-
Notifications
You must be signed in to change notification settings - Fork 0
/
health.py
73 lines (53 loc) · 2.12 KB
/
health.py
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
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
from dotenv import load_dotenv
load_dotenv() ## load all the environment variables
import streamlit as st
import os
import google.generativeai as genai
from PIL import Image
authorization = st.secrets["GOOGLE_API_KEY"]
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
## Function to load Google Gemini Pro Vision API And get response
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")
def get_gemini_repsonse(image,input,prompt):
model=genai.GenerativeModel('gemini-pro-vision')
response=model.generate_content([image[0],input,prompt])
return response.text
##initialize our streamlit app
st.set_page_config(page_title="Calories Counter ")
st.header("calories counter")
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
input=st.text_input("Addition Query related to food: ",key="input")
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("Results")
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
----
----
and address the query in input
"""
## If submit button is clicked
if submit:
image_data=input_image_setup(uploaded_file)
response=get_gemini_repsonse(image_data,input_prompt,input)
st.subheader("The Response is")
st.write(response)