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我正在用樹莓派上的kinect進行物體跟蹤工作。 我混合2代碼,因爲我需要找到kinect幾乎對象,然後使用OpenCV過濾器設置灰色後,跟蹤灰色對象的過程! 但我不能!請幫我通過kinect在樹莓派上進行物體跟蹤
import freenect
import cv2
import numpy as np
"""
Grabs a depth map from the Kinect sensor and creates an image from it.
"""
def getDepthMap():
depth, timestamp = freenect.sync_get_depth()
np.clip(depth, 0, 2**10 - 1, depth)
depth >>= 2
depth = depth.astype(np.uint8)
return depth
while True:
depth = getDepthMap()
#text_file = codecs.open("log2.txt", "a","utf-8-sig")
#text_file.write(str(depth)+'\n')
depth = getDepthMap()
blur = cv2.GaussianBlur(depth, (5, 5), 0)
cv2.imshow('image', blur)
這個代碼可以告訴我在2 Color對象:黑白 黑色幾乎是--- 我想混這段代碼目標跟蹤。但是icant。
# find contours in the mask and initialize the current
# (x, y) center of the ball
cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)[-2]
center = None
# only proceed if at least one contour was found
if len(cnts) > 0:
# find the largest contour in the mask, then use
# it to compute the minimum enclosing circle and
# centroid
c = max(cnts, key=cv2.contourArea)
((x, y), radius) = cv2.minEnclosingCircle(c)
M = cv2.moments(c)
center = (int(M["m10"]/M["m00"]), int(M["m01"]/M["m00"]))
# only proceed if the radius meets a minimum size
if radius > 10:
# draw the circle and centroid on the frame,
# then update the list of tracked points
cv2.circle(frame, (int(x), int(y)), int(radius),
(0, 255, 255), 2)
cv2.circle(frame, center, 5, (0, 0, 255), -1)
# update the points queue
pts.appendleft(center)
http://www.pyimagesearch.com/2015/09/14/ball-tracking-with-opencv/