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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")
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image.", use_column_width=True)
submit=st.button("Submit")
input_prompt ="""
You are an expert in understanding business cards.
Input: Image of a business card.
Task: Extract and label the following information in JSON format:
Lagels : person_name, company_name, occupation, contact_number, email addresse, website, address, other_details (services, features, etc.)
Constraints: Do not include missing information.
"""
if submit:
image_data = input_image_setup(uploaded_file)
if image_data is not None:
response = get_gemini_response(input_prompt, image_data, input_text)
st.subheader("Output :")
st.write(response) |