Model details
View repositoryExample usage
The model accepts a prompt which is some text describing the image you want to generate. The output images tend to get better as you add more descriptive words to the prompt.
The output JSON object contains a key called data which represents the generated image as a base64 string.
Input
1import httpx
2import os
3import base64
4from PIL import Image
5from io import BytesIO
6# Replace the empty string with your model id below
7model_id = ""
8baseten_api_key = os.environ["BASETEN_API_KEY"]
9# Function used to convert a base64 string to a PIL image
10def b64_to_pil(b64_str):
11 return Image.open(BytesIO(base64.b64decode(b64_str)))
12data = {
13 "prompt": 'red velvet cake spelling out the words "FLUX SCHNELL", tasty, food photography, dynamic shot'
14}
15# Call model endpoint
16res = httpx.post(
17 f"https://model-{model_id}.api.baseten.co/production/predict",
18 headers={"Authorization": f"Api-Key {baseten_api_key}"},
19 json=data
20)
21# Get output image
22res = res.json()
23output = res.get("data")
24# Convert the base64 model output to an image
25img = b64_to_pil(output)
26img.save("output_image.jpg")
27JSON output
1{
2 "output": "iVBORw0KGgoAAAANSUhEUgAABAAAAAQACAIAAA..."
3}Preview
