pyr_blender=pyrMask.pyrMask(frame,True,nlevs,inference_lev)
old_frame[:,:,:]=get_new_frame(frame,inference_lev)
started=False
tle=0
print tot_time
t = t+1
while(cap.isOpened() and ret):
print t
cap.set(cv2.CAP_PROP_POS_FRAMES,skip_frames*t);
ret, frame = cap.read()
new_frame[:,:,:]=get_new_frame(frame,inference_lev)
tic=time.time()
corr_frame[:,:]=corrConv.fastCorr(old_frame,new_frame,corr_support)
print time.time()-tic
bitmask[:,:]=np.uint8(corr_frame>confidence)*255
bitmask[:,:]=cv2.erode(bitmask,np.ones((erode_support,erode_support)))
#bitmask[:,:]=cv2.morphologyEx(cv2.morphologyEx(bitmask,cv2.MORPH_CLOSE,np.ones((morph_support,morph_support))),cv2.MORPH_OPEN,np.ones((morph_support,morph_support)))
#bitmask[:,:]=
for color in range(num_channels):
mask_frame[:,:,color]=bitmask
cv2.imshow(str(t),(mask_frame*255)*new_frame)
out_frame[:,:,:]=pyr_blender.maskOut(frame,mask_frame)
tle=pyr_blender.get_top_level_energy()
if not(started):
bit_frame[:,:]=bit_frame|(bitmask==255)
if np.product(bit_frame):
started=True
print "started"
import numpy as np
import cv2
import corrConv
im1 = cv2.imread('./slides/no-u-final-slide525.png')
im2 = cv2.imread('./slides/no-u-final-slide648.png')
results = corrConv.fastCorr(im1, im2, 5)
results = results * 255
results = results.astype(np.uint8)
cv2.imshow('results', results)
cv2.waitKey(0)
cv2.imwrite('./results/slide525.png', im1)
cv2.imwrite('./results/slide648.png', im2)
cv2.imwrite('./results/correlation.png', results)
#cv2.imshow('image', im1)
#cv2.waitKey(0)
sad=0
while(sad<thresh):
cap.set(cv2.CAP_PROP_POS_FRAMES,t*skip_frames);
ret,frame=cap.read()
this_frame[:,:,:]=frame
print t
print sad
sad=np.sum(np.abs(this_frame-last_frame))
t = t+1
print "out"
last_frame[:,:,:]=frame
#pyr_blender=pyrMaskiir.pyrMaskiir(frame,True,nlevs,inference_lev,r)
curr_frame[:,:,:]=frame
now_frame[:,:,:]=get_new_frame(frame,inference_lev)
corr_frame[:,:]=corrConv.fastCorr(old_frame,now_frame,corr_support)
bit_back[:,:]=corr_frame>confidence
tle=0
print tot_time
bounce=False
while(cap.isOpened() and ret):
print t
#cap.set(cv2.CAP_PROP_POS_FRAMES,skip_frames*t);
#ret, frame = cap.read()
sad=0
while(sad<thresh):
cap.set(cv2.CAP_PROP_POS_FRAMES,t*skip_frames);
ret,frame=cap.read()
this_frame[:,:,:]=frame
import numpy as np
import cv2
import corrConv
import pyrTest
nums=[77,199,321,369,463,581,684,794,860]
old=cv2.pyrDown(cv2.imread("./correlate/slidetest/fs4.png"))
otle=pyrTest.abs_tle_im(old)
resultsdir='./slide_debug/'
for num in nums:
new=cv2.pyrDown(cv2.imread("./correlate/slidetest/fs"+str(num)+".png"))
corrpic=corrConv.fastCorr(old,new,13)
cp=np.dstack((corrpic,corrpic,corrpic))
print cp.shape
ntle=pyrTest.abs_tle_im(new)
info_kept=np.multiply(otle,np.float64(cp>0.8))
p=pyrTest.rep_3d_name(np.subtract(otle,info_kept),'ilost'+str(num))
cv2.imwrite(resultsdir+'ilost'+str(num)+'.png',p)
info_lost=np.sum(np.subtract(otle,info_kept))
print info_lost
info_retained=np.multiply(ntle,np.float64(cp>0.8))
info_gained=np.sum(np.subtract(ntle,info_retained))
p=pyrTest.rep_3d_name(np.subtract(ntle,info_retained),'igained'+str(num))
cv2.imwrite(resultsdir+'igot'+str(num)+'.png',p)
print info_gained
if info_gained<info_lost:
print "better "+str(num)