Create BodyMetrics_Pro.py

Author: rogers-cyber

BMI-prediction-system/BodyMetrics_Pro.py

@@ -0,0 +1,205 @@
+"""
+BodyMetrics Pro v2.0 - Health Intelligence Edition
+ML-Powered BMI Risk Prediction System
+Age • Gender • AI Risk Scoring • Visual Analytics
+"""
+
+import tkinter as tk
+from tkinter import messagebox
+import ttkbootstrap as tb
+from ttkbootstrap.constants import *
+
+import numpy as np
+from sklearn.linear_model import LogisticRegression
+from sklearn.preprocessing import StandardScaler
+
+from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
+from matplotlib.figure import Figure
+
+
+# ---------------------- ML ENGINE ----------------------
+class BMIRiskModel:
+    def __init__(self):
+        self.scaler = StandardScaler()
+        self.model = LogisticRegression()
+        self._train()
+
+    def _train(self):
+        # Synthetic training data: [BMI, Age, Gender]
+        # Gender: Male=1, Female=0
+        X = np.array([
+            [18, 18, 0], [22, 25, 1], [24, 30, 0],
+            [27, 40, 1], [29, 45, 0], [32, 50, 1],
+            [35, 55, 0], [38, 60, 1], [42, 65, 0]
+        ])
+        y = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])  # Risk levels
+
+        X_scaled = self.scaler.fit_transform(X)
+        self.model.fit(X_scaled, y)
+
+    def predict(self, bmi, age, gender):
+        X = np.array([[bmi, age, gender]])
+        X_scaled = self.scaler.transform(X)
+        return self.model.predict(X_scaled)[0]
+
+
+# ---------------------- UTIL ----------------------
+def calculate_bmi(weight, height):
+    return round(weight / (height ** 2), 2)
+
+
+def risk_label(code):
+    return {
+        0: ("Low Risk", "✅"),
+        1: ("Moderate Risk", "⚠️"),
+        2: ("High Risk", "❌")
+    }[code]
+
+
+# ---------------------- MAIN APP ----------------------
+class BMIPredictorApp:
+    APP_NAME = "BodyMetrics Pro"
+    APP_VERSION = "2.0"
+
+    def __init__(self):
+        self.root = tb.Window(themename="darkly")
+        self.root.title(f"{self.APP_NAME} v{self.APP_VERSION}")
+        self.root.minsize(720, 620)
+
+        self.model = BMIRiskModel()
+
+        self._build_ui()
+
+    # ---------------------- UI ----------------------
+    def _build_ui(self):
+        main = tb.Frame(self.root, padding=15)
+        main.pack(fill=BOTH, expand=True)
+
+        tb.Label(
+            main,
+            text=f"🧠 {self.APP_NAME}",
+            font=("Segoe UI", 22, "bold")
+        ).pack()
+
+        tb.Label(
+            main,
+            text="ML-Based BMI Risk Prediction System",
+            font=("Segoe UI", 10, "italic"),
+            foreground="#9ca3af"
+        ).pack(pady=(0, 20))
+
+        # ---------------------- INPUT PANEL ----------------------
+        form = tb.Labelframe(main, text="Personal Data", padding=15)
+        form.pack(fill=X, pady=10)
+
+        self.weight = tb.Entry(form, width=15)
+        self.height = tb.Entry(form, width=15)
+        self.age = tb.Entry(form, width=15)
+
+        self.gender = tk.StringVar(value="Male")
+
+        labels = ["Weight (kg)", "Height (m)", "Age"]
+        entries = [self.weight, self.height, self.age]
+
+        for i, (l, e) in enumerate(zip(labels, entries)):
+            tb.Label(form, text=l).grid(row=i, column=0, sticky=W, pady=5)
+            e.grid(row=i, column=1, padx=10)
+
+        tb.Label(form, text="Gender").grid(row=3, column=0, sticky=W, pady=5)
+        tb.Combobox(
+            form,
+            values=["Male", "Female"],
+            textvariable=self.gender,
+            width=13
+        ).grid(row=3, column=1)
+
+        # ---------------------- ACTIONS ----------------------
+        tb.Button(
+            main,
+            text="🚀 Analyze Health Risk",
+            bootstyle=SUCCESS,
+            command=self.analyze
+        ).pack(pady=10)
+
+        self.progress = tb.Progressbar(
+            main,
+            bootstyle="success-striped",
+            maximum=100
+        )
+        self.progress.pack(fill=X, pady=5)
+
+        # ---------------------- RESULT ----------------------
+        self.result = tb.Label(
+            main,
+            text="Awaiting input...",
+            font=("Segoe UI", 14)
+        )
+        self.result.pack(pady=10)
+
+        # ---------------------- CHART ----------------------
+        chart_frame = tb.Labelframe(main, text="BMI Visualization", padding=10)
+        chart_frame.pack(fill=BOTH, expand=True)
+
+        self.figure = Figure(figsize=(5, 3))
+        self.ax = self.figure.add_subplot(111)
+        self.canvas = FigureCanvasTkAgg(self.figure, chart_frame)
+        self.canvas.get_tk_widget().pack(fill=BOTH, expand=True)
+
+    # ---------------------- LOGIC ----------------------
+    def analyze(self):
+        try:
+            self.progress["value"] = 0
+            self.root.update_idletasks()
+
+            w = float(self.weight.get())
+            h = float(self.height.get())
+            age = int(self.age.get())
+            gender = 1 if self.gender.get() == "Male" else 0
+
+            if w <= 0 or h <= 0 or age <= 0:
+                raise ValueError
+
+            self.progress["value"] = 30
+
+            bmi = calculate_bmi(w, h)
+            self.progress["value"] = 60
+
+            risk_code = self.model.predict(bmi, age, gender)
+            label, icon = risk_label(risk_code)
+
+            self.progress["value"] = 100
+
+            self.result.config(
+                text=f"{icon} BMI: {bmi} | {label}",
+                font=("Segoe UI", 16, "bold")
+            )
+
+            self._update_chart(bmi)
+
+        except Exception:
+            messagebox.showerror(
+                "Invalid Input",
+                "Please enter valid numeric values."
+            )
+            self.progress["value"] = 0
+
+    # ---------------------- CHART ----------------------
+    def _update_chart(self, bmi):
+        self.ax.clear()
+        self.ax.bar(["Your BMI"], [bmi])
+        self.ax.axhline(18.5, linestyle="--")
+        self.ax.axhline(25, linestyle="--")
+        self.ax.axhline(30, linestyle="--")
+        self.ax.set_ylabel("BMI Value")
+        self.ax.set_title("BMI Classification Zones")
+        self.canvas.draw()
+
+    # ---------------------- RUN ----------------------
+    def run(self):
+        self.root.mainloop()
+
+
+# ---------------------- RUN ----------------------
+if __name__ == "__main__":
+    app = BMIPredictorApp()
+    app.run()