以下代码在我的桌面(Mint 17)上运行没有任何问题,但是当我尝试在运行Raspbian的RPi上运行它时,我在第58行得到了上面提到的错误消息。我唯一能想到的就是&#39 ;导致它的是Python版本:
Mint使用Python 2.7.6
$ python -V
Python 2.7.6
RPi使用2.7.3,但我已经安装了2.7.8并将其别名
$ python -V
Python 2.7.3
$ alias python=/usr/local/bin/python2.7
$ python -V
Python 2.7.8
我知道这里有类似的问题,但问题似乎与代码有关。我知道这段代码没关系,所以它一定是个环境问题,对吧?
无论如何,这是程序:
#!/usr/bin/env python
# Determines if a set of three images contains at least one person
# Images are taken in quick succession, the 2nd and 3rd are diff images of the first
# Adapted from sample file: /opencv/samples/python2/peopledetect.py
#
# Example: ./pdTriple.py IMG_000.JPG IMG_001.JPG IMG_002.JPG
import numpy as np
import cv2
import sys
from glob import glob
import itertools as it
from array import *
def inside(r, q):
rx, ry, rw, rh = r
qx, qy, qw, qh = q
return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh
def draw_detections(img, rects, thickness = 1):
for x, y, w, h in rects:
# the HOG detector returns slightly larger rectangles than the real objects.
# so we slightly shrink the rectangles to get a nicer output.
pad_w, pad_h = int(0.15*w), int(0.05*h)
cv2.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)
if __name__ == '__main__':
hog = cv2.HOGDescriptor()
hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
count = 0
results = np.array([0,0,0])
for fn in it.chain(*map(glob, sys.argv[1:])):
print fn, ' - ',
try:
img = cv2.imread(fn)
if img is None:
print 'Failed to load image file:', fn
continue
except:
print 'loading error'
continue
# modify winstride and padding values to optimise results
found, w = hog.detectMultiScale(img, winStride=(4,4), padding=(8,8), scale=1.05)
found_filtered = []
for ri, r in enumerate(found):
for qi, q in enumerate(found):
if ri != qi and inside(r, q):uname # errors here
break
else:
found_filtered.append(r)
print '%d found (%d filtered)' % (len(found_filtered), len(found))
results[count] = len(found_filtered)
count += 1
if np.all(results>0):
print '\n--------------', fn, 'contains a person --------------\n'
答案 0 :(得分:0)
如果你删除'uname',它会工作;
for ri, r in enumerate(found):
for qi, q in enumerate(found):
if ri != qi and inside(r, q): # errors here
break
else:
found_filtered.append(r)