app.py

import streamlit as st
import requests
import io
from PIL import Image
import os
import cv2
import numpy as np

# Create a text input

api_key = os.getenv("ImageGenerating")
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
headers = {"Authorization": "f'Bearer {api_key}"}

user_input = st.text_input("Enter your text here:")

# Process the input (you can replace this with your own logic)
processed_output = user_input.upper()

# Display the processed output
# st.write(f"Processed output: {processed_output}")
def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content
image_bytes = query({
	"inputs": user_input,
})

def bytes_to_image_opencv(image_bytes):
    np_arr = np.frombuffer(image_bytes, np.uint8)
    image = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
    return image

result_image_opencv = bytes_to_image_opencv(image_bytes)
st.image(result_image_opencv,caption="image")

# image = Image.open(io.BytesIO(image_bytes))
# st.image(image, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="PNG")
# st.image(image=image,caption="image")
# st.image(image)
# st.image(image : image,caption=image)