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cf3981b e149839 cf3981b 4d5ba42 cf3981b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | import pathlib
import textwrap
import streamlit as st
import google.generativeai as genai
from PIL import Image
from IPython.display import Markdown
from IPython.display import display
genai.configure(api_key='AIzaSyA_XykKxC4aSi0af9VH5uP2eQlp9Nh25Ds')
model = genai.GenerativeModel(model_name="models/gemini-pro-vision")
def geminin_response(input,image,prompt):
response = model.generate_content([input,image[0],prompt])
return response.text
st.set_page_config(page_title="Multi Language Text Extractor")
st.header("Gemini Application")
input = st.text_input("Input Query :",key='input')
uploaded_file = st.file_uploader("Choose an image:",type=['.jpg','.pdf','.jpeg','png'])
image=''
if uploaded_file is not None:
format = ['.jpg','.jpeg','png']
for form in format:
if str(uploaded_file.name).endswith(form):
image = Image.open(uploaded_file)
st.image(image,caption='Uploaded Image!!!',use_column_width=True)
elif str(uploaded_file.name).endswith('.pdf'):
st.warning('Please Upload Images !!!', icon="⚠️")
break
submit = st.button("Extract Information about this image")
input_prompt = "We are uploading an image and you will have to answer any questions based on image"
def input_image_details(uploaded_file):
if uploaded_file:
bytes_data = uploaded_file.getvalue()
image_parts = [{
"mime_type":uploaded_file.type,
"data":bytes_data
}]
return image_parts
if submit:
image_data = input_image_details(uploaded_file)
resp = geminin_response(input_prompt,image_data,input)
st.subheader("The Response is:")
st.write(resp)
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