Kinect在Raspberry Pi上进行对象跟踪 [英] Object tracking by kinect on raspberry pi
问题描述
我正在用树莓派上的kinect进行对象跟踪. 我混合使用2个代码,因为我需要用kinect查找几乎对象,然后在跟踪灰色对象的过程之后使用OpenCV滤镜设置灰色! 但是我不能!请帮助我
I m working on object tracking with kinect on a raspberry pi. I mix 2 code because I need to find nearly object with kinect and then use OpenCV filter to setup gray color after this process tracking gray object! but I can't! please help me
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)
此代码可以向我显示2种颜色的对象:黑白 黑色几乎- 我想将这段代码混合到对象跟踪中.但很结冰.
This code can show me object in 2 color : black and white black is nearly --- I want to mix this code to object tracking. but 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/
推荐答案
代码中的逻辑似乎是正确的.不过,我注意到一些实现错误.
The logic in your code seems to be right. I noticed some implementation errors, though.
首先,您应该在while True
之后缩进该块.您还应该添加对waitKey()
的调用,以使OpenCV不会卡在imshow()
上:
First, you should indent the block after while True
. You should also add a call to waitKey()
so that OpenCV doesn't get stuck at imshow()
:
while True:
depth = getDepthMap()
blur = cv2.GaussianBlur(depth, (5, 5), 0)
cv2.imshow('image', blur)
cv2.waitKey(1)
最后,您应该将下一个块(mask
)的输入与上一个块(blur
)的输出关联:
Finally, you should associate the input of the next block (mask
) with the output of the previous one (blur
):
mask = blur
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