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
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]
keys = [
'index', 'person', 'imgname', 'center', 'scale', 'part', 'visible',
'normalize', 'torsoangle'
]
annot = {k: [] for k in keys}
dotrain = True
# Get image filenames
imgnameRef = mpii.annot['annolist'][0][0][0]['image'][:]
for idx in xrange(mpii.nimages):
print "\r", idx,
sys.stdout.flush()
if mpii.istrain(idx) == dotrain:
for person in xrange(mpii.numpeople(idx)):
c, s = mpii.location(idx, person)
if not c[0] == -1:
# Adjust center/scale slightly to avoid cropping limbs
# (in hindsight this should have been done in the Torch code...)
c[1] += 15 * s
s *= 1.25
# 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)
# Add info to annotation list
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
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]
import numpy as np
import sys
import mpii
keys = ['index','person','imgname','center','scale','part','visible','normalize','torsoangle']
annot = {k:[] for k in keys}
dotrain = True
# Get image filenames
imgnameRef = mpii.annot['annolist'][0][0][0]['image'][:]
for idx in xrange(mpii.nimages):
print "\r",idx,
sys.stdout.flush()
if mpii.istrain(idx) == dotrain:
for person in xrange(mpii.numpeople(idx)):
c,s = mpii.location(idx,person)
if not c[0] == -1:
# Adjust center/scale slightly to avoid cropping limbs
# (in hindsight this should have been done in the Torch code...)
c[1] += 15 * s
s *= 1.25
# 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)
# Add info to annotation list