Holistic Detection OpenCV Python With Source Code
The Holistic Detection OpenCV Python was developed using Python OpenCV, This Python OpenCV Project With Source Code we are going to do HOLISTIC DETECTION with MediaPipe and OpenCV in Python. We are going to see the results from the pose and holistic that we have detected in real time camera.
A OpenCV Python Holistic Detection We are going to detect left and right hand, face mesh, and pose detection. MediaPipe has a lot of built-in customizable Machine Learning Solutions. MediaPipe is the newest and fastest within machine learning solutions and can be run on common hardware which we are going to see throughout this article.
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.
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.
By the way if you are new to python programming and you don’t know what would be the the Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS that will suit for you. I also have here How to Download and Install Latest Version of Python on Windows.
To start executing Holistic Detection OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Holistic 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 Holistic 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 cv2 import mediapipe as mp
Complete Source Code
import cv2 import mediapipe as mp cap = cv2.VideoCapture(0) mpHolistic = mp.solutions.holistic holistic = mpHolistic.Holistic() mpDraw = mp.solutions.drawing_utils drawing_specs = mpDraw.DrawingSpec(thickness=1,circle_radius=1) while True: success,img = cap.read() if not success: break imgRGB = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) results = holistic.process(imgRGB) mpDraw.draw_landmarks(img,results.face_landmarks,mpHolistic.FACE_CONNECTIONS,drawing_specs,drawing_specs) mpDraw.draw_landmarks(img,results.left_hand_landmarks,mpHolistic.HAND_CONNECTIONS,drawing_specs,drawing_specs) mpDraw.draw_landmarks(img,results.right_hand_landmarks,mpHolistic.HAND_CONNECTIONS,drawing_specs,drawing_specs) mpDraw.draw_landmarks(img,results.pose_landmarks,mpHolistic.POSE_CONNECTIONS,drawing_specs,drawing_specs) cv2.imshow('Image',img) if cv2.waitKey(1) & 0xff==ord('q'): break
Holistic Detection OpenCV Python: Project Information
|Project Name:||Holistic Detection OpenCV Python|
|Language/s Used:||Python OpenCV|
|Python version (Recommended):||3.8 3.9|
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Anyway, if you want to level up your programming knowledge, especially Python OpenCV, try this new article I’ve made for you Best OpenCV Projects With Source Code For Beginners 2021.
In this Article Holistic Detection, Live perception of simultaneous human pose, face landmarks, and hand tracking in real-time can enable various modern life applications: fitness and sport analysis, gesture control and sign language recognition, augmented reality try-on and effects. It generate a total of 543 landmarks (33 pose landmarks, 468 face landmarks, and 21 hand landmarks per hand).
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