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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-samaritan-lightning"
# Request payload
data = {
"prompt": "hyper realistic, anthropomorphic tyrannosaurus rex, smiling, highly detailed lizard skin, wearing colorful aztec armour with feathers, drinking a milkshake, tropical jungle with aztec temples in the background, dramatic studio lighting, shadows",
"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": 10,
"guidance_scale": 1,
"seed": 951102,
"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.
Samaritan Lightning SDXL
The Samaritan Lightning SDXL model revolutionizes image generation by specializing in producing niji midjourney 3D style cartoon images that enchant viewers with their unique and captivating visual storytelling. This cutting-edge model is meticulously engineered to deliver high-quality and creatively styled cartoon images that stand out in the realm of digital artistry.
A standout feature of the Samaritan Lightning SDXL is its exceptional ability to swiftly and efficiently generate high-quality cartoon images in the distinctive niji midjourney 3D style, making it a preferred choice for applications that seek to infuse their visual content with a touch of artistic flair and storytelling. With the capacity to produce captivating and immersive 3D cartoon images that resonate with creativity, this model offers a unique blend of speed and artistic innovation.
To optimize the performance of the Samaritan 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 cartoon images that embody the essence of niji midjourney artistry.
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