CVZone

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 cvzone

60 FPS Face Detection

import cvzone
import cv2

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

while True:
    success, img = cap.read()
    img, bboxs = detector.findFaces(img)
    print(bboxs)
    cv2.imshow("Image", img)
    cv2.waitKey(1)

Hand Tracking

Basic Code Example

import cvzone
import cv2

cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)
detector = cvzone.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)
    cv2.waitKey(1)

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 cvzone
import cv2

cap = cv2.VideoCapture(0)
detector = cvzone.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)
    cv2.waitKey(1)

Face Mesh Detection

import cvzone
import cv2

cap = cv2.VideoCapture(0)
detector = cvzone.FaceMeshDetector(maxFaces=2)
while True:
    success, img = cap.read()
    img, faces = detector.findFaceMesh(img)
    if faces:
        print(faces[0])
    cv2.imshow("Image", img)
    cv2.waitKey(1)

Stack Images

import cvzone
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 = cvzone.stackImages(imgList, 3, 0.4)

    cv2.imshow("stackedImg", stackedImg)
    cv2.waitKey(1)

Corner Rectangle

import cvzone
import cv2

cap = cv2.VideoCapture(0)
detector = cvzone.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 cvzone
import cv2

fpsReader = cvzone.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)