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.
You can simply use pip to install the latest version of cvzone.
pip install cvzone
from cvzone.FaceDetectionModule import FaceDetector import cv2 cap = cv2.VideoCapture(0) detector = FaceDetector() while True: success, img = cap.read() img, bboxs = detector.findFaces(img) if bboxs: # bboxInfo - "id","bbox","score","center" center = bboxs[0]["center"] cv2.circle(img, center, 5, (255, 0, 255), cv2.FILLED) cv2.imshow("Image", img) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
from cvzone.HandTrackingModule import HandDetector import cv2 cap = cv2.VideoCapture(0) detector = HandDetector(detectionCon=0.8, maxHands=2) while True: # Get image frame success, img = cap.read() # Find the hand and its landmarks hands, img = detector.findHands(img) # with draw # hands = detector.findHands(img, draw=False) # without draw if hands: # Hand 1 hand1 = hands[0] lmList1 = hand1["lmList"] # List of 21 Landmark points bbox1 = hand1["bbox"] # Bounding box info x,y,w,h centerPoint1 = hand1['center'] # center of the hand cx,cy handType1 = hand1["type"] # Handtype Left or Right fingers1 = detector.fingersUp(hand1) if len(hands) == 2: # Hand 2 hand2 = hands[1] lmList2 = hand2["lmList"] # List of 21 Landmark points bbox2 = hand2["bbox"] # Bounding box info x,y,w,h centerPoint2 = hand2['center'] # center of the hand cx,cy handType2 = hand2["type"] # Hand Type "Left" or "Right" fingers2 = detector.fingersUp(hand2) # Find Distance between two Landmarks. Could be same hand or different hands length, info, img = detector.findDistance(lmList1[8], lmList2[8], img) # with draw # length, info = detector.findDistance(lmList1[8], lmList2[8]) # with draw # Display cv2.imshow("Image", img) cv2.waitKey(1) cap.release() cv2.destroyAllWindows()
from cvzone.PoseModule import PoseDetector import cv2 cap = cv2.VideoCapture(0) detector = PoseDetector() while True: success, img = cap.read() img = detector.findPose(img) lmList, bboxInfo = detector.findPosition(img, bboxWithHands=False) if bboxInfo: center = bboxInfo["center"] cv2.circle(img, center, 5, (255, 0, 255), cv2.FILLED) cv2.imshow("Image", img) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
from cvzone.FaceMeshModule import FaceMeshDetector import cv2 cap = cv2.VideoCapture(0) detector = 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()
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) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
import cvzone from cvzone.HandTrackingModule import HandDetector import cv2 cap = cv2.VideoCapture(0) detector = 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) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
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) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()