i have these
codebook.py
#http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.148.9778&rep=rep1&type=pdf
import numpy as np
import cv2
alpha = 5
beta = 0.95
Tdel = 80
Tadd = 140
Th= 80
mn,mx,f,l,p,q=0,1,2,3,4,5
class CodeBook():
def __init__(self,h,w):
self.h = h
self.w = w
self.M = np.empty((h, w), dtype=np.object)
self.H = np.empty((h, w), dtype=np.object)
filler = np.frompyfunc(lambda x: list(), 1, 1)
filler(self.M,self.M)
filler(self.H,self.H)
self.t = 1
def updatev(self,gray,cb):
I,t = gray,self.t
if not cb:
c = [max(0.0,I-alpha),min(255.0,I+alpha),1,t-1,t,t]
cb.append(c)
else:
found = False
for cm in cb:
if(cm[mn]<=I<=cm[mx] and not found):
cm[mn] = ((I-alpha)+(cm[f]*cm[mn]))/(cm[f]+1.0)
cm[mx] = ((I+alpha)+(cm[f]*cm[mx]))/(cm[f]+1.0)
cm[f] += 1
#cm[l] = max(cm[l],t-cm[q])
cm[l] = 0
cm[q] = t
found = True
else:
cm[l] = max(cm[l],10-cm[q]+cm[p]-1)
if not found:
c = [max(0.0,I-alpha),min(255.0,I+alpha),1,t-1,t,t]
cb.append(c)
return cb
def update(self,gray):
h,w,M = self.h,self.w,self.M
updatev = np.vectorize(self.updatev,otypes=[np.object])
self.M=updatev(gray,M)
self.t += 1
def fgv(self,gray,cwm,cwh):
I,t = gray,self.t
pixval = 0
found = False
for cm in cwm:
if(cm[mn]<=I<=cm[mx] and not found):
cm[mn] = (1-beta)*(I-alpha) + (beta*cm[mn])
cm[mx] = (1-beta)*(I+alpha) + (beta*cm[mx])
cm[f] += 1
#cm[l] = max(cm[l],t-cm[q])
cm[l] = 0
cm[q] = t
found = True
else:
cm[l] += 1
#cm[l]=max(cm[l],t-cm[q]+cm[p]-1)
cwm[:] = [cw for cw in cwm if cw[l]<Tdel]
if found: return 0
for cm in cwh:
if(cm[mn]<=I<=cm[mx] and not found):
cm[mn] = (1-beta)*(I-alpha) + (beta*cm[mn])
cm[mx] = (1-beta)*(I+alpha) + (beta*cm[mx])
cm[f] += 1
#cm[l] = max(cm[l],t-cm[q])
cm[l] = 0
cm[q] = t
found = True
else:
#cm[l]=max(cm[l],t-cm[q]+cm[p]-1)
cm[l] += 1
if not found:
c = [max(0.0,I-alpha),min(255.0,I+alpha),1,0,t,t]
cwh.append(c)
cwh[:] = [cw for cw in cwh if cw[l]<Th]
tomove = [cw for cw in cwh if cw[f]>Tadd]
cwh[:] = [cw for cw in cwh if not cw in tomove]
cwm.extend(tomove)
return 255
def fg(self,gray):
h,w,M,H = self.h,self.w,self.M,self.H
fgv = np.vectorize(self.fgv,otypes=[np.uint8])
fg = fgv(gray,M,H)
self.t += 1
return fg
test.py
import cv2
import sys
import numpy as np
import time
import cProfile
import pyximport; pyximport.install(reload_support=True,
setup_args={'script_args':["--compiler=mingw32"]})
import codebook
c = cv2.VideoCapture(0)
c.set(3,320)
c.set(4,240)
cv2.namedWindow('vid',0)
cv2.namedWindow('fg',0)
_,img = c.read()
img = cv2.resize(img,(160,120))
h,w = img.shape[:2]
cb = codebook.CodeBook(h,w)
N=0
def fillholes(gray):
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
res = cv2.morphologyEx(gray,cv2.MORPH_OPEN,kernel)
def run():
while(1):
global N
_,img = c.read()
img = cv2.resize(img,(160,120))
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow('vid',gray)
if N < 10:
cb.update(gray)
else:
start = time.clock()
fg = cb.fg(gray)
print time.clock()-start
element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(2,2))
fg= cv2.erode(fg,element)
fillholes(fg)
cv2.imshow('fg',fg)
N += 1
if cv2.waitKey(5)==27:
break
run()
cv2.destroyAllWindows()
c.release()
the code is stuck @ fgv. cython can speed it up somewhat. but it is still running slowly. i am thinking of doing either of the two
- make it run in parallel
- multithreading. i am using epd's numpy and changed the MKL_NUM_THREADS to 8. yet it is still bound to a single core.
- distribute to worker processes array slices
- redo some/all(which? i have no exp) parts in cpp although i really would like to avoid this
i have changed fgv as much as i know how. please let me know what should i be looking at next. thanks a lot!
