hand-detection/app2.py

from flask import Flask, render_template, Response , request, jsonify, send_file
import cv2
import mediapipe as mp
import numpy as np
import json
import os

app = Flask(__name__,
            static_folder='assets',
            template_folder='templates'
            )


# Load JSON file
with open('dataset.json', 'r') as f:
    all_data = json.load(f)

the_image_path = "gambar/tutorial.jpg"
the_name = None
the_keterangan = "Posisikan satu tangan kepada menunjuk dan tangan lainnya kepada terbuka dan tunjukkan ke arah titik tangan"

# Initialize MediaPipe hand detection
mp_hands = mp.solutions.hands
hands = mp_hands.Hands(static_image_mode=False, max_num_hands=2, min_detection_confidence=0.7, min_tracking_confidence=0.7)

# Initialize MediaPipe drawing utilities
mp_drawing = mp.solutions.drawing_utils

# Initialize camera capture
cap = cv2.VideoCapture(0)

# Landmark names
landmark_names = [str(landmark) for landmark in mp_hands.HandLandmark]


def generate_frames(stat):
    global the_image_path, the_name, the_keterangan
    while True:
        # Read frame from camera
        ret, frame = cap.read()

        if not ret:
            break

        # Convert frame to RGB for MediaPipe
        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

        # Detect hand landmarks with MediaPipe
        results = hands.process(frame_rgb)

        pointing_hand = []
        open_palm = []

        if results.multi_hand_landmarks:
            for idx, hand_landmarks in enumerate(results.multi_hand_landmarks):
                landmarks = hand_landmarks.landmark

                # Check for gestures
                gesture = None
                if is_pointing_gesture(landmarks):
                    gesture = "Pointing"
                    # check the idx of the hand
                    pointing_hand = hand_landmarks.landmark
                else:
                    gesture = "Open Palm"
                    open_palm = hand_landmarks.landmark

                if gesture:
                    # Get the coordinates for the wrist landmark to place the text above the hand
                    wrist = landmarks[mp_hands.HandLandmark.WRIST]
                    h, w, _ = frame.shape
                    cx, cy = int(wrist.x * w), int(wrist.y * h)

                    # Add text annotation to the frame
                    cv2.putText(frame, gesture, (cx, cy - 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2,
                                cv2.LINE_AA)

                    if gesture == "Pointing":
                        if open_palm:
                            finger_tip = pointing_hand[mp_hands.HandLandmark.INDEX_FINGER_TIP]

                            distances = [np.sqrt((landmark.x - finger_tip.x) ** 2 +
                                                 (landmark.y - finger_tip.y) ** 2) for landmark in open_palm]

                            if distances:
                                closest_landmark_idx = np.argmin(distances)
                                # print("ini index", closest_landmark_idx)

                                the_image_path = all_data[closest_landmark_idx]["image_path"]
                                the_name = all_data[closest_landmark_idx]["name"]
                                the_keterangan = all_data[closest_landmark_idx]["keterangan"]
                                closest_landmark_name = landmark_names[closest_landmark_idx]
                                cv2.putText(frame, f'Closest Landmark: {closest_landmark_name}',
                                            (int(finger_tip.x * w), int(finger_tip.y * h)),
                                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
                        else:
                            the_image_path = "gambar/tutorial.jpg"
                            the_name = None
                            the_keterangan = "Posisikan satu tangan kepada menunjuk dan tangan lainnya kepada terbuka dan tunjukkan ke arah titik tangan"
                            cv2.putText(frame, 'No open palm detected', (cx, cy - 50), cv2.FONT_HERSHEY_SIMPLEX, 1,
                                        (0, 0, 255), 2, cv2.LINE_AA)
                            

                # Draw landmarks on the frame
                mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
        else:
            the_image_path = "gambar/tutorial.jpg"
            the_name = None
            the_keterangan = "Posisikan satu tangan kepada menunjuk dan tangan lainnya kepada terbuka dan tunjukkan ke arah titik tangan"

        # Convert the frame to bytes
        ret, buffer = cv2.imencode('.jpg', frame)
        frame = buffer.tobytes()

        if stat == 'camera':
            yield (b'--frame\r\n'
                b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')


@app.route('/')
def index():
    return render_template('index2.html')


@app.route('/video_feed')
def video_feed():
    stat = request.args.get('stat','camera')
    return Response(generate_frames(stat), mimetype='multipart/x-mixed-replace; boundary=frame')


@app.route('/get_data', methods=['GET'])
def get_data():
    global the_image_path, the_name, the_keterangan
    if the_image_path and the_name and the_keterangan:
        return jsonify({"name": the_name, "keterangan": the_keterangan, "image_path": the_image_path})
    else: 
        # just return empty
        return jsonify({}) 

@app.route('/show_image')
def show_image():
    image_path = request.args.get('image_path')
    if image_path and os.path.exists(image_path):
        return send_file(image_path, mimetype='image/jpeg')
    else:
        return "Image not found", 404


def is_pointing_gesture(landmarks):
    # Index finger tip and other joints
    index_tip = landmarks[mp_hands.HandLandmark.INDEX_FINGER_TIP]
    index_dip = landmarks[mp_hands.HandLandmark.INDEX_FINGER_DIP]
    index_pip = landmarks[mp_hands.HandLandmark.INDEX_FINGER_PIP]
    index_mcp = landmarks[mp_hands.HandLandmark.INDEX_FINGER_MCP]

    # Check if the index finger is extended
    index_extended = (index_tip.y < index_dip.y < index_pip.y < index_mcp.y)

    # Check if other fingers are bent
    other_fingers_bent = True
    for finger_tip, finger_pip in [
        (mp_hands.HandLandmark.MIDDLE_FINGER_TIP, mp_hands.HandLandmark.MIDDLE_FINGER_PIP),
        (mp_hands.HandLandmark.RING_FINGER_TIP, mp_hands.HandLandmark.RING_FINGER_PIP),
        (mp_hands.HandLandmark.PINKY_TIP, mp_hands.HandLandmark.PINKY_PIP)]:
        if landmarks[finger_tip].y < landmarks[finger_pip].y:
            other_fingers_bent = False

    if other_fingers_bent is False:
        return True

    return False


if __name__ == '__main__':
    app.run(debug=True)