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