API
If you're looking for an API, you can choose from your desired programming language.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
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/sd1.5-scifi"
# Request payload
data = {
"prompt": "futuristic sci-fi high-tech city of Atlantis in late afternoon light, wispy clouds in a blue sky",
"negative_prompt": "blurry, blurred, amateur, ugly, low quality, sketch, low resolution, warped, crooked, deformed, cartoony, low detail",
"scheduler": "dpmpp_2m",
"num_inference_steps": 30,
"guidance_scale": 5,
"samples": 1,
"seed": 516797155652,
"img_width": 512,
"img_height": 768,
"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
Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'
Type of scheduler.
Allowed values:
Number of denoising steps.
min : 20,
max : 100
Scale for classifier-free guidance
min : 0.1,
max : 25
Number of samples to generate.
min : 1,
max : 4
Seed for image generation.
Width of the image.
Allowed values:
Height of the Image
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.
Scifi
The Scifi Model is a groundbreaking AI tool specifically designed for the creation of breathtaking science fiction environments. This model is a dream come true for creators and enthusiasts of the sci-fi genre, offering the ability to generate immersive and visually stunning settings that capture the essence of futuristic and otherworldly landscapes.
The Scifi Model is trained extensively on various aspects of science fiction imagery. This training enables the model to understand and replicate the unique elements that define sci-fi environments, from sprawling futuristic cities to distant alien landscapes.
Advantages
-
Cinematic Quality: Produces high-quality, visually captivating scifi environments perfect for film and game settings.
-
Immersive Worlds: Creates detailed and atmospheric settings that draw viewers into the heart of a scifi narrative.
-
Storytelling Enhancement: Elevates narrative and visual storytelling in scifi projects.
Use Cases
-
Video Game Development:Helps game designers craft immersive worlds that enhance gameplay and player experience.
-
Digital Art: Artists can explore and create unique sci-fi themed artworks.
-
Film and Television Production: Ideal for conceptualizing and creating visual effects and backgrounds.
Other Popular Models
fooocus
Fooocus enables high-quality image generation effortlessly, combining the best of Stable Diffusion and Midjourney.
illusion-diffusion-hq
Monster Labs QrCode ControlNet on top of SD Realistic Vision v5.1
sdxl1.0-txt2img
The SDXL model is the official upgrade to the v1.5 model. The model is released as open-source software
sd2.1-faceswapper
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training
