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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-dreamshaper-lightning"
# Request payload
data = {
"prompt": "1girl,on stage,beautiful,rich details,bokeh,",
"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": 7,
"guidance_scale": 1,
"seed": 2644125604,
"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.
DreamShaper Lightning SDXL
The DreamShaper Lightning SDXL model emerges as a versatile powerhouse in image generation, serving as a general-purpose solution that excels in producing high-quality visuals across various domains including photography, art, anime, and manga images. This advanced model is designed to deliver exceptional results in a wide range of creative endeavors. Distinguished by its all-encompassing capabilities, the DreamShaper Lightning SDXL sets a new standard for excellence by aiming to excel in diverse visual outputs such as photos, artwork, anime illustrations, and manga images.
A standout feature of the DreamShaper Lightning SDXL is its ability to swiftly and efficiently generate high-quality images across multiple genres and styles, making it a versatile choice for applications that require excellence in various visual formats. With the capacity to produce stunning photography, intricate artwork, captivating anime scenes, and engaging manga illustrations, this model offers a comprehensive solution for creative professionals seeking top-tier results.
To optimize the performance of the DreamShaper 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 meet the highest standards across photography, art, anime, and manga genres
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