytics", [os.path.join(model_path, "ultralytics")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("mmdets_bbox", [os.path.join(model_path, "mmdets", "bbox")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("mmdets_segm", [os.path.join(model_path, "mmdets", "segm")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("mmdets", [os.path.join(model_path, "mmdets")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("sams", [os.path.join(model_path, "sams")], folder_paths.supported_pt_extensions)
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add_folder_path_and_extensions("onnx", [os.path.join(model_path, "onnx")], {'.onnx'})
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class ultralyticsDetectorForDetailerFix:
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@classmethod
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def INPUT_TYPES(s):
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@@ -4697,7 +4764,8 @@ NODE_CLASS_MAPPINGS = {
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# "easy imageRemoveBG": imageREMBG,
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"dynamicThresholdingFull": dynamicThresholdingFull,
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# __for_testing 测试
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"easy fooocusInpaintLoader": fooocusInpaintLoader
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"easy fooocusInpaintLoader": fooocusInpaintLoader,
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"easy instantIDApply": instantIDApply,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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# prompt 提示词
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@@ -4773,5 +4841,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"easy imageRemoveBG": "ImageRemoveBG",
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"dynamicThresholdingFull": "DynamicThresholdingFull",
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# __for_testing 测试
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"easy fooocusInpaintLoader": "Load Fooocus Inpaint"
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"easy fooocusInpaintLoader": "Load Fooocus Inpaint",
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"easy instantIDApply": "Easy Apply InstantID"
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}
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+56
-34
@@ -1,12 +1,13 @@
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import folder_paths
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import comfy.controlnet
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import comfy.model_management
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from nodes import NODE_CLASS_MAPPINGS
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class easyControlnet:
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def __init__(self):
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pass
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def apply(self, control_net_name, image, positive, negative, strength, start_percent=0, end_percent=1, control_net=None, scale_soft_weights=1):
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def load_controlnet(self, control_net_name, control_net, scale_soft_weights):
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if control_net is None:
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if scale_soft_weights < 1:
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if "ScaledSoftControlNetWeights" in NODE_CLASS_MAPPINGS:
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@@ -19,43 +20,64 @@ class easyControlnet:
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else:
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controlnet_path = folder_paths.get_full_path("controlnet", control_net_name)
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control_net = comfy.controlnet.load_controlnet(controlnet_path)
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return control_net
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def apply(self, control_net_name, image, positive, negative, strength, start_percent=0, end_percent=1, control_net=None, scale_soft_weights=1, mask=None):
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if strength == 0:
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return (positive, negative)
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control_net = self.load_controlnet(control_net_name, control_net, scale_soft_weights)
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if mask is not None:
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mask = mask.to(self.device)
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if mask is not None and len(mask.shape) < 3:
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mask = mask.unsqueeze(0)
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control_hint = image.movedim(-1, 1)
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if strength != 0:
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if negative is None:
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p = []
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for t in positive:
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n = [t[0], t[1].copy()]
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c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent))
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if 'control' in t[1]:
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c_net.set_previous_controlnet(t[1]['control'])
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n[1]['control'] = c_net
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n[1]['control_apply_to_uncond'] = True
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p.append(n)
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positive = p
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else:
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cnets = {}
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out = []
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for conditioning in [positive, negative]:
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c = []
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for t in conditioning:
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d = t[1].copy()
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is_cond = True
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if negative is None:
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p = []
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for t in positive:
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n = [t[0], t[1].copy()]
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c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent))
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if 'control' in t[1]:
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c_net.set_previous_controlnet(t[1]['control'])
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n[1]['control'] = c_net
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n[1]['control_apply_to_uncond'] = True
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if mask is not None:
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n[1]['mask'] = mask
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n[1]['set_area_to_bounds'] = False
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p.append(n)
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positive = p
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else:
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cnets = {}
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out = []
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for conditioning in [positive, negative]:
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c = []
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for t in conditioning:
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d = t[1].copy()
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prev_cnet = d.get('control', None)
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if prev_cnet in cnets:
|
||||
c_net = cnets[prev_cnet]
|
||||
else:
|
||||
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent))
|
||||
c_net.set_previous_controlnet(prev_cnet)
|
||||
cnets[prev_cnet] = c_net
|
||||
prev_cnet = d.get('control', None)
|
||||
if prev_cnet in cnets:
|
||||
c_net = cnets[prev_cnet]
|
||||
else:
|
||||
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent))
|
||||
c_net.set_previous_controlnet(prev_cnet)
|
||||
cnets[prev_cnet] = c_net
|
||||
|
||||
d['control'] = c_net
|
||||
d['control_apply_to_uncond'] = False
|
||||
n = [t[0], d]
|
||||
c.append(n)
|
||||
out.append(c)
|
||||
positive = out[0]
|
||||
negative = out[1]
|
||||
d['control'] = c_net
|
||||
d['control_apply_to_uncond'] = False
|
||||
|
||||
if mask is not None:
|
||||
d['mask'] = mask
|
||||
d['set_area_to_bounds'] = False
|
||||
|
||||
n = [t[0], d]
|
||||
c.append(n)
|
||||
out.append(c)
|
||||
positive = out[0]
|
||||
negative = out[1]
|
||||
|
||||
return (positive, negative)
|
||||
+1
-1
@@ -367,7 +367,7 @@ class easyXYPlot():
|
||||
w_max=1.0,
|
||||
apply_to_pooled="enable", a1111_prompt_style=a1111_prompt_style, steps=steps)
|
||||
if "negative_cond" in plot_image_vars:
|
||||
positive = positive + plot_image_vars["negative_cond"]
|
||||
negative = negative + plot_image_vars["negative_cond"]
|
||||
|
||||
# ControlNet
|
||||
if "ControlNet" in self.x_type or "ControlNet" in self.y_type:
|
||||
|
||||
@@ -4,7 +4,7 @@ import { applyTextReplacements } from "/scripts/utils.js";
|
||||
app.registerExtension({
|
||||
name: "Comfy.Easy.SaveImageExtraOutput",
|
||||
async beforeRegisterNodeDef(nodeType, nodeData, app) {
|
||||
if (["easy imageSave", "easy fullkSampler", "easy kSampler", "easy kSamplerTiled","easy kSamplerInpainting", "easy kSamplerDownscaleUnet", "easy kSamplerSDTurbo"].includes(nodeData.name)) {
|
||||
if (["easy imageSave", "easy fullkSampler", "easy kSampler", "easy kSamplerTiled","easy kSamplerInpainting", "easy kSamplerDownscaleUnet", "easy kSamplerSDTurbo","easy detailerFix"].includes(nodeData.name)) {
|
||||
const onNodeCreated = nodeType.prototype.onNodeCreated;
|
||||
// When the SaveImage node is created we want to override the serialization of the output name widget to run our S&R
|
||||
nodeType.prototype.onNodeCreated = function () {
|
||||
|
||||
Reference in New Issue
Block a user