pixelle-mcp-Image-generation

{ "6": { "inputs": { "image": "06.JPG" }, "class_type": "LoadImage", "_meta": { "title": "$image.image!:The image to analyze, must be a url" } }, "10": { "inputs": { "model": "microsoft/Florence-2-large", "precision": "fp16", "attention": "sdpa" }, "class_type": "DownloadAndLoadFlorence2Model", "_meta": { "title": "DownloadAndLoadFlorence2Model" } }, "11": { "inputs": { "text_input": "", "task": "more_detailed_caption", "fill_mask": true, "keep_model_loaded": false, "max_new_tokens": 1024, "num_beams": 3, "do_sample": true, "output_mask_select": "", "seed": 1098631327477633, "image": [ "6", 0 ], "florence2_model": [ "10", 0 ] }, "class_type": "Florence2Run", "_meta": { "title": "Florence2Run" } }, "18": { "inputs": { "anything": [ "11", 2 ] }, "class_type": "easy showAnything", "_meta": { "title": "Show Any" } }, "20": { "inputs": { "value": "Generate high-quality text descriptions from images using local Florence model.\n \n Main use cases:\n 1. **Reverse image prompt generation**:\n - When users upload an image and want to get prompts for AI art generation\n - Analyzes visual elements, style, composition, etc. to generate prompts for Stable Diffusion, DALL-E, and other models\n - In this case, return the tool's raw output directly to users without any modification or summary\n - Users can directly use these prompts for image generation\n 2. **Image content understanding**:\n - When users ask about specific content, objects, scenes, people, etc. in the image\n - Need to understand the semantic content of the image and answer users' specific questions\n - In this case, combine tool output with conversation context to give users contextually appropriate natural responses\n - Don't return raw output directly, but provide targeted replies based on understanding results" }, "class_type": "PrimitiveStringMultiline", "_meta": { "title": "MCP" } } }