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import streamlit as st
import os
import pathlib
import textwrap
from PIL import Image
import google.generativeai as genai
os.getenv("GOOGLE_API_KEY")
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
## 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="Image description APP")
st.header("Image description Application 🤖💬")
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 nutritionist where you need to see the food items from the image
and calculate the total calories, also provide the details of every food items with calories intake
is below format
1. Item 1 - no of calories
2. Item 2 - no of calories
----
----
"""
## 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("The Response is")
st.write(response) |