Metadata-Version: 2.1
Name: HandDetector-cc
Version: 0.0.9
Summary: A simple way to use Mediapipe hand features.
Home-page: https://github.com/Chexa12cc/HandDetector-cc
Author: Chanchal Roy
Author-email: croy7667@gmail.com
Maintainer: Chanchal Roy
Maintainer-email: croy7667@gmail.com
License: MIT
Project-URL: Bug Tracker, https://github.com/Chexa12cc/HandDetector-cc/issues
Keywords: Hand Detection,Opencv,Hand Recognition,Mediapipe
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: opencv-contrib-python (==4.6.0.66)
Requires-Dist: mediapipe (==0.8.11)
Requires-Dist: termcolor (==2.0.1)


# HandDetector-cc Module

Simple python package to simply use mediapipe hand detection.


## Author Details

#### Name : [Chanchal Roy](https://github.com/Chexa12cc)
#### Email : [croy7667@gmail.com](https://mail.google.com/mail/u/0/#inbox?compose=GTvVlcSKjDXfbgxPqzlHGlKdhgKgDfbxZMfwLWHzBDlSCTsRdSrZxkGcgLHSwmlbGpKmVPcLfKxWQ)


## GitHub Project Details

#### Project : [HandDetector-cc](https://github.com/Chexa12cc/HandDetector-cc)


## Installation

Install HandDetector-cc with pip

```bash
  pip install HandDetector-cc
```


## Usage

```python
import HandDec
import time

timeS = time.time()

    class_obj = HandDetector()
    cam = class_obj.init_cam()

    while cam.isOpened():
        success, image = cam.read()
        if not success: continue

        detected_hand = class_obj.findHand(image, draw_detect=True)
        hand_landmark = class_obj.findLocations(image, draw_id=8)

        if hand_landmark[0] and hand_landmark[1]:

            finger_ups = class_obj.fingerUp()

            boundry = hand_landmark[1]
            cv2.rectangle(image, (boundry[0], boundry[1]), (boundry[2], boundry[3]), (0, 255, 255), 2)

            distance = class_obj.findDistance(image, 8, 12)
            print(f"Finger's Up : {finger_ups}       Finger Distance : {distance}")

        timeE = time.time()
        fps = int(1 / (timeE - timeS))
        timeS = timeE
        cv2.putText(image, str(f'FPS : {fps}'), (10, 30), 4, 1, (0, 255, 255), 3)
        cv2.imshow('Hand Detection - Chanchal Roy', image)
        if cv2.waitKey(1) & 0xff == ord('q'): break

    cam.release()
    cv2.destroyAllWindows()
```
