SDXL FaceID - Daydream

These are the parameters available when using the SDXL Turbo FaceID model.

Available Controlet for only SDXL Turbo FaceID

SDXL Models (stabilityai/sdxl-turbo):

xinsir/controlnet-depth-sdxl-1.0: High-resolution depth guidance for SDXL models
xinsir/controlnet-canny-sdxl-1.0: SDXL-optimized canny edge detection
xinsir/controlnet-tile-sdxl-1.0: Tile-based control for SDXL texture generation

Available Parameters for only SDXL Turbo FaceID

Parameters are also loaded with these values as default when creating a new stream on this specific pipeline.

{
  "params": {
    "seed": 789,
    "delta": 0.7,
    "width": 512,
    "height": 512,
    "prompt": "mona lisa, face-focused webcam portrait blooming into stained-glass prisms and aurora ribbons, retro studio glow, friendly cardigan vibes, dreamlike, cinematic, ultra-detailed",
    "model_id": "stabilityai/sdxl-turbo",
    "lora_dict": null,
    "ip_adapter": {
      "type": "faceid",
      "scale": 1,
      "enabled": true
    },
    "controlnets": [
      {
        "enabled": true,
        "model_id": "xinsir/controlnet-depth-sdxl-1.0",
        "preprocessor": "depth_tensorrt",
        "conditioning_scale": 0.4,
        "preprocessor_params": {},
        "control_guidance_end": 1,
        "control_guidance_start": 0
      },
      {
        "enabled": true,
        "model_id": "xinsir/controlnet-canny-sdxl-1.0",
        "preprocessor": "canny",
        "conditioning_scale": 0.1,
        "preprocessor_params": {},
        "control_guidance_end": 1,
        "control_guidance_start": 0
      },
      {
        "enabled": true,
        "model_id": "xinsir/controlnet-tile-sdxl-1.0",
        "preprocessor": "feedback",
        "conditioning_scale": 0.1,
        "preprocessor_params": {},
        "control_guidance_end": 1,
        "control_guidance_start": 0
      }
    ],
    "acceleration": "tensorrt",
    "do_add_noise": true,
    "t_index_list": [36],
    "use_lcm_lora": true,
    "guidance_scale": 1,
    "negative_prompt": "blurry, low quality, flat, 2d",
    "num_inference_steps": 50,
    "use_denoising_batch": true,
    "normalize_seed_weights": true,
    "normalize_prompt_weights": true,
    "seed_interpolation_method": "linear",
    "ip_adapter_style_image_url": "https://ipfs.livepeer.com/ipfs/bafkreifyvsoa6pbt5r5ahedl6ann4nsp7m2vezkjuwn7uvxuqbie2un4wi",
    "enable_similar_image_filter": false,
    "prompt_interpolation_method": "slerp",
    "similar_image_filter_threshold": 0.98,
    "similar_image_filter_max_skip_frame": 10
  }
}

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