class BoVWextractor(BaseEstimator):
def __init__(self, K=512, no_dump_codebook=False, force_reload=False):
self.K = K
self.no_dump_codebook=no_dump_codebook
self.force_reload = force_reload
def fit(self, X, y=None):
# Compute the codebook
self.codebook = Codebook(K=self.K,no_dump=self.no_dump_codebook, force_reload=self.force_reload)
self.codebook.fit(X['descriptors'])
return self
def transform(self, X):
print 'Getting BoVW representation'
init = time.time()
descriptors = X['descriptors']
visual_words = np.zeros((len(descriptors), self.K), dtype=np.float32)
for i in xrange(len(descriptors)):
words = self.codebook.predict(descriptors[i])
visual_words[i, :] = np.bincount(words, minlength=self.K)
end = time.time()
print '\tDone in ' + str(end - init) + ' secs.'
return visual_words
class SpatialPyramids(BaseEstimator):
def __init__(self, K=512, num_levels=3, no_dump_codebook=False):
self.K = K
self.num_levels = num_levels
self.no_dump_codebook = no_dump_codebook
def fit(self, X, y=None):
# Compute the codebook
self.codebook = Codebook(K=self.K, no_dump=self.no_dump_codebook)
self.codebook.fit(X['descriptors'])
return self
def transform(self, X):
print 'Getting Spatial Pyramid representation'
init = time.time()
descriptors = X['descriptors']
positions = X['positions']
imsizes = X['imsizes']
# Num. of cols/rows for each pyramid level
grid_ncolsrows = 2**np.arange(self.num_levels)
visual_words = np.zeros(
(len(descriptors), self.K * np.sum(grid_ncolsrows**2)),
dtype=np.float32)
for im in xrange(len(descriptors)):
# Compute the words
words = self.codebook.predict(descriptors[im])
# Compute the bincount for each grid cell in each pyramid level
current_vw = []
for l in range(self.num_levels):
r_vec = np.linspace(0,
imsizes[im][0] + 1,
num=grid_ncolsrows[l] + 1)
c_vec = np.linspace(0,
imsizes[im][1] + 1,
num=grid_ncolsrows[l] + 1)
for i in range(grid_ncolsrows[l]):
for j in range(grid_ncolsrows[l]):
rb = np.logical_and(positions[im][:, 0] >= r_vec[i],
positions[im][:, 0] < r_vec[i + 1])
cb = np.logical_and(positions[im][:, 1] >= c_vec[j],
positions[im][:, 1] < c_vec[j + 1])
current_vw.extend(
np.bincount(words[np.logical_and(rb, cb)],
minlength=self.K))
# Save the computed values
visual_words[im, :] = current_vw
end = time.time()
print '\tDone in ' + str(end - init) + ' secs.'
return visual_words
