def build_region(self):
start_time = time.time()
labels = slic.slic_n(np.array(self.q_cur_frame),
self.num_superpixels - 10, self.compactness)
print "Slic time : ", time.time() - start_time
_num_superpixels = np.max(labels) + 1
for lbl in range(_num_superpixels):
self.color_map[lbl].clear()
self.mean[lbl][0] = 0
self.mean[lbl][1] = 0
self.freq[lbl] = 0
for row in range(self.shape[0]):
for col in range(self.shape[1]):
if not self.color_map[labels[row, col]].has_key(
self.rgb_idx[row, col]):
self.color_map[labels[row, col]].__setitem__(
self.rgb_idx[row, col], 1)
else:
self.color_map[labels[row, col]][self.rgb_idx[row,
col]] += 1
self.freq[labels[row, col]] += 1
self.mean[labels[row,
col]][0] += (row -
self.mean[labels[row, col]][0]
) / self.freq[labels[row, col]]
self.mean[labels[row,
col]][1] += (col -
self.mean[labels[row, col]][1]
) / self.freq[labels[row, col]]
print "Build region (preprocess) : ", time.time() - start_time
return (labels, _num_superpixels)
def build_region(self):
start_time = time.time()
labels = slic.slic_n(np.array(self.q_cur_frame),
self.num_superpixels - 30, self.compactness)
print "Slic time : ", time.time() - start_time
_num_superpixels = np.max(labels) + 1
for lbl in range(_num_superpixels):
self.color_map[lbl, :] = np.zeros(3, dtype=np.float32)
self.mean[lbl][0] = 0
self.mean[lbl][1] = 0
self.freq[lbl] = 0
for row in range(self.shape[0]):
for col in range(self.shape[1]):
self.freq[labels[row, col]] += 1
_freq = self.freq[labels[row, col]]
self.color_map[labels[
row,
col], :] += (self.q_cur_frame[row, col, :] -
self.color_map[labels[row, col], :]) / _freq
self.mean[labels[
row,
col]][0] += (row - self.mean[labels[row, col]][0]) / _freq
self.mean[labels[
row,
col]][1] += (col - self.mean[labels[row, col]][1]) / _freq
print "Build region (preprocess) : ", time.time() - start_time
return (labels, _num_superpixels)
def build_region(self): start_time = time.time(); labels = slic.slic_n(np.array(self.q_cur_frame),self.num_superpixels-30, self.compactness) print "Slic time : ",time.time()-start_time _num_superpixels = np.max(labels) + 1 for lbl in range(_num_superpixels): self.color_map[lbl,:]=np.zeros(3,dtype=np.float32); self.mean[lbl][0] = 0; self.mean[lbl][1] = 0 self.freq[lbl] = 0 for row in range(self.shape[0]): for col in range(self.shape[1]): self.freq[labels[row,col]] += 1 _freq = self.freq[labels[row,col]] self.color_map[labels[row,col],:] += (self.q_cur_frame[row,col,:]-self.color_map[labels[row,col],:])/_freq; self.mean[labels[row,col]][0] += (row - self.mean[labels[row,col]][0])/_freq self.mean[labels[row,col]][1] += (col - self.mean[labels[row,col]][1])/_freq print "Build region (preprocess) : ",time.time()-start_time return (labels,_num_superpixels);
def build_region(self): start_time = time.time(); labels = slic.slic_n(np.array(self.q_cur_frame),self.num_superpixels-10, self.compactness) print "Slic time : ",time.time()-start_time _num_superpixels = np.max(labels) + 1 for lbl in range(_num_superpixels): self.color_map[lbl].clear(); self.mean[lbl][0] = 0; self.mean[lbl][1] = 0 self.freq[lbl] = 0 for row in range(self.shape[0]): for col in range(self.shape[1]): if not self.color_map[labels[row,col]].has_key(self.rgb_idx[row,col]): self.color_map[labels[row,col]].__setitem__(self.rgb_idx[row,col],1); else: self.color_map[labels[row,col]][self.rgb_idx[row,col]] += 1 self.freq[labels[row,col]] += 1 self.mean[labels[row,col]][0] += (row - self.mean[labels[row,col]][0])/self.freq[labels[row,col]] self.mean[labels[row,col]][1] += (col - self.mean[labels[row,col]][1])/self.freq[labels[row,col]] print "Build region (preprocess) : ",time.time()-start_time return (labels,_num_superpixels);
