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
37
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/ostris-crayon_style_lora_sdxl"
# Request payload
data = {
"prompt": "dog and cat",
"negative_prompt": "boring, poorly drawn, bad artist, (worst quality:1.4), simple background, uninspired, (bad quality:1.4), monochrome, low background contrast, background noise, duplicate, crowded, (nipples:1.2), big breasts",
"scheduler": "UniPC",
"num_inference_steps": 25,
"guidance_scale": 8,
"samples": 1,
"seed": 3426017487,
"img_width": 1024,
"img_height": 1024,
"base64": False,
"lora_scale": 1
}
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.
Scale of the lora
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.
Crayon Style - SDXL LoRA
Crayon Style - SDXL LoRA is an innovative AI model that turns the art of crayon drawing into a digital reality. This unique model is designed to convert any text prompt into a vibrant, crayon-style drawing, blending the simplicity of crayons with the complexity of AI technology. It's perfect for artists, educators, parents, and anyone looking to explore the charming world of crayon art through a modern lens.
Advantages
-
Authentic Crayon Texture: Reproduces the unique texture and feel of crayon art..
-
Creative Flexibility: Offers endless possibilities for creative expression through text.
Use Cases
-
Creative Projects:Ideal for artists and hobbyists looking to explore new styles and mediums.
-
Marketing and Advertising: Design unique, eye-catching visuals for marketing materials with a hand-drawn feel.
-
Children's Book Illustrations: Create charming illustrations for children's books or storytelling.
-
Educational Tools: Enhance learning experiences by creating crayon illustrations of educational concepts.
Other Popular Models
idm-vton
Best-in-class clothing virtual try on in the wild
faceswap-v2
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
sdxl-inpaint
This model is capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask
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
