How I Built a Real-Time Face Detector in Python Without TensorFlow or Mediapipe

 Demo :


Click Video 👇👇👇
















📢 Features:

  • Embed YouTube Short

  • Include GitHub link (if public)

  • Short write-up: Explain core logic and how Haar Cascade works

  • SEO Tip: Use keywords like “Python face detection 2025”, “OpenCV tutorial real time”


Code :


import cv2

import tkinter as tk

from tkinter import Label

from PIL import Image, ImageTk


# Haarcascade XML for face detection

face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")


# Initialize webcam

cap = cv2.VideoCapture(0)


# Create GUI Window

root = tk.Tk()

root.title("Modern Face Detector - FuzzuTech")

root.geometry("700x550")

root.configure(bg="#1e1e1e")


label = Label(root)

label.pack()


title = Label(root, text="Face Detector - No TensorFlow / Mediapipe", font=("Helvetica", 18), fg="white", bg="#1e1e1e")

title.pack(pady=10)


def detect_face():

    ret, frame = cap.read()

    if not ret:

        return


    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5)


    for (x, y, w, h) in faces:

        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)


    rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    img = Image.fromarray(rgb_frame)

    imgtk = ImageTk.PhotoImage(image=img)

    label.imgtk = imgtk

    label.configure(image=imgtk)

    label.after(10, detect_face)


detect_face()

root.mainloop()


# Release webcam after window closes

cap.release()

cv2.destroyAllWindows()

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