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Functions126 in github.com/MetaSLAM/SphereVLAD

↓ 20 callersFunctionlog_print
Print colored stream, color options:r, g, b, lb, y, p.
utils/log_print.py:34
↓ 7 callersMethoddo_sph_projection
Project a pointcloud into a spherical projection image.projection. Function takes no arguments because it can be also called externa
utils/pointProcess.py:120
↓ 4 callersFunctionsample_within_bounds
utils/geometry/so3_rotate.py:95
↓ 3 callersMethodget_features_recall
(self, traj_num, trans_IDX, rot_IDX, rand_idx=0)
eval/eval_utils.py:40
↓ 3 callersMethodload_file_func
(self, filename)
dataloader/triplet_dataloader.py:127
↓ 2 callersFunctionLatLon2Pixel
(LatLon)
utils/equirectRotate/utils.py:54
↓ 2 callersFunctionSphere2LatLon
(xyz)
utils/equirectRotate/utils.py:47
↓ 2 callersMethod_M
(self, axis, theta)
dataloader/data_augmentation.py:149
↓ 2 callersMethod__init__
(self, margin=0.2)
models/loop_closure/losses/lazy_quadruplet_loss.py:77
↓ 2 callersFunction_best_neg_distance
Caculate the distance between query and negitative query Args: query ([batch, 1, 8192]): Query information neg_vecs ([batch, 2
models/loop_closure/losses/lazy_quadruplet_loss.py:29
↓ 2 callersFunction_best_pos_distance
Find the minimum distance between query feature and positives features. Args: query (tensor: batch_size x 1 x feature_dim): Output fe
models/loop_closure/losses/lazy_quadruplet_loss.py:4
↓ 2 callersMethodconstruct_query_dict
(self, data_df, filename)
dataloader/pittsburgh.py:112
↓ 2 callersFunctiongetRotMatrix
:param rotation: (yaw, pitch, roll) in degree :return: general rotational matrix refer this: https://en.wikipedia.org/wiki/Rotation_matrix#Gene
utils/equirectRotate/utils.py:3
↓ 2 callersMethodget_df
(self, dataset_dir, type='train', is_shuffle=False)
dataloader/pittsburgh.py:91
↓ 2 callersFunctionget_projection_grid
returns the spherical grid in euclidean coordinates, where the sphere's center is moved to (0, 0, 1)
utils/geometry/so3_rotate.py:64
↓ 2 callersMethodget_queries_dict
(filename)
dataloader/triplet_dataloader.py:139
↓ 2 callersMethodinfer_frame
(self, x, t=False)
models/robotLCD.py:151
↓ 2 callersMethodload_checkpoint
(self, weight_path, resume=False)
models/robotLCD.py:122
↓ 2 callersMethodload_files_func
(self, filenames)
dataloader/triplet_dataloader.py:130
↓ 2 callersFunctionmake_data_loader
Args: config: parameter configurations gpu_ids: gpu indexes for training is_train: training or testing Returns:
dataloader/__init__.py:6
↓ 2 callersFunctionproject_2d_on_sphere
utils/geometry/so3_rotate.py:145
↓ 2 callersFunctionrand_rotation_matrix
Creates a random rotation matrix. deflection: the magnitude of the rotation. For 0, no rotation; for 1, competely random rotation. Small
utils/geometry/so3_rotate.py:13
↓ 2 callersFunctionrotate_grid
(rot, grid)
utils/geometry/so3_rotate.py:57
↓ 2 callersMethodsave_checkpoint
(self, epoch)
models/robotLCD.py:115
↓ 2 callersFunctionset_lcd_model
(cfg, logger=None, neptune=None)
models/__init__.py:7
↓ 1 callersFunctionLatLon2Sphere
(LatLon)
utils/equirectRotate/utils.py:37
↓ 1 callersFunctionPixel2LatLon
(equirect)
utils/equirectRotate/utils.py:24
↓ 1 callersMethod__init__
Args: num_clusters : int The number of clusters dim : int Dimension of descriptors
models/loop_closure/aggregator/netvlad.py:10
↓ 1 callersMethod__init__
(self, in_dim)
models/loop_closure/transformer/attention.py:12
↓ 1 callersMethod_init_params
(self)
models/loop_closure/aggregator/netvlad.py:41
↓ 1 callersMethodadjust_learning_rate
(self)
models/robotLCD.py:111
↓ 1 callersFunctionblue
blue color
utils/log_print.py:24
↓ 1 callersMethodeval_lcd
(self, x)
models/robotLCD.py:97
↓ 1 callersMethodgenerate_pickles
(self)
dataloader/pittsburgh.py:52
↓ 1 callersMethodget_data
(self)
dataloader/triplet_dataloader.py:46
↓ 1 callersMethodget_from_folder
(self, data_path, index)
dataloader/pittsburgh.py:72
↓ 1 callersMethodget_params
(self, coords)
dataloader/data_augmentation.py:267
↓ 1 callersMethodget_recall
(self, database_feature, queries_feature, num_neighbors=30)
eval/eval_utils.py:112
↓ 1 callersMethodget_tuple
hard_neg: bool, add hard negative? other_neg: bool, add other negatives?(quadra loss fuction required)
dataloader/triplet_dataloader.py:69
↓ 1 callersFunctiongreen
green color
utils/log_print.py:9
↓ 1 callersMethodinfer_image
(self, x, t=False)
models/robotLCD.py:157
↓ 1 callersMethodinfer_lidar
(self, x, t=False)
models/robotLCD.py:170
↓ 1 callersFunctionlblue
green color
utils/log_print.py:14
↓ 1 callersFunctionmake_collate_fn
