cvfiq

This is a Computer vision package that makes its easy to run Image processing and AI functions.

Installation

Before install cvfiq you must install opencv and mediapipe

pip install opencv-python pip install mediapipe

Then you can simply use pip to install the latest version of cvfiq.

pip install cvfiq

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60 FPS Face Detection

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from cvfiq.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()

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Hand Tracking

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Basic Code Example

from cvfiq.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()

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Pose Estimation

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from cvfiq.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()

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Face Mesh Detection

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from cvfiq.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()

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Stack Images

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

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

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FPS

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import cvfiq
import cv2

fpsReader = cvfiq.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()