ControlNet Scribble

This model corresponds to the ControlNet conditioned on Scribble images.

Playground

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PNG, JPG or GIF, Up-to 2048 x 2048 px

output image


Examples

Check out what others have created with ControlNet Scribble
Example preview

steampunk underwater helmet, dark ocean background

seed: 85497675147333guidance_scale: 7.5

API

If you're looking for an API, you can choose from your desired programming language.

POST
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 import requests import base64 # Use this function to convert an image file from the filesystem to base64 def image_file_to_base64(image_path): with open(image_path, 'rb') as f: image_data = f.read() return base64.b64encode(image_data).decode('utf-8') # Use this function to fetch an image from a URL and convert it to base64 def image_url_to_base64(image_url): response = requests.get(image_url) image_data = response.content return base64.b64encode(image_data).decode('utf-8') api_key = "YOUR_API_KEY" url = "https://api.segmind.com/v1/sd1.5-controlnet-scribble" # Request payload data = { "image": image_url_to_base64("https://segmind.com/scribble-input.jpeg"), # Or use image_file_to_base64("IMAGE_PATH") "samples": 1, "prompt": "steampunk underwater helmet, dark ocean background", "negative_prompt": "Disfigured, cartoon, blurry, nude", "scheduler": "UniPC", "num_inference_steps": 25, "guidance_scale": 7.5, "strength": 1, "seed": 85497675147333, "base64": False } headers = {'x-api-key': api_key} response = requests.post(url, json=data, headers=headers) print(response.content) # The response is the generated image
RESPONSE
image/jpeg
HTTP Response Codes
200 - OKImage Generated
401 - UnauthorizedUser authentication failed
404 - Not FoundThe requested URL does not exist
405 - Method Not AllowedThe requested HTTP method is not allowed
406 - Not AcceptableNot enough credits
500 - Server ErrorServer had some issue with processing

Attributes


imageimage *

Input Image


samplesint ( default: 1 ) Affects Pricing

Number of samples to generate.

min : 1,

max : 4


promptstr *

Prompt to render


negative_promptstr ( default: None )

Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'


schedulerenum:str ( default: UniPC )

Type of scheduler.

Allowed values:


num_inference_stepsint ( default: 20 ) Affects Pricing

Number of denoising steps.

min : 20,

max : 100


guidance_scalefloat ( default: 7.5 )

Scale for classifier-free guidance

min : 0.1,

max : 25


strengthfloat ( default: 1 )

How much to transform the reference image

min : 0.1,

max : 1


seedint ( default: -1 )

Seed for image generation.


base64boolean ( default: 1 )

Base64 encoding of the output image.

To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.


Pricing

Serverless Pricing

Buy credits that can be used anywhere on Segmind

$ 0.0015 /per second
FEATURES

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Unlock the full potential of generative AI with Segmind. Create stunning visuals and innovative designs with total creative control. Take advantage of powerful development tools to automate processes and models, elevating your creative workflow.

Segmented Creation Workflow

Gain greater control by dividing the creative process into distinct steps, refining each phase.

Customized Output

Customize at various stages, from initial generation to final adjustments, ensuring tailored creative outputs.

Layering Different Models

Integrate and utilize multiple models simultaneously, producing complex and polished creative results.

Workflow APIs

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ControlNet Scribble

ControlNet Scribble model, revolutionizes image generation through manual annotations. This innovative technique empowers users to directly influence the generation process by simply scribbling or marking desired modifications on the image, bridging the gap between user intent and AI capabilities.

At the heart of ControlNet Scribble lies a sophisticated mechanism that interprets user annotations as directives for image generation. By integrating these manual markings, the model comprehends and incorporates user preferences, ensuring that the generated output aligns closely with the user's vision.

Advantages

  1. User-Directed Generation: Provides users with the autonomy to guide the image generation process through direct annotations.

  2. Fine-Grained Control: Offers unparalleled precision, allowing users to influence specific aspects of the generated image.

  3. Tailored Outputs: Ensures that the generated images resonate with user preferences, capturing the essence of their desired modifications.

Use Cases

  1. Customized Image Editing: Ideal for users who wish to make specific edits or modifications to their images.

  2. Artistic Creations: Artists can harness the scribble preprocessors to infuse hand-drawn authenticity into digital artworks.

  3. Interactive Design: Designers can iteratively shape their designs, making real-time adjustments through scribbles.

  4. Educational Tools: Can be integrated into learning platforms, allowing students to interactively engage with image-based content.

ControlNet Scribble License

ControlNet Scribble, in its commitment to ethical AI practices, has embraced the CreativeML OpenRAIL M license. This decision not only underscores the model's dedication to responsible AI but also aligns it with the principles set forth by BigScience and the RAIL Initiative. Their collaborative work in AI ethics and responsibility has set the benchmark for licenses like the OpenRAIL M.

F.A.Q.

Frequently Asked Questions

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