raoumer/srrescycgan – API reference

raoumer / srrescycgan

Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution

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131 runs
GitHub
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Run raoumer/srrescycgan 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
image	string		Input image to be upscaled
variant	string	jpeg-compression	Model variant (options: jpeg-compression, real-image-corruptions, sensor-noise, unknown-compressions)
no_chop	boolean	False	Don't chop the image (uses more memory)

{
  "type": "object",
  "properties": {
    "image": {
      "type": "string",
      "format": "uri",
      "x-order": 0,
      "description": "Input image to be upscaled"
    },
    "no_chop": {
      "type": "boolean",
      "default": false,
      "x-order": 2,
      "description": "Don't chop the image (uses more memory)"
    },
    "variant": {
      "type": "string",
      "default": "jpeg-compression",
      "x-order": 1,
      "description": "Model variant (options: jpeg-compression, real-image-corruptions, sensor-noise, unknown-compressions)"
    }
  }
}

Output schema

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

Schema

{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "file": {
        "type": "string",
        "format": "uri",
        "x-order": 0
      },
      "text": {
        "type": "string",
        "x-order": 1
      }
    }
  },
  "x-cog-array-type": "iterator"
}