在本地使用时,我们将暴露端口 3000(api 接口)和端口 8188(让我们可以在本地访问 web ui)。 测试步骤 在浏览器中访问http://localhost:8188。 点击"Queue Prompt" 生成图像。 通过设置菜单启用开发者模式选项。你可以在菜单中看到一个新选项 "Save (API Format) 点击"Save(API Format)" 按钮并保存。你会...
你可以在菜单中看到一个新选项 "Save (API Format) 点击"Save(API Format)" 按钮并保存。你会得到一个名为workflow_api.json的文件,其中包含 ComfyUI 再次运行该提示所需的所有内容。 注意:你可能注意到这种提示格式不太直观,但它确实包含了 ComfyUI 使用的节点和连接。根据经验,ComfyUI web ui 是设计提示的...
大家搭好工作流,可以到处json 便于分享和协作。而我们开发也会用到,只不过保存时是点击有后缀的 save (api format)的按钮,这样我们就可以拿到让comfyui去处理的任务说明 api需要开启dev 模式 这里用最基础的生图工作流给大家演示 在节点中通常包含多个参数,如果其中有些参数的值需要从其他节点获取,则这些参数的结构...
Images can be saved to the output directory by running the workflow on the ComfyUI frontend. When I click 'Save (API Format)' and execute the API format, only temporary images are saved; the generated images are not saved to the output directory. See history below, { "prompt": [ 2, ...
Click Save (API Format) option in your menu: Save the file as workflow_api.json. Convert JSON to Python We’ll use the ComfyUI to Python Extension to convert the JSON from the previous step to Python code. This tool requires ComfyUI to be installed on the host machine, so we’ll use...
Save workflow with "Save (API Format)" Drop/Load created file in TouchDesigner project (TextDAT). Connect DAT to TDComfyUI input (InDAT) Set parameters on Workflow page and run "Generate" on Settings page. Image send/recieve: Send to ComfyUI - "Load Image (Base64)" node should be use...
.format(GIF_LOCATION)) if __name__ == "__main__": # 设置工作目录和项目相关的路径 WORKING_DIR = 'output' SageMaker_ComfyUI = WORKING_DIR workflowfile = '/mnt/d/code/aigc/workflow_api.json' COMFYUI_ENDPOINT = 'localhost:8188' server_address = COMFYUI_ENDPOINT client_id = str(uuid...
Open ComfyUI, load or edit your workflow, then save it in API format. edit workflow to add placeholders. Placeholders must be between curly braces. Paths or other escape charachters should be doubled. Ex: "ckpt_name":"Stable-diffusion\\SdXl\\sd_xl_turbo_1.0_fp16.safetensors" ...
The most powerful and modular stable diffusion GUI and backend. This ui will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. For some workflow examples and see what ComfyUI can do you can check out: ...
request = urllib.request.Request("http://{}/upload/image".format(server_address), data=data, headers=headers) with urllib.request.urlopen(request) as response: return response.read() API 工作流程 要通过 API 使用 ComfyUI 工作流,请使用“保存(API 格式)”保存工作流。如果没有此按钮,则必须通过...