Object tracking with Mean-shift – OpenCV 3.4 with python 3 Tutorial 29
Source code:
[python]
import cv2
import numpy as np
video = cv2.VideoCapture("mouthwash.avi")
_, first_frame = video.read()
x = 300
y = 305
width = 100
height = 115
roi = first_frame[y: y + height, x: x + width]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
roi_hist = cv2.calcHist([hsv_roi], [0], None, [180], [0, 180])
roi_hist = cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)
term_criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)
while True:
_, frame = video.read()
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
_, track_window = cv2.meanShift(mask, (x, y, width, height), term_criteria)
x, y, w, h = track_window
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Mask", mask)
cv2.imshow("Frame", frame)
key = cv2.waitKey(60)
if key == 27:
break
video.release()
cv2.destroyAllWindows()
[/python]
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Opencv Beginner Tutorial
- 1) Loading images
- 2) Loading Video and Webcam
- 3) Drawing and writing on images
- 4) Basic operations on images
- 5) Add images and Threshold
- 6) Blending images
- 7) Bitwise Operators
- 8) Trackbars
- 9) Object detection using HSV Color space
- 10) Basic Thresholding
- 11) Histograms
- 12) Basic geometric transformations
- 13) Perspective transformation
- 14) Affine transformation
- 15) Adaptive thresholding5
- 16) Smoothing images
- 17) Morphological transformation
- 18) Edge detection
- 19) Find and Draw Contours
- 20) Template matching
- 21) Lines detection with Hough Transform
- 22) Corners detection
- 23) Image Pyramids
- 24) Image Pyramids (Blending and reconstruction)
- 25) Feature detection (SIFT, SURF, ORB)
- 26) Feature Matching (Brute-Force)
- 27) Mouse Events
- 28) Histogram and Back Projection
- 29) Object tracking with Mean-shift
- 30) Object tracking with Camshift
- 31) Optical Flow with Lucas-Kanade method
- 32) Background Subtraction
- 33) k-Nearest Neighbour classification
- 34) Object tracking using Homography
- 35) Fourier Transform
- 36) Knn handwritten digits recognition
- 37) Face detection using Haar Cascades
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problem in line 11
how to fix it