CAMShift_OpenCV_Python

最新推荐文章于 2023-09-20 20:56:08 发布

Leyooo

最新推荐文章于 2023-09-20 20:56:08 发布

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分类专栏： Python_OpenCV 文章标签： Python OpenCV

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本文介绍了一种使用Python和OpenCV库实现的目标跟踪方法。通过从摄像头捕获视频帧并应用颜色直方图来初始化感兴趣区域（ROI），然后利用CamShift算法在后续帧中持续跟踪该目标。此过程涉及HSV颜色空间的转换、掩膜创建、直方图计算及归一化等关键步骤。

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Reference to 《learning opencv3 computer vision with python》

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
# take first frame of the video
ret, frame = cap.read()
# setup initial location of window
r, h, c, w = 300, 200, 400, 300
track_window = (c, r, w, h)
roi = frame[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((100., 30, 32.)),
np.array((180., 120, 255.)))
roi_hist = cv2.calcHist([hsv_roi], [0], mask, [180], [0, 180])
cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)
while(1):
    ret, frame = cap.read()
    if ret == True:
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
        ret, track_window = cv2.CamShift(dst, track_window, term_crit)
        pts = cv2.boxPoints(ret)
        pts = np.int0(pts)
        img2 = cv2.polylines(frame, [pts], True, 255, 2)
        cv2.imshow('Capture', img2)
        k = cv2.waitKey(60) & 0xff
        if k == 27:
            break
    else:
        break
cv2.destroyAllWindows()
cap.release()