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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/stable-diffusion-3.5-large-txt2img"
# Request payload
data = {
"prompt": "~*~ aesthetic ~*~ #boho #fashion full-body 30-something woman laying on microfloral grass, candid pose, overlay reads Stable Diffusion 3.5, cheerful cursive typography font,",
"negative_prompt": "low quality, blurry",
"steps": 25,
"guidance_scale": 5.5,
"seed": 98552302,
"sampler": "euler",
"scheduler": "sgm_uniform",
"width": 1024,
"height": 1024,
"aspect_ratio": "custom",
"batch_size": 1,
"image_format": "jpeg",
"image_quality": 95,
"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 for image generation
The negative prompt to exclude unwanted details
Number of inference steps for generating the image
min : 10,
max : 70
Guidance scale for controlling how closely the generation matches the prompt
min : 1,
max : 15
Random number,seed for image generation
Sampling method for image generation
Allowed values:
Scheduler for image generation
Allowed values:
Width of the output image in pixels
min : 64,
max : 2048
Height of the output image in pixels
min : 64,
max : 2048
Aspect ratio of the output image. Select 'custom' to specify the width and height manually.
Allowed values:
Number of images to generate in one batch
min : 1,
max : 10
Output image format
Allowed values:
Image quality setting for output
min : 10,
max : 100
Output as base64 encoded string
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.
Stable Diffusion 3.5 Large Text-to-Image
Stable Diffusion 3.5 Large Text-to-Image (SD3.5 Large) is the latest and most advanced addition to the Stable Diffusion family of image-to-image models. SD3.5 text-to-image Large is designed to be more resource-efficient, making it a better choice for users with limited computational resources. Due to its smaller size, SD3.5 Large can run efficiently on consumer-grade hardware, including consumer PCs and laptops, as well as enterprise-tier GPUs. SD3.5 Large is designed to be more resource-efficient, making it a better choice for users with limited computational resources.
Stable Diffusion 3.5 Large Text-to-Image Capabilities
SD3.5 Large crafts stunningly realistic images, breaking new ground in photorealistic generation. It also tackles intricate prompts with multiple subjects, even if you have a typo or two. SD3.5 Large incorporates typography within your images with unparalleled precision, making your message shine.
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