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import requests | |
import gradio as gr | |
from PIL import Image | |
import numpy as np | |
# Replace with your Dream API key | |
api_key = 'sk-CED85fi0ZhUDMWg4GvFQ5k53o7yoL7WOaPyPQcb8zPi7eDGi' | |
def generate_image(prompt): | |
# Set up the request headers | |
headers = { | |
"Content-Type": "application/json", | |
"Authorization": f"Bearer {api_key}" | |
} | |
# Set up the request data | |
data = { | |
"model": "stable-diffusion", | |
"prompt": prompt, | |
"steps": 100, | |
"batch_size": 1, | |
"gamma": 0.99, | |
"device": "cpu" | |
} | |
# Send the request to Dream's API | |
response = requests.post("https://api.dream.co/stable-diffusion/generate", json=data, headers=headers) | |
response.raise_for_status() | |
# Extract the image URL from the response | |
image_url = response.json()["data"][0]["url"] | |
# Download and display the image using PIL and Gradio | |
image_bytes = requests.get(image_url).content | |
image = Image.open(io.BytesIO(image_bytes)) | |
image_arr = np.array(image) | |
return image_arr | |
iface = gr.Interface(fn=generate_image, inputs="text", outputs="image", title="bhAI (text to image using Dream Studio's Stable Difusion)", description="Enter a prompt to generate an image.") | |
iface.launch() | |