I am trying to use mediapipe for hands detection and it is not working. Plus I am new to Python

Question

INFO : Created TensorFlow Lite XNNPACK delegate for CPU

It is not detecting the hands or doing anything, only the camera is opening.

Code :

import cv2
import mediapipe as mp

cap = cv2.VideoCapture(0)

mp_hands = mp.solutions.hands
mp_drawing = mp.solutions.drawing_utils

hands = mp_hands.Hands(min_detection_confidence=0.8, min_tracking_confidence=0.5)

tipIds = [4, 8, 12, 16, 20]

def countFingers(image, hand_landmarks, handNo=0):
    
    if hand_landmarks:
        # Get all Landmarks of the FIRST Hand VISIBLE
        landmarks = hand_landmarks[handNo].landmark
        # print(landmarks)

        # Count Fingers        
        fingers = []

        for lm_index in tipIds:
                # Get Finger Tip and Bottom y Position Value
                finger_tip_y = landmarks[lm_index].y 
                finger_bottom_y = landmarks[lm_index - 2].y

                # Check if ANY FINGER is OPEN or CLOSED
                if lm_index !=4:
                    if finger_tip_y < finger_bottom_y:
                        fingers.append(1)
                        print("FINGER with id ",lm_index," is Open")

                    if finger_tip_y > finger_bottom_y:
                        fingers.append(0)
                        print("FINGER with id ",lm_index," is Closed")

        # print(fingers)
        totalFingers = fingers.count(1)

        # Display Text
        text = f'Fingers: {totalFingers}'

        cv2.putText(image, text, (50,50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2)
 
def drawHandLanmarks(image, hand_landmarks):

    # Darw connections between landmark points
    if hand_landmarks:

      for landmarks in hand_landmarks:
               
        mp_drawing.draw_landmarks(image, landmarks, mp_hands.HAND_CONNECTIONS)


while True:
    success, image = cap.read()

    image = cv2.flip(image, 1)
    
    # Detect the Hands Landmarks 
    results = hands.process(image)

    # Get landmark position from the processed result
    hand_landmarks = results.multi_hand_landmarks

    # Draw Landmarks
    drawHandLanmarks(image, hand_landmarks)

    # Get Hand Fingers Position        
    countFingers(image, hand_landmarks)

    cv2.imshow("Media Controller", image)

    
    key = cv2.waitKey(1)
    if key == 32:
        break

cv2.destroyAllWindows()

ERROR/Warning : INFO: Created TensorFlow Lite XNNPACK delegate for CPU.

Answer 1

Looking over the code you posted, here are a few things you could do.

1. You misspelt "drawHandLandmarks()" in its definition.
2. When using "cv2.VideoCapture()", before running anything use "cap.isOpened()" instead of "while True:".
3. hands.process() requires an image in RGB format, meanwhile "cap.read()" outputs BGR.
4. Sometimes updating opencv-python resolves errors with cv2.VideoCapture(0).
5. use a guard clause to prevent empty images from causing issues.

import cv2
import mediapipe as mp

cap = cv2.VideoCapture(0)
mp_hands = mp.solutions.hands
mp_drawing = mp.solutions.drawing_utils

hands = mp_hands.Hands(min_detection_confidence=0.8, min_tracking_confidence=0.5)

tipIds = [4, 8, 12, 16, 20]


def countFingers(image, hand_landmarks, handNo=0):
    if hand_landmarks:
        # Get all Landmarks of the FIRST Hand VISIBLE
        landmarks = hand_landmarks[handNo].landmark
        # print(landmarks)

        # Count Fingers
        fingers = []

        for lm_index in tipIds:
            # Get Finger Tip and Bottom y Position Value
            finger_tip_y = landmarks[lm_index].y
            finger_bottom_y = landmarks[lm_index - 2].y

            # Check if ANY FINGER is OPEN or CLOSED
            if lm_index != 4:
                if finger_tip_y < finger_bottom_y:
                    fingers.append(1)
                    print("FINGER with id ", lm_index, " is Open")

                if finger_tip_y > finger_bottom_y:
                    fingers.append(0)
                    print("FINGER with id ", lm_index, " is Closed")

        # print(fingers)
        totalFingers = fingers.count(1)

        # Display Text
        text = f"Fingers: {totalFingers}"

        cv2.putText(image, text, (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)


def drawHandLandmarks(image, hand_landmarks):
    # Darw connections between landmark points
    if hand_landmarks:
        for landmarks in hand_landmarks:
            mp_drawing.draw_landmarks(image, landmarks, mp_hands.HAND_CONNECTIONS)



# use cap.isOpened() insted of while True
while cap.isOpened():
    success, image = cap.read()

    # some cameras take a couple seconds to show show any images. This prevents empty images from causing errors
    if not success or image is None:
        continue

    image = cv2.flip(image, 1)
    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    # Detect the Hands Landmarks
    results = hands.process(image_rgb)

    # Get landmark position from the processed result
    hand_landmarks = results.multi_hand_landmarks

    # Draw Landmarks
    drawHandLandmarks(image, hand_landmarks)

    # Get Hand Fingers Position
    countFingers(image, hand_landmarks)

    cv2.imshow("Media Controller", image)

    #cleaner way to exit out of the loop
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

cap.release()
cv2.destroyAllWindows()