s-henmind/redraw | API reference

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Run s-henmind/redraw 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 Max: 1	ControlNet strength, depth works best at 0.2, canny works best at 0.4. Recommended range is 0.3-0.8
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: 28	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: 1	Scale for the LoRA weights
image	string		id image
num_outputs	integer	1 Min: 1 Max: 4	Number of images to output.
style	string		style

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt"
  ],
  "properties": {
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 6,
      "description": "Random seed. Set for reproducible generation"
    },
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 11,
      "description": "id image"
    },
    "style": {
      "type": "string",
      "title": "Style",
      "x-order": 13,
      "description": "style"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 0,
      "description": "Prompt for generated image"
    },
    "strength": {
      "type": "number",
      "title": "Strength",
      "default": 0.8,
      "maximum": 1,
      "minimum": 0,
      "x-order": 2,
      "description": "Img2Img strength"
    },
    "lora_scale": {
      "type": "number",
      "title": "Lora Scale",
      "default": 0.8,
      "maximum": 1,
      "minimum": 0,
      "x-order": 10,
      "description": "Scale for the LoRA weights"
    },
    "num_outputs": {
      "type": "integer",
      "title": "Num Outputs",
      "default": 1,
      "maximum": 4,
      "minimum": 1,
      "x-order": 12,
      "description": "Number of images to output."
    },
    "lora_weights": {
      "type": "string",
      "title": "Lora Weights",
      "x-order": 9,
      "description": "Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux"
    },
    "output_format": {
      "enum": [
        "webp",
        "jpg",
        "png"
      ],
      "type": "string",
      "title": "output_format",
      "description": "Format of the output images",
      "default": "jpg",
      "x-order": 7
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 3.5,
      "maximum": 30,
      "minimum": 0,
      "x-order": 3,
      "description": "Guidance scale"
    },
    "output_quality": {
      "type": "integer",
      "title": "Output Quality",
      "default": 100,
      "maximum": 100,
      "minimum": 0,
      "x-order": 8,
      "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,
      "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": 28,
      "minimum": 1,
      "x-order": 5,
      "description": "Number of inference steps"
    },
    "enable_hyper_flux_8_step": {
      "type": "boolean",
      "title": "Enable Hyper Flux 8 Step",
      "default": false,
      "x-order": 4,
      "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"
}