AlexanderCGO2 / demo-automatic1111-sd-webui

Banana Implementation

This repository is the implementation of stable-diffusion-webui

Endpoints

At the moment only one endpoint is implemented.

• /txt2img is the implementation of stable-diffusion-webui /sdapi/v1/txt2img api.

  Json Input

  {
      "body": {
          "params": {
              "prompt": "CAT",
              "negative_prompt": "low quality",
              "steps": 25,
              "sampler_name": "Euler a",
              "cfg_scale": 7.5,
              "seed": 42,
              "batch_size": 1,
              "n_iter": 1,
              "width": 400,
              "height": 400,
              "tiling": 'false',
          }
      }
  }

  OUTPUT:

  {
      "output": "<base64 image>"
  }

• img2img is the implementation of /sdapi/v1/img2img api

  JSON INPUT

  img2img_inputs = {
      "params": {
          "prompt": "blue banana",
          "negative_prompt": "cartoonish, low quality",
          "steps": 25,
          "sampler_name": "Euler a",
          "cfg_scale": 7.5,
          "denoising_strength": 0.7,
          "seed": 42,
          "batch_size": 1,
          "n_iter": 1,
          "width": 768,
          "height": 768,
          "tiling": "false",
          "init_images": [
              "b64images"
          ]
      }
  }
  

Client Implementation in Python

import banana_dev as client

my_model = client.Client(
    api_key="[API_KEY]",
    model_key="[MODEL_KEY]",
    url="[MODEL_URL]",
)

txt2img_inputs = {
    "params": {
        "prompt": "Nurse in scrub dress with her hair tied",
        "negative_prompt": "low quality",
        "steps": 25,
        "sampler_name": "Euler a",
        "cfg_scale": 7.5,
        "seed": 42,
        "batch_size": 1,
        "n_iter": 1,
        "width": 400,
        "height": 400,
        "tiling": "false",
    }
}

img2img_inputs = {
    "params": {
        "prompt": "blue banana",
        "negative_prompt": "cartoonish, low quality",
        "steps": 25,
        "sampler_name": "Euler a",
        "cfg_scale": 7.5,
        "denoising_strength": 0.7,
        "seed": 42,
        "batch_size": 1,
        "n_iter": 1,
        "width": 768,
        "height": 768,
        "tiling": "false",
        "init_images": [
            "b64images"
        ]
    }
}



txt2img_result, meta = my_model.call("/txt2img", txt2img_inputs)
img2img_result, meta = my_model.call("/img2img", img2img_inputs)

print(txt2img_inputs, img2img_result)