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