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---
license: openrail
tags:
- stable-diffusion
- stable-diffusion-diffusers
- controlnet
inference: true
---
# Inference Endpoint for [Seg2Sat](https://huggingface.co/rgres/Seg2Sat-sd-controlnet) using [runwayml/stable-diffusion-v1-5](https://huggingface.co/stabilityai/stable-diffusion-2-1-base)
The code from the project can be found here: https://github.com/RubenGres
Inference endpoint for Seg2Map used on the demo available on rubengr.es/Seg2Sat
```python
import base64
import requests
API_URL = "https://zqz606ggn85ysase.us-east-1.aws.endpoints.huggingface.cloud"
def encode_image(image_path):
with open(image_path, "rb") as i:
b64 = base64.b64encode(i.read())
return b64.decode("utf-8")
prompt = "aerial view of jardin princier, Toulouse. Flowers, flowers, garden"
image = encode_image("handdrawn.png")
headers = {
"Accept": "image/png",
"Content-Type": "application/json"
}
# test the handler
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.content
payload = {
"inputs": prompt,
"prompt": prompt,
"image": image,
"steps": 20,
"seed": 999
}
import json
with open('payload.json', 'w') as f:
json.dump(payload, f)
image_bytes = query(payload)
# You can access the image with PIL.Image for example
import io
from PIL import Image
image = Image.open(io.BytesIO(image_bytes))
image.save("output.png")
``` |