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import streamlit as st
import os
import pathlib
import textwrap
from PIL import Image
import google.generativeai as genai
genai.configure(api_key='AIzaSyCeNgXfZx0kJ736XFVtxXxev_RdscB0i5s')
## Function to load OpenAI model and get respones
def get_gemini_response(input,image,prompt):
model = genai.GenerativeModel('gemini-pro-vision')
response = model.generate_content([input,image[0],prompt])
return response.text
def input_image_setup(uploaded_file):
# Check if a file has been uploaded
if uploaded_file is not None:
# Read the file into bytes
bytes_data = uploaded_file.getvalue()
image_parts = [
{
"mime_type": uploaded_file.type, # Get the mime type of the uploaded file
"data": bytes_data
}
]
return image_parts
else:
raise FileNotFoundError("No file uploaded")
##initialize our streamlit app
st.set_page_config(page_title="Gemini Image Demo")
st.header("Generative AI : Business Card Reader")
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
image=""
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image.", use_column_width=True)
input=st.text_input("Input Prompt(optional): ",key="input")
submit=st.button("Submit")
input_prompt = """
Input: Image of a business card
Task: Extract and label the following information in JSON format:
Labels : person_name, company_name, occupation, contact_numbers, email addresses, website, address, other_details (services, features)
Constraints: Do not include missing information. Maintain appropriate data types (e.g., phone numbers as strings).
"""
## If ask button is clicked
if submit:
image_data = input_image_setup(uploaded_file)
response=get_gemini_response(input_prompt,image_data,input)
st.subheader("Output :")
st.write(response) |