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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/sdxl1.0-colossus-lightning"
# Request payload
data = {
"prompt": "half body,cinematic film still, a cat mage, armor, wrathful eyes, dark atmosphere, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic",
"negative_prompt": "((close up)),(octane render, render, drawing, bad photo, bad photography:1.3), (worst quality, low quality, blurry:1.2), (bad teeth, deformed teeth, deformed lips), (bad anatomy, bad proportions:1.1), (deformed iris, deformed pupils), (deformed eyes, bad eyes), (deformed face, ugly face, bad face), (deformed hands, bad hands, fused fingers), morbid, mutilated, mutation, disfigured",
"samples": 1,
"scheduler": "DPM++ SDE",
"num_inference_steps": 9,
"guidance_scale": 1,
"seed": 902448,
"img_width": 1024,
"img_height": 1024,
"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
blur, noisy, disfigured
Number of samples to generate.
min : 1,
max : 4
Type of scheduler.
Allowed values:
Number of denoising steps.
min : 1,
max : 100
Scale for classifier-free guidance
min : 1,
max : 25
Seed for image generation.
min : -1,
max : 999999999999999
Can only be 1024 for SDXL
Allowed values:
Can only be 1024 for SDXL
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.
Colossus Lightning SDXL
The Colossus Lightning SDXL model redefines image generation capabilities by producing a wide range of content with exceptional realism, spanning from extremely realistic pictures to captivating anime and art pieces. This advanced model is a powerhouse in creating diverse visual content that resonates with lifelike precision and artistic flair. This model is finely tuned to excel in producing a variety of visuals that encompass extreme realism, anime aesthetics, and artistic expressions.
A standout feature of the Colossus Lightning SDXL is its unparalleled ability to swiftly and efficiently create high-quality images across various styles and genres, making it a go-to choice for applications that demand a broad spectrum of visual content. With the capability to generate realistic pictures, anime illustrations, and artistic creations with exceptional detail and precision, this model offers a unique blend of speed and creative versatility.
To optimize the performance of the Colossus Lightning SDXL, ensuring compatibility with the DPM++ SDE Karras / DPM++ SDE sampler is essential. Leveraging 4-6 sampling steps and a CFG Scale set between 1 and 2 is recommended to achieve peak performance and efficiency in the image generation process. These tailored settings are crucial for unlocking the full creative potential of this advanced model and producing visuals that span from extreme realism to captivating anime and art pieces.
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