annot['index'] += [idx]
annot['person'] += [person]
imgname = np.zeros(16)
refname = str(imgnameRef[idx][0][0][0][0])
for i in range(len(refname)): imgname[i] = ord(refname[i])
annot['imgname'] += [imgname]
annot['center'] += [c]
annot['scale'] += [s]
annot['multi'] += [multiRef[idx]]
if mpii.istrain(idx) == True:
# Part annotations and visibility
coords = np.zeros((16,2))
vis = np.zeros(16)
for part in xrange(16):
coords[part],vis[part] = mpii.partinfo(idx,person,part)
annot['part'] += [coords]
annot['visible'] += [vis]
annot['normalize'] += [mpii.normalization(idx,person)]
annot['torsoangle'] += [mpii.torsoangle(idx,person)]
annot['istrain'] += [1]
else:
annot['part'] += [-np.ones((16,2))]
annot['visible'] += [np.zeros(16)]
annot['normalize'] += [1]
annot['torsoangle'] += [0]
if trainRef[idx] == 0: # Test image
annot['istrain'] += [0]
else: # Training image (something missing in annot)
annot['istrain'] += [2]
annot['index'] += [idx]
annot['person'] += [person]
imgname = np.zeros(16)
refname = str(imgnameRef[idx][0][0][0][0])
for i in range(len(refname)): imgname[i] = ord(refname[i])
annot['imgname'] += [imgname]
annot['center'] += [c]
annot['scale'] += [s]
annot['multi'] += [multiRef[idx]]
if mpii.istrain(idx) == True:
# Part annotations and visibility
coords = np.zeros((16,2))
vis = np.zeros(16)
for part in xrange(16):
coords[part],vis[part] = mpii.partinfo(idx,person,part)
annot['part'] += [coords]
annot['visible'] += [vis]
annot['normalize'] += [mpii.normalization(idx,person)]
annot['torsoangle'] += [mpii.torsoangle(idx,person)]
annot['istrain'] += [1]
else:
annot['part'] += [-np.ones((16,2))]
annot['visible'] += [np.zeros(16)]
annot['normalize'] += [1]
annot['torsoangle'] += [0]
if trainRef[idx] == 0: # Test image
annot['istrain'] += [0]
else: # Training image (something missing in annot)
annot['istrain'] += [2]