API
If you're looking for an API, you can choose from your desired programming language.
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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/kandinsky2.1-txt2im"
# Request payload
data = {
"prompt": "tiny isometric city on a tiny floating island, highly detailed, 3d render",
"negative_prompt": "NONE",
"scheduler": "DDIM",
"samples": 1,
"num_inference_steps": 25,
"guidance_scale": 7.5,
"seed": 1024,
"img_width": 512,
"img_height": 512,
"base64": False
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated imageAttributes
Prompt to render
Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'
Type of scheduler.
Allowed values:
Number of samples to generate.
min : 1,
max : 8
Number of denoising steps.
min : 10,
max : 40
Scale for classifier-free guidance
Seed for image generation.
Image resolution.
Image resolution.
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.
Kandinsky 2.1
Kadinsky is an AI-powered tool that can be used to create abstract art. It works by first generating a random image. Then, it uses a deep learning model to transform the image into an abstract painting. Kadinsky is a powerful tool that can be used to create a variety of abstract art styles, such as expressionism, cubism, and surrealism.
To use Kadinsky, you can follow these steps:
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Go to the Segmind website: https://segmind.com/
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Click on the "Models" tab and select "Kadinsky".
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Click on the "Try it out" button and upload an image that you want to use as a starting point.
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Click on the "Generate" button to generate the abstract painting.
Kadinsky is a powerful tool that can be used to create abstract art. It is easy to use and it can be used to achieve impressive results. If you are interested in experimenting with the tool, contact us for customized solutions, large-scale deployment, and research support.
Applications/Use Cases
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Try using different starting images to see how they affect the output painting.
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Experiment with different settings for the abstract painting model to see how they affect the output painting.
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Compare the results of Kadinsky to other abstract art generation algorithms.
Other Popular Models
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SDXL ControlNet gives unprecedented control over text-to-image generation. SDXL ControlNet models Introduces the concept of conditioning inputs, which provide additional information to guide the image generation process
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sdxl1.0-txt2img
The SDXL model is the official upgrade to the v1.5 model. The model is released as open-source software
sd2.1-faceswapper
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training
