Detection / Image to Prompt — v2.2 (Nodes 2.0)
nodes 2.0 layout, requires Eclipse 4.1.30 (fixes some layout issues)
Perfil de ejecución
- Acceso
- Flujo externo
- Estado
- Verificado
- Versión
- detectionImageTo_v22Nodes20.json
- Fuente
- Civitai
- Actualizado
- 18 oct 2026
What you need
- Model files
- 0 GiB
Remaining hardware or download-size estimates are not available yet.
Requisitos
Paquetes de nodos
1- Encontrado
Paquete de nodos · Registry
Comentario generado por IA
Explicación generada por IA basada en los detalles de la fuente y la configuración. Las sugerencias están claramente identificadas.
Propósito
This workflow is for analyzing images and creating text: it accepts a single image, a folder of images, video frames, or text prompts and themes, and can produce captions, tags, object detections and masks, timeline prompts, prompt variations, lyrics, and chat responses.
Flujo
Load one image directly or choose a folder or video; for folder or video input, Image Selector lets you choose files or frames before the active image is routed to Detection, Image to Prompt, and Timeline Prompts.
Named Set/Get channels share the image with those groups, while Prompt Variations, Song Lyrics, and Direct Chat use text prompts, themes, or selected system prompts.
Entradas y salidas
Image to Prompt displays image descriptions and comma-separated tags in Show Text; Detection shows textual results, isolated regions, and binary masks.
Timeline Prompts produces time-coded descriptions for video models such as Wan2.1 and LTX-Video; Prompt Variations expands a seed prompt into three variations.
Song Lyrics creates lyrics or poetry from user-supplied themes, and Direct Chat displays responses from the selected language or vision-language model.
Configuración inicial
Eclipse 4.1.30 is listed as a requirement for the Nodes 2.0 layout.
Dependencias
The workflow requires the ComfyUI_Eclipse node pack.
Configuración
For batch image tagging, switch to Folder Mode and enter a folder path; bypass Image Selector to process files sequentially, or leave it active to choose files when prompted.
Sugerencia · sin verificar
Choose a vision-language model in Smart LM Loader for image descriptions, and enter a query such as “face, hair” in detection_prompt for object detection.
Sugerencia · sin verificar
For Docker-based backends, configure Hugging Face, GGUF, or Ollama credentials in config.json; the guide places local GGUF and Transformers models in models/llms/ or models/text_encoders/.
Sugerencia · sin verificar
Precauciones
The two parallel Image to Prompt loaders are a demonstration; captioning and tag generation can instead run sequentially in one loader.
No license is specified for this workflow.
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Fuentes
1 fuente
Fuentes
1 fuenteExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractosSource context: 356 downloads · Type Workflows · Base model Other
Source context: 195 downloads · Type Workflows · Base model Other
Source context: 151 downloads · Type Workflows · Base model Other
