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import streamlit as st |
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import os |
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import pathlib |
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import textwrap |
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from PIL import Image |
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import google.generativeai as genai |
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genai.configure(api_key='AIzaSyCeNgXfZx0kJ736XFVtxXxev_RdscB0i5s') |
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def get_gemini_response(input, image,prompt): |
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model = genai.GenerativeModel('gemini-pro-vision') |
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response = model.generate_content([input,image[0],prompt]) |
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return response.text |
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def input_image_setup(uploaded_file): |
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if uploaded_file is not None: |
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bytes_data = uploaded_file.getvalue() |
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image_parts = [ |
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{ |
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"mime_type": uploaded_file.type, |
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"data": bytes_data |
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} |
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] |
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return image_parts |
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else: |
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raise FileNotFoundError("No file uploaded") |
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st.set_page_config(page_title="Gemini Image Demo") |
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st.header("Generative AI : Business Card Reader") |
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uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) |
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image="" |
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if uploaded_file is not None: |
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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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input=st.text_input("Input Prompt (optional) : ",key="input") |
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submit=st.button("Submit") |
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input_prompt = """ |
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You are an expert in understanding business cards. |
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Input: Image of a business card |
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Task: Extract and label the following information in JSON format if available: |
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Labels : company_name, person_name, occupation, contact_number, email addresse, website, address, other_details (services, features, etc.) |
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Constraints: Do not include missing information. |
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""" |
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if submit: |
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image_data = input_image_setup(uploaded_file) |
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response=get_gemini_response(input_prompt,image_data, input) |
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st.subheader("Output :") |
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st.write(response) |
