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| import os | |
| import google.generativeai as genai | |
| import streamlit as st | |
| from dotenv import load_dotenv, find_dotenv | |
| from PIL import Image | |
| load_dotenv(find_dotenv()) | |
| genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) | |
| def get_gemini_response(input, image): | |
| model = genai.GenerativeModel("gemini-1.5-pro-latest") | |
| response = model.generate_content([input,image[0]]) | |
| return response.text | |
| def input_image_setup(uploaded_file): | |
| # check if a file has been uploaded | |
| 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="Vaibhav's Nutrition Monitor", page_icon="🔮") | |
| st.header("Vaibhav's Nutrition Monitor") | |
| # input=st.text_input("Input Prompt: ",key="input") | |
| uploaded_file = st.file_uploader("Upload an image of the food item", 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 total calories") | |
| 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 | |
| ---- | |
| ---- | |
| Finally you can also mention whether the food is healthy or not. Mention the percentage | |
| split of protein, carbs and fats in the food item. Mention total fiber content in the food item. | |
| Also mention any other important details about the food item. | |
| """ | |
| ## If submit button is clicked | |
| if submit: | |
| image_data=input_image_setup(uploaded_file) | |
| response= get_gemini_response(input_prompt,image_data) | |
| st.subheader("Food Analysis:") | |
| st.write(response) | |