Hand Landmark Detection OpenCV Python With Source Code
The Hand Landmark Detection OpenCV Python was developed using Python OpenCV, In this Python Project With Source Code we are going to learn how to obtain hand landmarks from an web cam, using Python, MediaPipe and OpenCV.
Watch the video here to see the full demonstration of the Hand Landmark OpenCV Python
What is OpenCV?
OpenCV is short for Open Source Computer Vision. Intuitively by the name, it is an open-source Computer Vision and Machine Learning library. This library is capable of processing real-time image and video while also boasting analytical capabilities. It supports the Deep Learning frameworks.
A OpenCV Python Hand Landmark Detection, We will be using OpenCV to read the image and displaying it and MediaPipe to perform the hand detection and landmark estimation. In short, MediaPipe is a free and open-source framework that offers cross-platform, customizable Machine Learning solutions for live and streaming media.
In This Python OpenCV Project also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.
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To start executing Hand Landmark Detection OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Hand Landmark Detection OpenCV Python With Source Code : Steps on how to run the project
Time needed: 5 minutes.
These are the steps on how to run Hand Landmark Detection OpenCV Python With Source Code
- Step 1: Download the given source code below.
First, download the given source code below and unzip the source code.
- Step 2: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
- Step 3: Run the project.
last, run the project with the command “py main.py”
import mediapipe as mp
Complete Source Code
import mediapipe as mp
cap = cv2.VideoCapture(0)
mpHands = mp.solutions.hands
hands = mpHands.Hands()
mpDraw = mp.solutions.drawing_utils
success,img = cap.read()
imgRGB = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
results = hands.process(imgRGB)
for handlandmark in results.multi_hand_landmarks:
for id,lm in enumerate(handlandmark.landmark):
print(id,lm) # lm produce output in ratio format
h,w,_ = img.shape
cx,cy = int(lm.x*w),int(lm.y*h)
if cv2.waitKey(1) & 0xff==ord('q'):
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Download Source Code below
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Hand detection is the process of finding the joints on the fingers as well as the finger-tips in a given image. It is similar to finding keypoints on Face or Body. but, different from Hand Detection since in that case, we treat the whole hand as one object.
In this Python OpenCV Project also includes a downloadable Python Project With Source Code for free.
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