pixelle-mcp-Image-generation

{ "3": { "inputs": { "seed": 121110126638218, "steps": 10, "cfg": 1, "sampler_name": "uni_pc", "scheduler": "normal", "denoise": 1, "model": [ "48", 0 ], "positive": [ "6", 0 ], "negative": [ "7", 0 ], "latent_image": [ "40", 0 ] }, "class_type": "KSampler", "_meta": { "title": "KSampler" } }, "6": { "inputs": { "text": [ "49", 0 ], "clip": [ "38", 0 ] }, "class_type": "CLIPTextEncode", "_meta": { "title": "CLIP Text Encode (Positive Prompt)" } }, "7": { "inputs": { "text": "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走", "clip": [ "38", 0 ] }, "class_type": "CLIPTextEncode", "_meta": { "title": "CLIP Text Encode (Negative Prompt)" } }, "8": { "inputs": { "samples": [ "3", 0 ], "vae": [ "39", 0 ] }, "class_type": "VAEDecode", "_meta": { "title": "VAE Decode" } }, "30": { "inputs": { "frame_rate": 16, "loop_count": 0, "filename_prefix": "Video", "format": "video/h264-mp4", "pix_fmt": "yuv420p", "crf": 19, "save_metadata": true, "trim_to_audio": false, "pingpong": false, "save_output": true, "images": [ "8", 0 ] }, "class_type": "VHS_VideoCombine", "_meta": { "title": "Video Combine 🎥🅥🅗🅢" } }, "37": { "inputs": { "unet_name": "WanT2V_MasterModel.safetensors", "weight_dtype": "default" }, "class_type": "UNETLoader", "_meta": { "title": "Load Diffusion Model" } }, "38": { "inputs": { "clip_name": "umt5_xxl_fp8_e4m3fn_scaled.safetensors", "type": "wan", "device": "default" }, "class_type": "CLIPLoader", "_meta": { "title": "Load CLIP" } }, "39": { "inputs": { "vae_name": "wan_2.1_vae.safetensors" }, "class_type": "VAELoader", "_meta": { "title": "Load VAE" } }, "40": { "inputs": { "width": [ "50", 0 ], "height": [ "51", 0 ], "length": 81, "batch_size": 1 }, "class_type": "EmptyHunyuanLatentVideo", "_meta": { "title": "EmptyHunyuanLatentVideo" } }, "48": { "inputs": { "shift": 1.0000000000000002, "model": [ "37", 0 ] }, "class_type": "ModelSamplingSD3", "_meta": { "title": "Shift" } }, "49": { "inputs": { "value": "" }, "class_type": "PrimitiveStringMultiline", "_meta": { "title": "$prompt.value!:The prompt to generate the video, must be english" } }, "50": { "inputs": { "value": 512 }, "class_type": "easy int", "_meta": { "title": "$width.value:The width of the video" } }, "51": { "inputs": { "value": 288 }, "class_type": "easy int", "_meta": { "title": "$height.value:The height of the video" } }, "53": { "inputs": { "value": "Generate high-quality videos from text prompts using local WAN2.1 FusionX model.\n\n Creates completely new videos with exceptional detail, style diversity, and prompt adherence.\n The model excels at photorealistic scenes, artistic styles, and complex compositions.\n\n About parameters:\n - default video size: 512x288 (recommended), use 1024x576 only when user explicitly requests high quality.\n\n Prompt writing tips for best results:\n 1. Length and Detail: Keep prompts around 80–100 words long, offering rich descriptions to support layered and vivid video output.\n 2. Camera Movement: Clearly describe how the camera moves, such as tracking shots, pan left/right, dolly in/out, or tilt up/down. Avoid fast movements like whip pans or crash zooms, which Wan 2.1 struggles to render properly.\n 3. Lighting and Shadows: Define lighting styles and sources—use terms like soft light, hard light, backlight, and volumetric lighting to shape the scene's atmosphere and depth.\n 4. Atmosphere and Mood: Each prompt should convey a clear emotional tone such as somber, mysterious, dreamlike, or euphoric, enhancing the storytelling power of the visuals.\n 5. Composition and Perspective: Use cinematic framing techniques like close-ups, wide shots, low angles, or high angles to emphasize focus and perspective in the scene.\n 6. Visual Style: Incorporate stylistic cues such as cinematic, vintage film look, shallow depth of field, or motion blur to give the video a unique, cohesive aesthetic.\n 7. Time and Environmental Context: Include relevant context such as time of day (e.g., dawn, dusk), weather conditions (e.g., rain, fog), and setting (e.g., forest, city, coast) to enhance realism and immersion." }, "class_type": "PrimitiveStringMultiline", "_meta": { "title": "MCP" } } }