HandTrackingModule.py

import cv2
import mediapipe as mp
import time
import math


class handDetector:
    def __init__(self, mode=False, maxHands=2, modelComplexity=1, detectionCon=0.5, trackCon=0.5):
        self.mode = mode
        self.maxHands = maxHands
        self.modelComplex = modelComplexity
        self.detectionCon = detectionCon
        self.trackCon = trackCon

        self.mpHands = mp.solutions.hands
        self.hands = self.mpHands.Hands(static_image_mode=self.mode,
                                        max_num_hands=self.maxHands,
                                        model_complexity=self.modelComplex,
                                        min_detection_confidence=self.detectionCon,
                                        min_tracking_confidence=self.trackCon)
        self.mpDraw = mp.solutions.drawing_utils
        self.tipIds = [4, 8, 12, 16, 20]
        self.results = None
        self.lmList = []

    def findHands(self, img, draw=True):
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.hands.process(imgRGB)

        if self.results.multi_hand_landmarks:
            for handLms in self.results.multi_hand_landmarks:
                if draw:
                    self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS)
        return img

    def findPosition(self, img, handNo=0, draw=True):
        xList = []
        yList = []
        bbox = []
        self.lmList = []

        if self.results.multi_hand_landmarks:
            if len(self.results.multi_hand_landmarks) > handNo:
                myHand = self.results.multi_hand_landmarks[handNo]

                for id, lm in enumerate(myHand.landmark):
                    h, w, c = img.shape
                    cx, cy = int(lm.x * w), int(lm.y * h)
                    xList.append(cx)
                    yList.append(cy)
                    self.lmList.append([id, cx, cy])

                    if draw:
                        # Draw a circle for each landmark
                        cv2.circle(img, (cx, cy), 5, (255, 0, 255), cv2.FILLED)

                    # If the landmark is the thumb tip (id 4), draw a red dot
                    # if id == 4:
                    #     cv2.circle(img, (cx, cy), 15, (0, 0, 255), cv2.FILLED)  # Red dot on thumb tip

                if xList and yList:
                    xmin, xmax = min(xList), max(xList)
                    ymin, ymax = min(yList), max(yList)
                    bbox = xmin, ymin, xmax, ymax

                    if draw:
                        cv2.rectangle(img, (bbox[0] - 20, bbox[1] - 20),
                                      (bbox[2] + 20, bbox[3] + 20), (0, 255, 0), 2)

        return self.lmList, bbox

    def fingersUp(self):
        fingers = []
        if len(self.lmList) >= 21:  # Check if we have all landmarks
            # Thumb
            if self.lmList[self.tipIds[0]][1] > self.lmList[self.tipIds[0] - 1][1]:
                fingers.append(1)
            else:
                fingers.append(0)
            # 4 Fingers
            for id in range(1, 5):
                if self.lmList[self.tipIds[id]][2] < self.lmList[self.tipIds[id] - 2][2]:
                    fingers.append(1)
                else:
                    fingers.append(0)
        return fingers

    def findDistance(self, p1, p2, img, draw=True):
        if len(self.lmList) >= max(p1, p2):
            x1, y1 = self.lmList[p1][1], self.lmList[p1][2]
            x2, y2 = self.lmList[p2][1], self.lmList[p2][2]
            cx, cy = (x1 + x2) // 2, (y1 + y2) // 2

            if draw:
                cv2.circle(img, (x1, y1), 15, (255, 0, 255), cv2.FILLED)
                cv2.circle(img, (x2, y2), 15, (255, 0, 255), cv2.FILLED)
                cv2.line(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
                cv2.circle(img, (cx, cy), 15, (255, 0, 255), cv2.FILLED)

            length = math.hypot(x2 - x1, y2 - y1)
            return length, img, [x1, y1, x2, y2, cx, cy]
        return None


def main():
    pTime = 0
    cap = cv2.VideoCapture(0)  # Make sure to change index to 0 for default camera
    detector = handDetector()

    while True:
        success, img = cap.read()
        if not success:
            print("Ignoring empty frame from the webcam.")
            break

        img = detector.findHands(img)
        lmList, bbox = detector.findPosition(img)

        if len(lmList) != 0:
            print(lmList[4])  # Example of printing specific landmark positions

        # Calculate FPS
        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime

        # Display FPS on image
        cv2.putText(img, f'FPS: {int(fps)}', (10, 70), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)

        # Show the image
        cv2.imshow("Image", img)

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()


if __name__ == "__main__":
    main()