llsean / clip-interrogator-image-analysis

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  • 14 runs

Run llsean/clip-interrogator-image-analysis 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
Self-portrait oil painting, a beautiful cyborg with golden hair, 8k
For multiple prompts, enter each on a new line.
width
integer
768
Width of output image. Lower if out of memory
height
integer
768
Height of output image. Lower if out of memory
sizing_strategy
string (enum)
width/height

Options:

width/height, input_image, control_image

Decide how to resize images – use width/height, resize based on input image or control image
image
string
Input image for img2img
prompt_strength
number
0.8

Max: 1

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
num_images
integer
1

Min: 1

Max: 50

Number of images per prompt
num_inference_steps
integer
8

Min: 1

Max: 50

Number of denoising steps. Recommend 1 to 8 steps.
guidance_scale
number
8

Min: 1

Max: 20

Scale for classifier-free guidance
lcm_origin_steps
integer
50

Min: 1

None
seed
integer
Random seed. Leave blank to randomize the seed
control_image
string
Image for controlnet conditioning
controlnet_conditioning_scale
number
2

Min: 0.1

Max: 4

Controlnet conditioning scale
control_guidance_start
number
0

Max: 1

Controlnet start
control_guidance_end
number
1

Max: 1

Controlnet end
canny_low_threshold
number
100

Min: 1

Max: 255

Canny low threshold
canny_high_threshold
number
200

Min: 1

Max: 255

Canny high threshold
archive_outputs
boolean
False
Option to archive the output images
disable_safety_checker
boolean
False
Disable safety checker for generated images. This feature is only available through the API

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"
}