def reconstruct(self,img):
"""
This is a "just for fun" method as a sanity check for the BOF codeook.
The method takes in an image, extracts each codebook code, and replaces
the image at the position with the code.
"""
retVal = cv.CreateImage((img.width,img.height), cv.IPL_DEPTH_8U, 1)
data = self._getPatches(img)
p = spsd.cdist(data,self.mCodebook)
foo = p.shape[0]
codes = np.argmin(p,axis=1)
count = 0
wsteps = img.width/self.mPatchSize[0]
hsteps = img.height/self.mPatchSize[1]
w=self.mPatchSize[0]
h=self.mPatchSize[1]
length = w*h
retVal = Image(retVal)
for widx in range(wsteps):
for hidx in range(hsteps):
x = (widx*self.mPatchSize[0])
y = (hidx*self.mPatchSize[1])
p = codes[count]
temp = Image(self.mCodebook[p,:].reshape(self.mPatchSize[0],self.mPatchSize[1]))
retVal.blit(temp,pos=(x,y))
count = count + 1
return retVal
def reconstruct(self, img):
"""
This is a "just for fun" method as a sanity check for the BOF codeook.
The method takes in an image, extracts each codebook code, and replaces
the image at the position with the code.
"""
retVal = cv.CreateImage((img.width, img.height), cv.IPL_DEPTH_8U, 1)
data = self._getPatches(img)
p = spsd.cdist(data, self.mCodebook)
foo = p.shape[0]
codes = np.argmin(p, axis=1)
count = 0
wsteps = img.width / self.mPatchSize[0]
hsteps = img.height / self.mPatchSize[1]
w = self.mPatchSize[0]
h = self.mPatchSize[1]
length = w * h
retVal = Image(retVal)
for widx in range(wsteps):
for hidx in range(hsteps):
x = (widx * self.mPatchSize[0])
y = (hidx * self.mPatchSize[1])
p = codes[count]
temp = Image(self.mCodebook[p, :].reshape(
self.mPatchSize[0], self.mPatchSize[1]))
retVal.blit(temp, pos=(x, y))
count = count + 1
return retVal
def _codebook2Img(self, cb, patchsize, count, patch_arrangement, spacersz):
"""
cb = the codebook
patchsize = the patch size (ususally 11x11)
count = total codes
patch_arrangement = how are the patches grided in the image (eg 128 = (8x16) 256=(16x16) )
spacersz = the number of pixels between patches
"""
w = (patchsize[0]*patch_arrangement[0])+((patch_arrangement[0]+1)*spacersz)
h = (patchsize[1]*patch_arrangement[1])+((patch_arrangement[1]+1)*spacersz)
bm = np.zeros((h, w), np.uint8)
img = Image(bm)
count = 0
for widx in range(patch_arrangement[0]):
for hidx in range(patch_arrangement[1]):
x = (widx*patchsize[0])+((widx+1)*spacersz)
y = (hidx*patchsize[1])+((hidx+1)*spacersz)
temp = Image(cb[count,:].reshape(patchsize[0],patchsize[1]))
img.blit(temp,pos=(x,y))
count = count + 1
return img
