cvlearn 0.0.5

Coumputer Vision helping Library

cvlearn

An easy to use package which helps to do hand tracking, face detection, etc. with use of opencv module.

Installation

• Use Python 3.x
• Open cmd/terminal and type:

pip install cvlearn

Dependencies

• python 3.x
• opencv-python
• numpy
• mediapipe

Examples

Hand Tracking:

from cvlearn import HandTrackingModule as handTracker

import cv2
cap = cv2.VideoCapture(0)
detector = handTracker.handDetector()
while True:
    ret, img = cap.read()
    img = detector.findHands(img)

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

Result:

Face Detection:

from cvlearn import FaceDetector as faceDetector

import cv2
cap = cv2.VideoCapture(0)
detector = faceDetector.FaceDetector()
while True:
    ret, img = cap.read()
    img = detector.findFaces(img)

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

Result:

SideView:

Drawing face mesh:

from cvlearn import FaceMesh as fms

import cv2
cap = cv2.VideoCapture(0)
detector = fms.FaceMeshDetector()
while True:
    ret, img = cap.read()
    img, face = detector.findFaceMesh(img)

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

Result:

Finger Counting

from cvlearn import FingerCounter as fc
import cvlearn.HandTrackingModule as handTracker
import cv2

cap = cv2.VideoCapture(0)

detector = handTracker.handDetector(maxHands=1)

counter = fc.FingerCounter()
while True:
    ret, frame = cap.read()
    frame = cv2.flip(frame, 180)

    frame = detector.findHands(frame)
    lmList, bbox = detector.findPosition(frame)

    if lmList:
        frame1 = counter.drawCountedFingers(frame, lmList, bbox)

    cv2.imshow("res", frame)
    key = cv2.waitKey(1)
    if key == 27:
        break

cv2.destroyAllWindows()

Result: