Human Pose Estimation OpenCV Python With Source Code
This 2022 Human Pose Estimation OpenCV Python was developed using Python OpenCV, In this Python Project With Source Code, Deep Learning based Python Project using OpenCV. In this article, we will focus on human pose estimation, where it is required to detect and localize the major parts/joints of the body ( e.g. shoulders, ankle, knee, wrist etc. ).
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 Human Pose is a general problem in Computer Vision where we detect the position and orientation of an object. This usually means detecting keypoint locations that describe the object.
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 Human Pose Estimation OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.
Human Pose Estimation OpenCV Python With Source Code : Steps on how to run the project
Time needed: 5 minutes
These are the steps on how to run Human Pose Estimation 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) mpPose = mp.solutions.pose pose = mpPose.Pose() mpDraw = mp.solutions.drawing_utils while True: success,img = cap.read() if not success: break imgRGB = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) results = pose.process(imgRGB) mpDraw.draw_landmarks(img,results.pose_landmarks,mpPose.POSE_CONNECTIONS) cv2.imshow('Image',img) if cv2.waitKey(1) & 0xff==ord('q'): break
Download Source Code below
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This Project is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years.
In this Python OpenCV Project also includes a downloadable Python Project With Source Code for free.
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