import numpy as np
import cv2

cap = cv2.VideoCapture('slow.flv')

# take first frame of the video
ret,frame = cap.read()

# setup initial location of window
r,h,c,w = 250,90,400,125  # simply hardcoded the values
track_window = (c,r,w,h)

# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]
hsv_roi =  cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)

# Setup the termination criteria, either 10 iteration or move by atleast 1 pt
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)

        # apply meanshift to get the new location
        ret, track_window = cv2.meanShift(dst, track_window, term_crit)

        # Draw it on image
        x,y,w,h = track_window
        img2 = cv2.rectangle(frame, (x,y), (x+w,y+h), 255,2)
        cv2.imshow('img2',img2)

        k = cv2.waitKey(60) & 0xff
        if k == 27:
            break
        else:
            cv2.imwrite(chr(k)+".jpg",img2)

    else:
        break

cv2.destroyAllWindows()
cap.release()

import numpy as np
import cv2

cap = cv2.VideoCapture('slow.flv')

# take first frame of the video
ret,frame = cap.read()

# setup initial location of window
r,h,c,w = 250,90,400,125  # simply hardcoded the values
track_window = (c,r,w,h)

# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]#需要使用Inteage类型
hsv_roi =  cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)

# Setup the termination criteria, either 10 iteration or move by atleast 1 pt
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)

        # apply meanshift to get the new location
        ret, track_window = cv2.CamShift(dst, track_window, term_crit)

        # Draw it on image
        pts = cv2.boxPoints(ret)
        pts = np.int0(pts)
        img2 = cv2.polylines(frame,[pts],True, 255,2)
        cv2.imshow('img2',img2)

        k = cv2.waitKey(60) & 0xff
        if k == 27:
            break
        else:
            cv2.imwrite(chr(k)+".jpg",img2)

    else:
        break

cv2.destroyAllWindows()
cap.release()

import numpy as np
import cv2
# local module
import video
class App(object):
def __init__(self, video_src):
    self.cam = video.create_capture(video_src)
    ret, self.frame = self.cam.read()
    cv2.namedWindow('camshift')
    cv2.setMouseCallback('camshift', self.onmouse)
    self.selection = None
    self.drag_start = None
    self.tracking_state = 0
    self.show_backproj = False
def onmouse(self, event, x, y, flags, param):
    x, y = np.int16([x, y])
    if event == cv2.EVENT_LBUTTONDOWN:
    self.drag_start = (x, y)
    self.tracking_state = 0
    # 官方示例中下面一行判断有问题，作如下修改就可以了
    if self.drag_start and event == cv2.EVENT_MOUSEMOVE:
    # print x,y
    if flags==cv2.EVENT_FLAG_LBUTTON:
    # print 'ok'
    h, w = self.frame.shape[:2]
    xo, yo = self.drag_start
    x0, y0 = np.maximum(0, np.minimum([xo, yo], [x, y]))
    x1, y1 = np.minimum([w, h], np.maximum([xo, yo], [x, y]))
    self.selection = None
    if x1-x0 > 0 and y1-y0 > 0:
    self.selection = (x0, y0, x1, y1)
    print self.selection
    else:
    self.drag_start = None
    if self.selection is not None:
    self.tracking_state = 1
def show_hist(self):
    bin_count = self.hist.shape[0]
    bin_w = 24