trainRef = mpii.annot['img_train'][0][0][0]
allIdxs = np.arange(0,trainRef.shape[0])
with h5py.File('../../data/mpii/annot/multi-idxs.h5','r') as f:
mTrain = f['train'][:] - 1
mTest = f['test'][:] - 1
multiRef[allIdxs[trainRef == 1][mTrain]] = 1
multiRef[allIdxs[trainRef == 0][mTest]] = 1
# Get image filenames
imgnameRef = mpii.annot['annolist'][0][0][0]['image'][:]
for idx in xrange(mpii.nimages):
print "\r",idx,
sys.stdout.flush()
for person in xrange(mpii.numpeople(idx)):
c,s = mpii.location(idx,person)
if not c[0] == -1:
# Add info to annotation list
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
trainRef = mpii.annot['img_train'][0][0][0]
allIdxs = np.arange(0,trainRef.shape[0])
with h5py.File('../../data/mpii/annot/multi-idxs.h5','r') as f:
mTrain = f['train'][:] - 1
mTest = f['test'][:] - 1
multiRef[allIdxs[trainRef == 1][mTrain]] = 1
multiRef[allIdxs[trainRef == 0][mTest]] = 1
# Get image filenames
imgnameRef = mpii.annot['annolist'][0][0][0]['image'][:]
for idx in xrange(mpii.nimages):
print("\r",idx, end=' ')
sys.stdout.flush()
for person in xrange(mpii.numpeople(idx)):
c,s = mpii.location(idx,person)
if not c[0] == -1:
# Add info to annotation list
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