|
|
| import streamlit as st |
| import os |
| import pathlib |
| import textwrap |
| from PIL import Image |
|
|
|
|
| import google.generativeai as genai |
|
|
| genai.configure(api_key='AIzaSyAA_R5VXv1qjJ5jDMObkluREA8BxJO67RU') |
|
|
| |
|
|
| 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): |
| |
| if uploaded_file is not None: |
| |
| bytes_data = uploaded_file.getvalue() |
|
|
| image_parts = [ |
| { |
| "mime_type": uploaded_file.type, |
| "data": bytes_data |
| } |
| ] |
| return image_parts |
| else: |
| raise FileNotFoundError("No file uploaded") |
|
|
|
|
| |
|
|
| st.set_page_config(page_title="Gemini Image Demo") |
|
|
| st.header("Generative AI : Invoice Reader") |
| input=st.text_input("Input Prompt: ",key="input") |
| 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) |
|
|
|
|
| submit=st.button("Tell me about the image") |
|
|
| input_prompt = """ |
| You are an expert in understanding invoices. |
| You will receive input images as invoices & |
| you will have to answer questions based on the input image |
| """ |
|
|
| |
|
|
| if submit: |
| image_data = input_image_setup(uploaded_file) |
| response=get_gemini_response(input_prompt,image_data,input) |
| st.subheader("The Response is") |
| st.write(response) |
