OpenCVZone

This is a Computer vision package that makes its easy to run Image processing and AI functions. At the core it uses OpenCV and Mediapipe libraries.

Installation

You can simply use pip to install the latest version of cvzone.

pip install opencvzone

60 FPS Face Detection

import opencvzone
import cv2

cap = cv2.VideoCapture(0)
detector = opencvzone.FaceDetector()

while True:
    success, img = cap.read()
    img, bboxs = detector.findFaces(img)
    print(bboxs)
    cv2.imshow("Image", img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

Hand Tracking

Basic Code Example

import opencvzone
import cv2

cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)
detector = opencvzone.HandDetector(detectionCon=0.5, maxHands=1)

while True:
    # Get image frame
    success, img = cap.read()

    # Find the hand and its landmarks
    img = detector.findHands(img)
    lmList, bbox = detector.findPosition(img)
    
    # Display
    cv2.imshow("Image", img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

Finding How many finger are up

if lmList:
        # Find how many fingers are up
        fingers = detector.fingersUp()
        totalFingers = fingers.count(1)
        cv2.putText(img, f'Fingers:{totalFingers}', (bbox[0] + 200, bbox[1] - 30),
                    cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)

Finding distace between two fingers

                 
if lmList:
        # Find Distance Between Two Fingers
        distance, img, info = detector.findDistance(8, 12, img)
        cv2.putText(img, f'Dist:{int(distance)}', (bbox[0] + 400, bbox[1] - 30),
                    cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)

Find Hand Type - i.e. Left or Right

if lmList:
        # Find Hand Type
        myHandType = detector.handType()
        cv2.putText(img, f'Hand:{myHandType}', (bbox[0], bbox[1] - 30),
                    cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)

Pose Estimation

import opencvzone
import cv2

cap = cv2.VideoCapture(0)
detector = opencvzone.PoseDetector()
while True:
    success, img = cap.read()
    img = detector.findPose(img)
    lmList = detector.findPosition(img, draw=False)
    if lmList:
        print(lmList[14])
        cv2.circle(img, (lmList[14][1], lmList[14][2]), 15, (0, 0, 255), cv2.FILLED)

    cv2.imshow("Image", img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

Face Mesh Detection

import opencvzone
import cv2

cap = cv2.VideoCapture(0)
detector = opencvzone.FaceMeshDetector(maxFaces=2)
while True:
    success, img = cap.read()
    img, faces = detector.findFaceMesh(img)
    if faces:
        print(faces[0])
    cv2.imshow("Image", img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

Stack Images

import opencvzone
import cv2

cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)

while True:
    success, img = cap.read()
    imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    imgList = [img, img, imgGray, img, imgGray, img,imgGray, img, img]
    stackedImg = opencvzone.stackImages(imgList, 3, 0.4)

    cv2.imshow("stackedImg", stackedImg)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

Corner Rectangle

import opencvzone
import cv2

cap = cv2.VideoCapture(0)
detector = opencvzone.HandDetector()

while True:
    # Get image frame
    success, img = cap.read()

    # Find the hand and its landmarks
    img = detector.findHands(img, draw=False)
    lmList, bbox = detector.findPosition(img, draw=False)
    if bbox:
        # Draw  Corner Rectangle
        cvzone.cornerRect(img, bbox)

    # Display
    cv2.imshow("Image", img)
    cv2.waitKey(1)

FPS

import opencvzone
import cv2

fpsReader = opencvzone.FPS()
cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)

while True:
    success, img = cap.read()
    fps, img = fpsReader.update(img,pos=(50,80),color=(0,255,0),scale=5,thickness=5)
    cv2.imshow("Image", img)
    cv2.waitKey(1)

Gesture Volume Control

import opencvzone
import cv2
from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume

wCam, hCam = 640, 480

cap = cv2.VideoCapture(1)
cap.set(3, wCam)
cap.set(4, hCam)
pTime = 0

detector = opencvzone.HandDetector(detectionCon=0.5, maxHands=1)

devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))
volRange = volume.GetVolumeRange()
minVol = volRange[0]
maxVol = volRange[1]
vol = 0
volBar = 400
volPer = 0
area = 0
colorVol = (255, 0, 0)

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

    # Find Hand
    img = detector.findHands(img)
    lmList, bbox = detector.findPosition(img, draw=True)
    if len(lmList) != 0:

        # Filter based on size
        area = (bbox[2] - bbox[0]) * (bbox[3] - bbox[1]) // 100
        # print(area)
        if 250 < area < 1000:

            # Find Distance between index and Thumb
            length, img, lineInfo = detector.findDistance(4, 8, img)
            # print(length)

            # Convert Volume
            volBar = np.interp(length, [50, 200], [400, 150])
            volPer = np.interp(length, [50, 200], [0, 100])

            # Reduce Resolution to make it smoother
            smoothness = 10
            volPer = smoothness * round(volPer / smoothness)

            # Check fingers up
            fingers = detector.fingersUp()
            # print(fingers)

            # If pinky is down set volume
            if not fingers[4]:
                volume.SetMasterVolumeLevelScalar(volPer / 100, None)
                cv2.circle(img, (lineInfo[4], lineInfo[5]), 15, (0, 255, 0), cv2.FILLED)
                colorVol = (0, 255, 0)
            else:
                colorVol = (255, 0, 0)

    # Drawings
    cv2.rectangle(img, (50, 150), (85, 400), (255, 0, 0), 3)
    cv2.rectangle(img, (50, int(volBar)), (85, 400), (255, 0, 0), cv2.FILLED)
    cv2.putText(img, f'{int(volPer)} %', (40, 450), cv2.FONT_HERSHEY_COMPLEX,1, (255, 0, 0), 3)
    cVol = int(volume.GetMasterVolumeLevelScalar() * 100)
    cv2.putText(img, f'Vol Set: {int(cVol)}', (400, 50), cv2.FONT_HERSHEY_COMPLEX,1, colorVol, 3)

    # Frame rate
    cTime = time.time()
    fps = 1 / (cTime - pTime)
    pTime = cTime
    cv2.putText(img, f'FPS: {int(fps)}', (40, 50), cv2.FONT_HERSHEY_COMPLEX,1, (255, 0, 0), 3)

    cv2.imshow("Img", img)
    cv2.waitKey(1)