Computer Vision : Hand Detection using Python with Source code

When it comes to data visualization and computer vision, Python is the best-used programming of all. Python provides libraries like Open CV and Mediapipe which are pretty easy to use for computer vision. In this tutorial, we will develop a program using Python that can detect hands as shown in the picture below.

Let's unpack libraries.

Open CV

OpenCV is a library of programming functions mainly aimed at real-time computer vision. It was originally developed by Intel and later supported by Willow Garage then Itseez. The library is cross-platform and free for use under the open-source Apache 2 License.

Mediapipe

Mediapipe is a cross-platform library developed by Google that provides amazing ready-to-use ML solutions for computer vision tasks.

Source Code

import cv2
import mediapipe as mp 
import time

cap = cv2.VideoCapture(0)

mpHands = mp.solutions.hands
hands = mpHands.Hands()
mpDraw = mp.solutions.drawing_utils

pTime = 0
cTime = 0

while True:
	success, img = cap.read()
	imgRBG = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
	results = hands.process(imgRBG)
	print(results.multi_hand_landmarks)

	if results.multi_hand_landmarks:
		for handLms in results.multi_hand_landmarks:
			for id, lm in enumerate(handLms.landmark):
				# print(id,lm)
				h, w, c = img.shape
				cx, cy = (int(lm.x * w), int(lm.y * h))
				print(id, cx, cy)
				if id == 0:
					cv2.circle(img, (cx,cy), 15, (255,0,255), cv2.FILLED)
			mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)


	cTime = time.time()
	fps = 1/(cTime-pTime)
	pTime = cTime

	cv2.putText(img,str(int(fps)),(10,70),cv2.FONT_HERSHEY_PLAIN,3,(255,0,255),3)

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

You can view and get the source code in GitHub from here.

Source Code