try:
step = int(sys.argv[4])
except:
step = 10
sys.path.append(
os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../.."))
from mvn.datasets.human36m import Human36MMultiViewDataset
dataset = Human36MMultiViewDataset(h36m_root,
labels_path,
train=True,
test=True,
image_shape=(512, 512),
retain_every_n_frames_in_test=1,
with_damaged_actions=True,
scale_bbox=1.0,
kind='human36m',
norm_image=False,
undistort_images=False,
ignore_cameras=[])
print(len(dataset))
prev_action = None
patience = 0
sample_idx = 0 # number of sample to start from
step = 10 # in frames
while True:
sample = dataset[sample_idx]
import os, sys
sys.path.append(
os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../.."))
from mvn.datasets.human36m import Human36MMultiViewDataset
h36m_root = os.path.join(sys.argv[1], "processed")
labels_multiview_npy_path = sys.argv[2]
number_of_processes = int(sys.argv[3])
dataset = Human36MMultiViewDataset(
h36m_root,
labels_multiview_npy_path,
train=True, # include all possible data
test=True,
image_shape=None, # don't resize
retain_every_n_frames_in_test=1, # yes actually ALL possible data
with_damaged_actions=True, # I said ALL DATA
kind="mpii",
norm_image=False, # don't do unnecessary image processing
crop=False) # don't crop
print("Dataset length:", len(dataset))
n_subjects = len(dataset.labels['subject_names'])
n_cameras = len(dataset.labels['camera_names'])
# First, prepare: compute distorted meshgrids
print("Computing distorted meshgrids")
meshgrids = np.empty((n_subjects, n_cameras), dtype=object)
for sample_idx in tqdm(range(len(dataset))):
import os, sys
sys.path.append(
os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../.."))
from mvn.datasets.human36m import Human36MMultiViewDataset
h36m_root = sys.argv[1]
labels_multiview_npy_path = sys.argv[2]
number_of_processes = int(sys.argv[3])
dataset = Human36MMultiViewDataset(h36m_root,
labels_multiview_npy_path,
train=True,
test=True,
image_shape=None,
retain_every_n_frames_in_test=1,
with_damaged_actions=True,
scale_bbox=1.0,
kind="mpii",
norm_image=False)
print("Dataset length:", len(dataset))
n_subjects = len(dataset.labels['subject_names'])
n_cameras = len(dataset.labels['camera_names'])
# First, prepare: compute distorted meshgrids
print("Computing distorted meshgrids")
meshgrids = np.empty((n_subjects, n_cameras), dtype=object)
for sample_idx in tqdm(range(len(dataset))):
subject_idx = dataset.labels['table']['subject_idx'][sample_idx]