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| import streamlit as st | |
| import google.generativeai as genai | |
| import os | |
| from dotenv import load_dotenv | |
| load_dotenv() # loading all the environment variables | |
| from PIL import Image | |
| genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) | |
| def get_gemini_response(input_prompt,image): | |
| model=genai.GenerativeModel('gemini-pro-vision') | |
| response=model.generate_content([input_prompt,image[0]]) | |
| 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="Calorie Advisor App") | |
| st.header("Calorie Advisor App") | |
| 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 total calories") | |
| input_prompt=""" | |
| You are an expert in nutrition. You need to see the food items from the image | |
| and calculate the total calories. Provide the details of every | |
| food item with calories intake in below format | |
| 1. Item 1 - no. of calories | |
| 2. Item 2 - no. of calories | |
| ---- | |
| ---- | |
| Finally, mention whether the food is health or not and also mention the | |
| percentage split of carbohydrates,proteins,fats,fibers,sugar and other | |
| things required in our diet. | |
| """ | |
| if submit: | |
| image_data=input_image_setup(uploaded_file) | |
| response=get_gemini_response(input_prompt,image_data) | |
| st.header("The Response is") | |
| st.write(response) |