s-henmind/xz-depth-pose | API reference

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Run s-henmind/xz-depth-pose with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field	Type	Default value	Description
prompt	string		Prompt for generated image
conditioning_scale	number	0.5 Max: 1	ControlNet strength, depth works best at 0.2, canny works best at 0.4. Recommended range is 0.3-0.8
image	string		The image to restyle
strength	number	0.8 Max: 1	Img2Img strength
guidance_scale	number	3.5 Max: 30	Guidance scale
enable_hyper_flux_8_step	boolean	False	Whether to use Hyper-FLUX.1-dev-8steps or not. If False, make sure to increase your number of inference steps
num_inference_steps	integer	8 Min: 1 Max: 38	Number of inference steps
seed	integer		Random seed. Set for reproducible generation
output_format	None	jpg	Format of the output images
output_quality	integer	100 Max: 100	Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
lora_weights	string		Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux
lora_scale	number	0.8 Max: 2	Scale for the LoRA weights
id_image	string		id image
id_image_1	string		id image
id_image_2	string		id image
id_weight	number	Max: 1	id weight
num_outputs	integer	1 Min: 1 Max: 4	Number of images to output.
dilate_pixels	integer	10 Max: 30	dilate pixels
repaint_steps	integer	4 Max: 10	Number of repaint steps

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt"
  ],
  "properties": {
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 7,
      "description": "Random seed. Set for reproducible generation"
    },
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 2,
      "description": "The image to restyle"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 0,
      "description": "Prompt for generated image"
    },
    "id_image": {
      "type": "string",
      "title": "Id Image",
      "format": "uri",
      "x-order": 12,
      "description": "id image"
    },
    "strength": {
      "type": "number",
      "title": "Strength",
      "default": 0.8,
      "maximum": 1,
      "minimum": 0,
      "x-order": 3,
      "description": "Img2Img strength"
    },
    "id_weight": {
      "type": "number",
      "title": "Id Weight",
      "maximum": 1,
      "minimum": 0,
      "x-order": 15,
      "description": "id weight"
    },
    "id_image_1": {
      "type": "string",
      "title": "Id Image 1",
      "format": "uri",
      "x-order": 13,
      "description": "id image"
    },
    "id_image_2": {
      "type": "string",
      "title": "Id Image 2",
      "format": "uri",
      "x-order": 14,
      "description": "id image"
    },
    "lora_scale": {
      "type": "number",
      "title": "Lora Scale",
      "default": 0.8,
      "maximum": 2,
      "minimum": 0,
      "x-order": 11,
      "description": "Scale for the LoRA weights"
    },
    "num_outputs": {
      "type": "integer",
      "title": "Num Outputs",
      "default": 1,
      "maximum": 4,
      "minimum": 1,
      "x-order": 16,
      "description": "Number of images to output."
    },
    "lora_weights": {
      "type": "string",
      "title": "Lora Weights",
      "x-order": 10,
      "description": "Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux"
    },
    "dilate_pixels": {
      "type": "integer",
      "title": "Dilate Pixels",
      "default": 10,
      "maximum": 30,
      "minimum": 0,
      "x-order": 17,
      "description": "dilate pixels"
    },
    "output_format": {
      "enum": [
        "webp",
        "jpg",
        "png"
      ],
      "type": "string",
      "title": "output_format",
      "description": "Format of the output images",
      "default": "jpg",
      "x-order": 8
    },
    "repaint_steps": {
      "type": "integer",
      "title": "Repaint Steps",
      "default": 4,
      "maximum": 10,
      "minimum": 0,
      "x-order": 18,
      "description": "Number of repaint steps"
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 3.5,
      "maximum": 30,
      "minimum": 0,
      "x-order": 4,
      "description": "Guidance scale"
    },
    "output_quality": {
      "type": "integer",
      "title": "Output Quality",
      "default": 100,
      "maximum": 100,
      "minimum": 0,
      "x-order": 9,
      "description": "Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs"
    },
    "conditioning_scale": {
      "type": "number",
      "title": "Conditioning Scale",
      "default": 0.5,
      "maximum": 1,
      "minimum": 0,
      "x-order": 1,
      "description": "ControlNet strength, depth works best at 0.2, canny works best at 0.4. Recommended range is 0.3-0.8"
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 8,
      "maximum": 38,
      "minimum": 1,
      "x-order": 6,
      "description": "Number of inference steps"
    },
    "enable_hyper_flux_8_step": {
      "type": "boolean",
      "title": "Enable Hyper Flux 8 Step",
      "default": false,
      "x-order": 5,
      "description": "Whether to use Hyper-FLUX.1-dev-8steps or not. If False, make sure to increase your number of inference steps"
    }
  }
}

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema

{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}