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MOTION DETECTION AND TRACKING USING OPENCV AND PYTHON

In this post, we are going to see how to detect and track movements(simply motion detection and tracking) using the OpenCV module. At first, you need to install the OpenCV-python module, to install the module just open your command prompt and type, pip install OpenCV-python Then hit enter, it will install the module automatically. After installing the module, just import the module and write the basic code to read the video. # import the opencv module import cv2 # capturing video capture = cv2.VideoCapture( "videos/input.mp4" ) After that, we have to get the two frames from the video or webcam and find the difference between the two frames, which is nothing but if there is a movement that occurs between the frames there might be a difference.  So, here we are trying to get the difference using the  cv2.absdiff() function in the OpenCV module and this method takes two parameters which are the two frames. # find difference between two frames diff = cv2.absdiff(img_1 , img_2) T
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BASIC HAND TRACKING USING PYTHON

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     Basically, the hand tracking is based on the 21 landmarks in 3D with multi-hand support, based on high-performance palm detection and hand landmark model. The 21 hand landmarks will be like,  And, The output will be like this,  Packages to install :  pip install opencv-python. pip install mediapipe. Program :  # Hand Tracking with python import cv2 import mediapipe as mp import time # Capturing video from the web cam video = cv2.VideoCapture( 0 ) # Creating objects for hands mpHands = mp.solutions.hands hands = mpHands.Hands() previousTime = 0 currentTime = 0 while True : success , img = video.read() # Converting BGR image to RGB image RGBimg = cv2.cvtColor(img , cv2.COLOR_BGR2RGB) # Getting landmark points and storing in multiHandLandmarks variable result = hands.process(RGBimg) multiHandLandmarks = result.multi_hand_landmarks # This 'if' block will run when it's having the handlandmark points if multiHandLandmarks: for handLand
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FACE DETECTION USING MEDIAPIPE AND PYTHON

Packages to install :  pip install opencv-python. pip install mediapipe. Program :  # Face Detection using mediapipe with python import cv2 import mediapipe as mp import time # Creating objects for detecting face mpFaceDetection = mp.solutions.face_detection mpDraw = mp.solutions.drawing_utils faceDetection = mpFaceDetection.FaceDetection() # Capturing video from the web cam video = cv2.VideoCapture( 0 ) currentTime = 0 previousTime = 0 while True : success , img = video.read() # Converting BGR image to RGB image RGBimg = cv2.cvtColor(img , cv2.COLOR_BGR2RGB) # Getting landmark points and storing in multiHandLandmarks variable result = faceDetection.process(RGBimg) # This 'if' block will run when it's having the face landmark points if result.detections: for index , detection in enumerate (result.detections): score = detection.score[ 0 ] * 100 boundingBox = detection.location_data.relative_bounding_box
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