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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/Simple_Vector_Flux"
# Request payload
data = {
"prompt": "v3ct0r style, simple vector art, salesman giving a thumbs up in front of a car, character asset, clip art",
"steps": 25,
"seed": 6652105,
"scheduler": "simple",
"sampler_name": "euler",
"aspect_ratio": "1:1",
"lora_strength": 1
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated imageAttributes
Text prompt for generating the image
Number of steps for generating the image
min : 1,
max : 100
Seed for random number generation
Scheduler type for image generation
Allowed values:
Sampler type for image generation
Allowed values:
Aspect ratio for the generated image
Allowed values:
Strength of the LoRA (Low-Rank Adaptation) for fine-tuning
min : -10,
max : 10
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.
Simple Vector Flux Lora
Simple Vector Flux was trained on a curated dataset of ~50 synthetic images in classic vector style, 17 epochs, 2 repeats, ~1700 steps.
This is a work in progress and it can be a little temperamental, the captioning was done using Joy Caption Batch with the trigger "v3ct0r" and "vector" in the prefix of the captions.
You have to work a little bit to get desired results and sometimes there is bleeding/blending of subjects but overall the style is present and the results can be really good. This LoRA takes a couple of tries adjusting your prompt and adding tokens to match the style.
Trigger words
You should use v3ct0r to trigger the image generation.
You should use vector to trigger the image generation.
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