File size: 2,472 Bytes
379d7e2 b414125 379d7e2 b414125 379d7e2 b414125 379d7e2 b414125 379d7e2 b414125 379d7e2 b414125 87fcbc9 b414125 6ba85da b414125 379d7e2 b414125 379d7e2 |
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 74 75 76 77 78 79 80 |
import gradio as gr
import pandas as pd
# Function to calculate BMI
def calculate_bmi(weight, height):
height_in_meters = height / 100 # Convert cm to meters
bmi = weight / (height_in_meters ** 2)
if bmi < 18.5:
category = "Underweight"
elif 18.5 <= bmi < 24.9:
category = "Normal weight"
else:
category = "Overweight"
return bmi, category
# Function to estimate daily calorie intake based on activity level
def calorie_intake(age, gender, weight, height, activity_level):
if gender == "Male":
bmr = 10 * weight + 6.25 * height - 5 * age + 5
else:
bmr = 10 * weight + 6.25 * height - 5 * age - 161
activity_multiplier = {
"Sedentary": 1.2,
"Lightly active": 1.375,
"Moderately active": 1.55,
"Very active": 1.725,
"Super active": 1.9
}
calories_needed = bmr * activity_multiplier[activity_level]
return calories_needed
# Function to read the CSV file and calculate BMI & Calorie Intake for each user
def process_csv(file):
df = pd.read_csv(file.name)
results = []
for _, row in df.iterrows():
name = row["Name"]
age = row["Age"]
gender = row["Gender"]
height = row["Height_cm"]
weight = row["Weight_kg"]
activity_level = row["Activity_Level"]
bmi, bmi_category = calculate_bmi(weight, height)
calories = calorie_intake(age, gender, weight, height, activity_level)
results.append({
"Name": name,
"BMI": f"{bmi:.2f}",
"BMI Category": bmi_category,
"Daily Calorie Needs (kcal)": f"{calories:.0f}",
})
return pd.DataFrame(results)
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Personal Health Tracker")
gr.Markdown("### Upload your CSV file to calculate BMI and daily calorie needs for each person. format should be: Name,Age,Gender,Height_cm,Weight_kg,Activity_Level")
# File Upload
file_upload = gr.File(label="Upload CSV File", type="filepath")
# Output for the result
output = gr.DataFrame(headers=["Name", "BMI", "BMI Category", "Daily Calorie Needs (kcal)"])
# Button to trigger processing
process_button = gr.Button("Process CSV")
# Function trigger
process_button.click(fn=process_csv, inputs=[file_upload], outputs=[output])
# Launch the app
demo.launch()
|