Python ML Hand Gesture Control GUI 🖐 | Control PC with Gestures (No CV2/No Mediapipe)

 Demo :


Click Video 👇👇👇






























Features:

  • Hand gestures mapped to PC actions (Launch apps, Show desktop, Lock screen)

  • Modern GUI with Dark Mode

  • Works with ML model or Random Simulation


Code :


import customtkinter as ctk

import imageio

import threading

import numpy as np

import pyautogui

from PIL import Image, ImageTk

import tensorflow as tf

import os

import random


# ===== GUI Settings =====

ctk.set_appearance_mode("dark")

ctk.set_default_color_theme("blue")


class GestureApp(ctk.CTk):

    def __init__(self):

        super().__init__()

        self.title("Fuzzu ML Hand Gesture Control (No CV2/No Mediapipe)")

        self.geometry("500x500")

        self.resizable(False, False)


        # Camera

        self.camera = None

        self.gesture_enabled = False


        # Title

        self.label = ctk.CTkLabel(self, text="🖐 Hand Gesture Control",

                                  font=("Arial", 28, "bold"))

        self.label.pack(pady=15)


        # Video Area

        self.video_label = ctk.CTkLabel(self, text="")

        self.video_label.pack(pady=10)


        # Buttons

        self.toggle_btn = ctk.CTkButton(self, text="Enable Gesture Control",

                                        command=self.toggle_gesture,

                                        width=200, height=50, fg_color="green")

        self.toggle_btn.pack(pady=10)


        self.quit_btn = ctk.CTkButton(self, text="Exit App", command=self.destroy,

                                      width=200, height=40, fg_color="red")

        self.quit_btn.pack(pady=10)


        # Load Model (Optional: Replace with your gesture_model.h5)

        self.model = None

        if os.path.exists("gesture_model.h5"):

            self.model = tf.keras.models.load_model("gesture_model.h5")


    def toggle_gesture(self):

        if not self.gesture_enabled:

            self.gesture_enabled = True

            self.toggle_btn.configure(text="Disable Gesture Control", fg_color="orange")

            self.camera = imageio.get_reader("<video0>")  # default webcam

            threading.Thread(target=self.run_camera, daemon=True).start()

        else:

            self.gesture_enabled = False

            self.toggle_btn.configure(text="Enable Gesture Control", fg_color="green")

            if self.camera:

                self.camera.close()


    def run_camera(self):

        for frame in self.camera:

            if not self.gesture_enabled:

                break


            img = Image.fromarray(frame)

            imgtk = ImageTk.PhotoImage(image=img)

            self.video_label.imgtk = imgtk

            self.video_label.configure(image=imgtk)


            # Detect gesture (dummy / model-based)

            gesture = self.detect_gesture(frame)

            self.perform_action(gesture)


    def detect_gesture(self, frame):

        """ Replace this with real ML predictions """

        if self.model:

            resized = np.array(Image.fromarray(frame).resize((64, 64))) / 255.0

            prediction = np.argmax(self.model.predict(resized.reshape(1, 64, 64, 3)))

            gestures = ["OPEN_PALM", "ONE_FINGER", "TWO_FINGER", "FIST"]

            return gestures[prediction]

        else:

            # Random simulate if no model

            return random.choice(["OPEN_PALM", "ONE_FINGER", "TWO_FINGER", "FIST", None])


    def perform_action(self, gesture):

        if gesture == "OPEN_PALM":

            print("🖐 Open palm → Exit App")

            self.destroy()

        elif gesture == "ONE_FINGER":

            print("☝ One finger → Open Notepad")

            os.system("notepad.exe")

        elif gesture == "TWO_FINGER":

            print("✌ Two fingers → Show Desktop")

            pyautogui.hotkey('win', 'd')

        elif gesture == "FIST":

            print("✊ Fist → Lock Screen")

            pyautogui.hotkey('win', 'l')


if __name__ == "__main__":

    app = GestureApp()

    app.mainloop()

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