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import os
import streamlit as st
import google.generativeai as genai
from PIL import Image
import base64
# Function to set the Google API key
def set_api_key(api_key):
os.environ["GOOGLE_API_KEY"] = api_key
genai.configure(api_key=api_key)
# Function to get description from the image
def get_image_description(image, user_prompt=None):
model = genai.GenerativeModel(model_name="gemini-1.5-flash")
prompt = user_prompt if user_prompt else "What is in this photo?"
response = model.generate_content([prompt], images=[image])
return response.text
# Helper function to convert image to base64
def get_base64_of_image(image_path):
with open(image_path, "rb") as image_file:
base64_str = base64.b64encode(image_file.read()).decode()
return base64_str
def main():
st.set_page_config(page_title="Talk to Image", layout="wide")
st.markdown(
f"""
<style>
.stApp {{
background: url(data:image/png;base64,{get_base64_of_image('image.png')});
background-size: cover
}}
</style>
""",
unsafe_allow_html=True
)
st.title("Image Description using Gemini!")
st.subheader("Upload your Image File")
uploaded_file = st.file_uploader("Upload your image file", type=["png", "jpg", "jpeg"])
st.sidebar.header("Configuration")
api_key = st.sidebar.text_input("Google API Key:", type="password")
if st.sidebar.button("Set API Key"):
if api_key:
set_api_key(api_key)
st.sidebar.success("API Key set successfully.")
else:
st.sidebar.error("Please enter a valid API Key.")
prompt = st.text_input("Enter your prompt (optional):", value="What is in this photo?")
if st.button("Describe Image") and uploaded_file:
if "GOOGLE_API_KEY" in os.environ and os.environ["GOOGLE_API_KEY"]:
try:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
with st.spinner("Generating description..."):
description = get_image_description(image, prompt)
st.write("**Description:** ", description)
except Exception as e:
st.error(f"An error occurred: {e}")
else:
st.warning("Please enter your Google API key and click 'Set API Key'.")
st.markdown("---")
st.write("Happy to Connect:")
kaggle, linkedin, google_scholar, youtube, github = st.columns(5)
image_urls = {
"kaggle": "https://www.kaggle.com/static/images/site-logo.svg",
"linkedin": "https://upload.wikimedia.org/wikipedia/commons/thumb/c/ca/LinkedIn_logo_initials.png/600px-LinkedIn_logo_initials.png",
"google_scholar": "https://upload.wikimedia.org/wikipedia/commons/thumb/c/c7/Google_Scholar_logo.svg/768px-Google_Scholar_logo.svg.png",
"youtube": "https://upload.wikimedia.org/wikipedia/commons/thumb/7/72/YouTube_social_white_square_%282017%29.svg/640px-YouTube_social_white_square_%282017%29.svg.png",
"github": "https://github.githubassets.com/assets/GitHub-Mark-ea2971cee799.png"
}
social_links = {
"kaggle": "https://www.kaggle.com/muhammadimran112233",
"linkedin": "https://www.linkedin.com/in/muhammad-imran-zaman",
"google_scholar": "https://scholar.google.com/citations?user=ulVFpy8AAAAJ&hl=en",
"youtube": "https://www.youtube.com/@consolioo",
"github": "https://github.com/Imran-ml"
}
kaggle.markdown(f'<a href="{social_links["kaggle"]}"><img src="{image_urls["kaggle"]}" width="50" height="50"></a>', unsafe_allow_html=True)
linkedin.markdown(f'<a href="{social_links["linkedin"]}"><img src="{image_urls["linkedin"]}" width="50" height="50"></a>', unsafe_allow_html=True)
google_scholar.markdown(f'<a href="{social_links["google_scholar"]}"><img src="{image_urls["google_scholar"]}" width="50" height="50"></a>', unsafe_allow_html=True)
youtube.markdown(f'<a href="{social_links["youtube"]}"><img src="{image_urls["youtube"]}" width="50" height="50"></a>', unsafe_allow_html=True)
github.markdown(f'<a href="{social_links["github"]}"><img src="{image_urls["github"]}" width="50" height="50"></a>', unsafe_allow_html=True)
st.markdown("---")
if __name__ == "__main__":
main()
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