def check_coordinate_transforms():
example = dataset[keys]
p3w = example['p3w']
p3c = example['p3c']
r = example.attrs['r']
t = example.attrs['t']
transformed = np_impl.transform_frame(p3w, r, t)
print(np.max(np.abs(transformed - p3c)), np.max(np.abs(p3c)))
def __getitem__(self, key):
if key == 'p3w':
p3c = self['p3c']
r = self.attrs['r']
t = self.attrs['t']
return np_impl.transform_frame(p3c, r, t, inverse=True)
return self._converter.convert(
self._group[MpiInfExample._group_map[key]][self._camera])
def _test_example_transforms(self, example):
p3w, p3c, r, t = (example[k] for k in ['p3w', 'p3c', 'r', 't'])
actual_p3c = transform_frame(p3w, r, t)
np.testing.assert_allclose(actual_p3c, p3c, atol=1.0)
def apply_consistent_pose(sequence):
p3w = sequence['p3w']
r, t = (sequence.attrs[k] for k in ['r', 't'])
sequence['p3c'] = np_impl.transform_frame(p3w, r=r, t=t)
def p2(self):
return np_impl.transform_frame(self.p3c, f=self.f,
c=self.c) / self.pixel_scale
def p3c(self):
return np_impl.transform_frame(self.p3w, r=self.r, t=self.t)
# raise Exception('Unrecognized skeleton, %s' % skeleton)
# else:
# return dataset
if __name__ == '__main__':
import numpy as np
from human_pose_util.skeleton import vis3d, vis2d
from human_pose_util.transforms.np_impl import transform_frame
from human_pose_util.transforms.np_impl import project
from skeleton import s14
# from skeleton import s16
from skeleton import s20
import matplotlib.pyplot as plt
# dataset = human_eva_dataset(skeleton=s16)
example = get_example(list(train_ids())[0]).map(
{k: s20.to_s14
for k in ['p2', 'p3c', 'p3w']})
p3w, p3c, p2, r, t, f, c = example['p3w', 'p3c', 'p2', 'r', 't', 'f', 'c']
p3w = p3w[0]
p3c = p3c[0]
p2 = p2[0]
p3c2 = transform_frame(p3w, r, t)
print(np.max(np.abs(p3c - p3c2)) / np.max(np.abs(p3c)))
p22 = project(p3c, f, c)
print(np.max(np.abs(p22 - p2)) / np.max(np.abs(p2)))
skeleton = s14
vis3d(skeleton, p3w)
vis3d(skeleton, p3c)
vis2d(skeleton, p2)
plt.show()