工作流名稱：多頭部視圖角色表
【工作流介紹】
當你打開這個工作流時，首先需要上傳 3 張圖像。位於左邊的第一張圖像是用於面部遷移的肖像，左邊的第二張圖像則是作為提示詞參考的圖像，而第三張圖像可以是骨骼圖像或者多視角圖像，並且需要用 DWopenpose 對其進行提取。接下來，透過 PuLID 來進行面部遷移操作，利用 controlnet 的骨骼功能進行控制，再結合 Flux 模型進行圖像生成。目前，工作流的內置參數已經設置完成，各位可以趕快體驗啦！
【使用場景】
就按照這樣的工作流程而言，當你上傳哈利波特圖作為自身風格的提示詞參考之後，接著再上傳一張屬於你自己的肖像，那麼便能夠獲取同款多視圖的相似造型效果。這無疑給你帶來了極大的驚喜。
【關鍵節點】
PuLID
【模型版本】
FLUX
模型名稱:fux1-dev-Q8 0.gguf
【LoRA模型】
無
【ControlNet應用】
FLUX.1-dev-ControINet-Union-Pro-Shakker-Labs.safetensors
DW姿態預處理器
開始時間：0
結束時間：0.7
強度：0.65
【自定義採樣器（高級）】
採樣方法：deis
調度器：beta
降噪：1
多頭部視角角色表
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下載
2
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工作流名稱：多頭部視圖角色表
【工作流介紹】
當你打開這個工作流時，首先需要上傳 3 張圖像。位於左邊的第一張圖像是用於面部遷移的肖像，左邊的第二張圖像則是作為提示詞參考的圖像，而第三張圖像可以是骨骼圖像或者多視角圖像，並且需要用 DWopenpose 對其進行提取。接下來，透過 PuLID 來進行面部遷移操作，利用 controlnet 的骨骼功能進行控制，再結合 Flux 模型進行圖像生成。目前，工作流的內置參數已經設置完成，各位可以趕快體驗啦！
【使用場景】
就按照這樣的工作流程而言，當你上傳哈利波特圖作為自身風格的提示詞參考之後，接著再上傳一張屬於你自己的肖像，那麼便能夠獲取同款多視圖的相似造型效果。這無疑給你帶來了極大的驚喜。
【關鍵節點】
PuLID
【模型版本】
FLUX
模型名稱:fux1-dev-Q8 0.gguf
【LoRA模型】
無
【ControlNet應用】
FLUX.1-dev-ControINet-Union-Pro-Shakker-Labs.safetensors
DW姿態預處理器
開始時間：0
結束時間：0.7
強度：0.65
【自定義採樣器（高級）】
採樣方法：deis
調度器：beta
降噪：1
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Primitive Nodes (8) Custom Nodes (21)工作流名稱：多頭部視圖角色表
【工作流介紹】
當你打開這個工作流時，首先需要上傳 3 張圖像。位於左邊的第一張圖像是用於面部遷移的肖像，左邊的第二張圖像則是作為提示詞參考的圖像，而第三張圖像可以是骨骼圖像或者多視角圖像，並且需要用 DWopenpose 對其進行提取。接下來，透過 PuLID 來進行面部遷移操作，利用 controlnet 的骨骼功能進行控制，再結合 Flux 模型進行圖像生成。目前，工作流的內置參數已經設置完成，各位可以趕快體驗啦！
【使用場景】
就按照這樣的工作流程而言，當你上傳哈利波特圖作為自身風格的提示詞參考之後，接著再上傳一張屬於你自己的肖像，那麼便能夠獲取同款多視圖的相似造型效果。這無疑給你帶來了極大的驚喜。
【關鍵節點】
PuLID
【模型版本】
FLUX
模型名稱:fux1-dev-Q8 0.gguf
【LoRA模型】
無
【ControlNet應用】
FLUX.1-dev-ControINet-Union-Pro-Shakker-Labs.safetensors
DW姿態預處理器
開始時間：0
結束時間：0.7
強度：0.65
【自定義採樣器（高級）】
採樣方法：deis
調度器：beta
降噪：1
Primitive Nodes (8) Custom Nodes (21)