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/sd1.5-526mix"
# Request payload
data = {
"prompt": "POV photo of an amazing snozboffle milkshake with chocolate syrup on a plain glass. busy retro diner interior background, people in background, kodak vision 3",
"negative_prompt": "<neg-sketch-2>, illustration, unreal, unclear",
"scheduler": "dpmpp_sde_ancestral",
"num_inference_steps": 20,
"guidance_scale": 7,
"samples": 1,
"seed": 3111376584,
"img_width": 512,
"img_height": 768,
"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 denoising steps.
min : 20,
max : 100
Scale for classifier-free guidance
min : 0.1,
max : 25
Number of samples to generate.
min : 1,
max : 4
Seed for image generation.
Width of the image.
Allowed values:
Height of the Image
Allowed values:
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.
526 Mix
526 Mix is based on Stable Diffusion 1.5, a cutting-edge model designed to offer enhanced saturation control and unparalleled realism. Whether you're aiming for 3D style images, classic paintings, or detailed illustrations, the 526 Mix model offers tailored solutions to meet your creative needs. The 526 Mix model, in its latest version at 7 CFG, has significantly reduced issues related to high saturation compared to its predecessors.
Advantages
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Enhanced Saturation Control: The model's design ensures vibrant outputs without over-saturation, providing a balanced visual experience.
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Tailored Prompts for Paintings: For fullscreen painting outputs without any 3D-like anomalies, using "framed, borders, photo" as a negative prompt is suggested.
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Optimized Illustration Outputs: For illustrations, negative prompts like "photo" or "realistic" can yield the best results.
Use Cases
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Digital Art Creation: Artists can harness the 526 Mix model to craft vibrant paintings or detailed illustrations.
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3D Visualization: Ideal for designers and animators seeking to create lifelike 3D images with controlled saturation.
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Educational Platforms: Art students can explore various styles and techniques, enhancing their learning experience.
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Interactive Design: Designers can iteratively shape their creations, experimenting with a myriad of styles and saturation levels.
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