cvlearn 0.5.3

Coumputer Vision helping Library

CVLearn

An easy-to-use package that helps with hand tracking, face detection, and more using OpenCV and Mediapipe.

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Features

Core Features

• Hand Tracking - Real-time hand pose detection and tracking
• Face Detection - Multi-face detection and bounding boxes
• Face Mesh - Detailed facial landmarks
• Finger Counting - Single and dual-hand finger detection
• Pose Detection - Full body pose estimation
• Gesture Recognition - Gesture recognition with combo detection and velocity-based gestures

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Installation

• Use Python 3.6+
• Open your terminal or command prompt and run:

pip install cvlearn

Install Dependencies (if needed)

pip install mediapipe opencv-python numpy

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:

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Face Detection

from cvlearn import FaceDetection 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:

Side View:

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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:

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

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

cv2.destroyAllWindows()

Result:

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Two Hands Finger Counting

from cvlearn import TwoHandsFingerCounter as fc
import cv2

cap = cv2.VideoCapture(0)
counter = fc.FingerCounter()

while True:
    ret, frame = cap.read()
    frame = counter.drawCountedFingers(frame)

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

cv2.destroyAllWindows()

Result:

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Pose Detection

import cv2
import cvlearn
from cvlearn import PoseDetector, Utils

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Gesture Recognition

import cv2
from cvlearn import GestureRecognizer

cap = cv2.VideoCapture(0)
detector = GestureRecognizer(maxHands=2)

while True:
    ret, frame = cap.read()
    frame = detector.findHands(frame)

    gesture, confidence = detector.recognizeGesture(frame)
    frame = detector.drawGestureInfo(frame, gesture, confidence)

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

cv2.destroyAllWindows()