Skip to main content

About

It is a package having pre-built codes of Hand Tracking. You can implement with just single line of code.

Function

handTracker(image,draw=True)

  • Function Parameter : This function takes image (a single frame) as input and a variable draw with default value False. You can change the value of parameter draw to True if you want to the mapping of hands over the image frame.
  • Output : This function returns a nested list of length 2. The element at index 1 is the frame and a list of handLandmarks. Know more about these handLandmarks on this link. The list of handLandmarks consist of 21 lists containing data of all 21 points. Each list is in the format of [indexOfPoint, xCoordinate, yCoordinate, zCoordinate] for all 21 points. NOTE that the function will return [0] at index 1 in the list if no hands are detected.

Usage

handTracker(image,draw=False)

Mapping over the hands directly from function.


from lkhandmapping import handTracker
import cv2

cap = cv2.VideoCapture(0)
while True:
    success, image = cap.read()
    functionValues = handTracker(image,draw=True)
    image = functionValues[0]
    handLms = functionValues[1]
    print(handLms)
    cv2.imshow('Hands', image)
    cv2.waitKey(1)
cap.release()

Track hands without mapping.


from lkhandmapping import handTracker
import cv2
    
cap = cv2.VideoCapture(0)
while True:
    success, image = cap.read()
    functionValues = handTracker(image,draw=False)
    image = functionValues[0]
    handLms = functionValues[1]
    print(handLms)
    cv2.imshow('Hands', image)
    cv2.waitKey(1)
cap.release()

Developer

This package is developed by Lakshay Kumar an enthusiastic AI Researcher. This is developed keeping in mind the pain to write lengthy lines of code just to detect faces. This will enable other developers to focus more on implementation part rather than spending time on coding the face detection module.
Feel free to share your feedback via mail

Metadata

Release files for lkhandmapping 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for lkhandmapping 0.1.2
File Interpreter ABI Platform Actions
lkhandmapping-0.1.2-py3-none-any.whl Python 3 none any Details for lkhandmapping-0.1.2-py3-none-any.whl

Release files / lkhandmapping-0.1.2-py3-none-any.whl

Download URL lkhandmapping-0.1.2-py3-none-any.whl
Size 3.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
79745b05adc971f34212d0ed4807d4755d79ff30973e34930dc62b4eab0d624b
BLAKE2b-256 checksum
How to use checksums
911931ac95b37cbde2586183404118eb49170e8ab838759235be8db10c8f8668
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.10.2

Security for lkhandmapping 0.1.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page