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github.com/cwc1260/HandFold
/ functions
Functions
35 in github.com/cwc1260/HandFold
⨍
Functions
35
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Types & classes
4
↓ 6 callers
Function
group_points
(points, opt, sampling_func='random')
train_eval/utils.py:202
↓ 4 callers
Function
final_group
(joint_coarse, original_points, num_neighbors, ball_radius)
train_eval/utils.py:266
↓ 2 callers
Method
__get_frmae_num
(self, data_dir)
train_eval/dataset_msra.py:125
↓ 2 callers
Method
__loaddata
(self, data_dir)
train_eval/dataset_msra.py:96
↓ 2 callers
Function
group_points_2
(points, sample_num_level1, sample_num_level2, knn_K, ball_radius, sampling_func='random')
train_eval/utils.py:234
↓ 2 callers
Function
rotate_point_cloud_by_angle_flip
Rotate the point cloud along up direction with certain angle. Input: BxNx3 array, original batch of point clouds Return:
train_eval/utils.py:127
↓ 1 callers
Method
__fileToNumpy
(self, filename)
train_eval/dataset_icvl.py:82
↓ 1 callers
Method
__loaddata
(self, data_dir)
train_eval/dataset_icvl.py:69
↓ 1 callers
Method
__total_frmae_num
(self)
train_eval/dataset_msra.py:111
Method
__get_frmae_num
(self, data_dir)
train_eval/dataset_icvl.py:78
Method
__getitem__
(self, index)
train_eval/dataset_icvl.py:63
Method
__getitem__
(self, index)
train_eval/dataset_msra.py:90
Method
__init__
(self, opt)
train_eval/network_icvl_folding.py:34
Method
__init__
(self, opt)
train_eval/network_msra_folding.py:32
Method
__init__
(self, root_path, opt, sample=1024, train=True, shuffle=False)
train_eval/dataset_icvl.py:18
Method
__init__
(self, root_path, opt, train=True)
train_eval/dataset_msra.py:20
Method
__len__
(self)
train_eval/dataset_icvl.py:66
Method
__len__
(self)
train_eval/dataset_msra.py:93
Function
_debug
(model)
train_eval/train_icvl_folding.py:74
Function
_debug
(model)
train_eval/train_msra_folding.py:74
Function
farthest_point_sample
Input: xyz: pointcloud data, [B, N, 3] npoint: number of samples Return: centroids: sampled pointcloud index, [B, npo
train_eval/utils.py:160
Method
forward
(self, x, y)
train_eval/network_icvl_folding.py:198
Method
forward
(self, x, y)
train_eval/network_msra_folding.py:196
Function
group_points_2_coarse
(points, sample_num_level1, sample_num_level2, knn_K, ball_radius, sampling_func='random')
train_eval/utils.py:347
Function
group_points_coarse
(points, opt, sampling_func='random')
train_eval/utils.py:309
Function
grouping
(points, k, radius, sample_size=None)
train_eval/utils.py:384
Function
index_points
Input: points: input points data, [B, N, C] idx: sample index data, [B, S] Return: new_points:, indexed points data,
train_eval/utils.py:183
Function
jitter
(points, var=0.01, clip=0.05)
train_eval/utils.py:60
Function
knn
(point_center, points_samples, num_neighbors)
train_eval/utils.py:294
Function
offset_cal
(points,opt)
train_eval/utils.py:10
Function
random_cut_arm
(points)
train_eval/utils.py:419
Function
rotate_point_cloud_by_angle
Rotate the point cloud along up direction with certain angle. Input: BxNx3 array, original batch of point clouds Return:
train_eval/utils.py:98
Function
rotate_point_cloud_by_random
Rotate the point cloud along up direction with certain angle. Input: BxNx3 array, original batch of point clouds Return:
train_eval/utils.py:69
Function
smooth_l1_loss
(input, target, sigma=10., reduce=True, normalizer=1.0)
train_eval/train_icvl_folding.py:115
Function
smooth_l1_loss
(input, target, sigma=10., reduce=True, normalizer=1.0)
train_eval/train_msra_folding.py:118