File size: 3,338 Bytes
4be498f 8b3ed0b 4be498f 8b3ed0b 4be498f f0aa736 4be498f 8b3ed0b 4be498f 8b3ed0b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
#------------------------------------------------------------------------
# Import
#------------------------------------------------------------------------
import streamlit as st
import requests
from PIL import Image
import io
import os
#------------------------------------------------------------------------
# HF API
#------------------------------------------------------------------------
# Retrieve the HF API key from environment variables
hf_api_key = os.getenv('HF_API_KEY')
if not hf_api_key:
raise ValueError("HF_API_KEY not set in environment variables")
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
headers = {"Authorization": f"Bearer {hf_api_key}"}
#------------------------------------------------------------------------
# Configurations
#------------------------------------------------------------------------
# Streamlit page setup
st.set_page_config(
page_title="Intervention Program Analysis",
page_icon=":bar_chart:",
layout="centered",
initial_sidebar_state="auto",
menu_items={
'Get Help': 'mailto:[email protected]',
'About': "This app is built to support spreadsheet analysis"
}
)
#------------------------------------------------------------------------
# Sidebar
#------------------------------------------------------------------------
with st.sidebar:
# Password input field
# password = st.text_input("Enter Password:", type="password")
# Set the desired width in pixels
image_width = 300
# Define the path to the image
image_path = "mimtss.png"
# Display the image
st.image(image_path, width=image_width)
# Toggle for Help and Report a Bug
with st.expander("Need help and report a bug"):
st.write("""
**Contact**: Cheyne LeVesseur, PhD
**Email**: [email protected]
""")
st.divider()
st.subheader('User Instructions')
# Principles text with Markdown formatting
User_Instructions = """
Enter a detailed description of the image you want to generate, and the app will create it based on your prompt.
"""
st.markdown(User_Instructions)
#------------------------------------------------------------------------
# Define functions
#------------------------------------------------------------------------
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
if response.status_code != 200:
st.error(f"Error: {response.status_code} - {response.text}")
return None
return response.content
def generate_image(prompt):
image_bytes = query({"inputs": prompt})
if image_bytes:
return Image.open(io.BytesIO(image_bytes))
return None
def main():
st.title("Stable Diffusion XL 1.0")
prompt = st.text_input("Enter a prompt for image generation:")
if st.button("Generate Image"):
if prompt:
image = generate_image(prompt)
if image:
st.image(image, caption="Generated Image")
else:
st.warning("Please enter a prompt.")
#------------------------------------------------------------------------
# Main Guard
#------------------------------------------------------------------------
if __name__ == "__main__":
main() |