Generate Collate_functions Args: config (class): parameter configurations
dataloader/utils.py:1
↓ 1 callersFunctionmake_losses
(config)
models/loop_closure/losses/__init__.py:3
↓ 1 callersFunctionmake_models
(config)
models/loop_closure/__init__.py:4
↓ 1 callersFunctionpara_args
()
train_lcd.py:27
↓ 1 callersFunctionpara_args
()
eval/evaluate_pitt.py:15
↓ 1 callersFunctionpara_args
()
generating_sph/gene_pitt.py:43
↓ 1 callersFunctionpc_normalize
(pc)
utils/pointProcess.py:7
↓ 1 callersFunctionpink
pink color
utils/log_print.py:19
↓ 1 callersFunctionproject_sphere_on_xy_plane
returns xy coordinates on the plane obtained from projecting each point of the spherical grid along the ray from the projection origin th
utils/geometry/so3_rotate.py:77
↓ 1 callersFunctionred
red color
utils/log_print.py:4
↓ 1 callersFunctionsample_bilinear
utils/geometry/so3_rotate.py:110
↓ 1 callersFunctionsetup_logger
(name, cfg, args, is_train)
utils/logger.py:7
↓ 1 callersMethodshuffle_query
(self)
dataloader/triplet_dataloader.py:65
↓ 1 callersFunctiontrain
(config, logger, neptune)
train_lcd.py:37
↓ 1 callersMethodtrain_lcd
[summary] Args: x ([type]): [description]
models/robotLCD.py:74
↓ 1 callersFunctionval
(config, type, noise, trans_noise, rot_noise, log)
eval/evaluate_pitt.py:30
↓ 1 callersFunctionyellow
yellow color
utils/log_print.py:29
Method__call__
(self, input)
dataloader/data_augmentation.py:41
Method__call__
(self, input)
dataloader/data_augmentation.py:67
Method__call__
(self, input)
dataloader/data_augmentation.py:90
Method__call__
(self, sph_img)
dataloader/data_augmentation.py:102
Method__call__
(self, coords)
dataloader/data_augmentation.py:128
Method__call__
(self, coords)
dataloader/data_augmentation.py:152
Method__call__
(self, coords)
dataloader/data_augmentation.py:171
Method__call__
(self, coords)
dataloader/data_augmentation.py:181
Method__call__
(self, coords)
dataloader/data_augmentation.py:190
Method__call__
Randomly jitter points. jittering is per point. Input: BxNx3 array, original batch of point clouds Return:
dataloader/data_augmentation.py:204
Method__call__
(self, e)
dataloader/data_augmentation.py:243
Method__call__
(self, coords)
dataloader/data_augmentation.py:285
Method__getitem__
(self, idx)
dataloader/triplet_dataloader.py:42
Method__init__
(self, device, top_size=[64, 64], z_range=[-100.0, 100.0], sph_size=[64, 64], fov_range=[-90, 90], max_dis=30,
utils/pointProcess.py:50
Method__init__
(self, pers, fov_x, rot)
utils/geometry/equi_trans.py:7
Method__init__
(self, pers, rot)
utils/geometry/equi_trans.py:30
Method__init__
(self, height: int, width: int, rotation: tuple)
utils/equirectRotate/EquirectRotate.py:11
Method__init__
(self, config, is_train)
dataloader/triplet_dataloader.py:22
Method__init__
(self, config, is_train)
dataloader/pittsburgh.py:26
Method__init__
(self, mode=0, is_train=False)
dataloader/data_augmentation.py:22
Method__init__
(self, mode=0, is_train=False)
dataloader/data_augmentation.py:47
Method__init__
(self, img_size, mode=0, is_train=False)
dataloader/data_augmentation.py:73
Method__init__
(self, p, img_size)
dataloader/data_augmentation.py:97
Method__init__
(self, p)
dataloader/data_augmentation.py:121
Method__init__
(self, axis=None, max_theta=180, max_theta2=15)
dataloader/data_augmentation.py:144
Method__init__
(self, max_delta=0.05)
dataloader/data_augmentation.py:168
Method__init__
(self, min, max)
dataloader/data_augmentation.py:177
Method__init__
(self, delta=0.1)
dataloader/data_augmentation.py:187
Method__init__
(self, sigma=0.01, clip=None, p=1.)
dataloader/data_augmentation.py:196
Method__init__
(self, r)
dataloader/data_augmentation.py:231
Method__init__
(self, p=0.5, scale=(0.02, 0.33), ratio=(0.3, 3.3))
dataloader/data_augmentation.py:262
Method__init__
(self, config, model, device, number_neighbors=20)
eval/eval_utils.py:22
Method__init__
(self, config, logger, use_cuda, device, neptune=None, gpu_ids=None)
models/robotLCD.py:19
Method__init__
(self, dim, add_batch_norm=True)
models/loop_closure/aggregator/netvlad.py:81
Method__init__
(self, config)
models/loop_closure/lidar/spherevlad2.py:22
Method__init__
(self, config)
models/loop_closure/lidar/spherevlad.py:21
Method__init__
(self, config)
models/loop_closure/visual/spherevlad.py:21
Method__init__
(self, in_dim, type)
models/loop_closure/transformer/attention.py:52
Method__init__
(self, margin=0.2)
models/loop_closure/losses/lazy_quadruplet_loss.py:52
Method__init__
(self, margin_dis, margin_sec)
models/loop_closure/losses/lazy_quadruplet_loss.py:116
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