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()






