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Functions207 in github.com/JMoonr/LATR

⨍ Functions 207◇ Types & classes 27
↓ 25 callersFunctionis_main_process
()
experiments/gpu_utils.py:12
↓ 17 callersMethodupdate
(self, val, n=1)
utils/utils.py:352
↓ 13 callersMethodto
(self, device)
models/sparse_inst_loss.py:33
↓ 10 callersMethodclose
(self)
utils/utils.py:335
↓ 10 callersFunctionresample_laneline_in_y
Interpolate x, z values at each anchor grid, including those beyond the range of input lnae y range :param input_lane: N x 2 or N x 3 n
utils/utils.py:125
↓ 9 callersFunctionprojection_g2im
(cam_pitch, cam_height, K)
utils/utils.py:195
↓ 8 callersFunctionmkdir_if_missing
(directory)
utils/utils.py:284
↓ 6 callersFunctionprune_3d_lane_by_visibility
(lane_3d, visibility)
utils/utils.py:107
↓ 5 callersFunctionprojective_transformation
Helper function to transform coordinates defined by transformation matrix Args: Matrix (multi dim - array): 3x4 projection m
utils/utils.py:252
↓ 5 callersMethodwrite
(self, msg)
utils/utils.py:324
↓ 4 callersFunctiongpu_available
()
experiments/gpu_utils.py:16
↓ 4 callersFunctionhomograpthy_g2im
(cam_pitch, cam_height, K)
utils/utils.py:186
↓ 4 callersMethodinit_weights
(self)
models/transformer_bricks.py:536
↓ 4 callersFunctionprojection_g2im_extrinsic
(E, K)
utils/utils.py:211
↓ 4 callersFunctionprune_3d_lane_by_range
(lane_3d, x_min, x_max)
utils/utils.py:112
↓ 4 callersFunctionscatter_sum
(src: torch.Tensor, index: torch.Tensor, dim: int = -1, out: Optional[torch.Tensor] = None,
models/scatter_utils.py:20
↓ 3 callersFunctionSolveMinCostFlow
Solving an Assignment Problem with MinCostFlow" :param adj_mat: adjacency matrix with binary values indicating possible matchings between
utils/MinCostFlow.py:32
↓ 3 callersMethod__init__
(self, tensors, mask: Optional[Tensor])
models/sparse_inst_loss.py:29
↓ 3 callersMethod__init__
(self, encoder=None, decoder=None, init_cfg=None)
models/transformer_bricks.py:526
↓ 3 callersMethod_init_weights
(self)
models/sparse_ins.py:30
↓ 3 callersMethodbench
Matching predicted lanes and ground-truth lanes in their IPM projection, ignoring z attributes. x error, y_error, and z error
utils/eval_3D_lane_apollo.py:75
↓ 3 callersMethodeval
(self)
experiments/runner.py:514
↓ 3 callersFunctionground2img
(coords3d, H, W, lidar2img, ori_shape, mask=None, return_img_pts=False)
models/transformer_bricks.py:65
↓ 3 callersFunctionhomography_crop_resize
compute the homography matrix transform original image to cropped and resized image :param org_img_size: [org_h, org_w] :param cro
utils/utils.py:217
↓ 3 callersMethodlog_eval_stats
(self, eval_stats)
experiments/runner.py:685
↓ 2 callersMethod__init__
(self, cfg, in_channels)
models/sparse_ins.py:21
↓ 2 callersMethod_get_src_permutation_idx
(self, indices)
models/sparse_inst_loss.py:228
↓ 2 callersFunction_make_stack_3x3_convs
(num_convs, in_channels, out_channels)
models/sparse_ins.py:10
↓ 2 callersFunction_max_by_axis
(the_list)
models/sparse_inst_loss.py:19
↓ 2 callersMethodbench
Matching predicted lanes and ground-truth lanes in their IPM projection, ignoring z attributes. x error, y_error, and z error
utils/eval_3D_lane.py:61
↓ 2 callersMethodbench_PR
Matching predicted lanes and ground-truth lanes in their IPM projection, ignoring z attributes. x error, y_error, and z error
utils/eval_3D_lane_apollo.py:595
↓ 2 callersMethodbench_one_submit_ddp
(self, pred_lines_sub, gt_lines_sub, model_name, prob_th=0.5, vis=False)
utils/eval_3D_lane.py:423
↓ 2 callersFunctionbroadcast
(src: torch.Tensor, other: torch.Tensor, dim: int)
models/scatter_utils.py:8
↓ 2 callersMethoddecompose
(self)
models/sparse_inst_loss.py:43
↓ 2 callersFunctionget_loader
create dataset from ground-truth return a batch sampler based ont the dataset
data/Load_Data.py:527
↓ 2 callersFunctionhomograpthy_g2im_extrinsic
E: extrinsic matrix, 4*4
utils/utils.py:203
↓ 2 callersFunctioninverse_sigmoid
Inverse function of sigmoid. Args: x (Tensor): The tensor to do the inverse. eps (float): EPS avoid numerical
models/utils.py:6
↓ 2 callersFunctionis_dist_avail_and_initialized
()
models/sparse_inst_loss.py:133
↓ 2 callersFunctionmap_once_json2img
(json_label_file)
data/Load_Data.py:587
↓ 2 callersFunctionnested_masks_from_list
(tensor_list: List[Tensor], input_shape=None)
models/sparse_inst_loss.py:108
↓ 2 callersMethodproj_oneline_zx
:param one_lane: N*3,[[x,y,z],...] :return:
utils/eval_3D_once.py:32
↓ 2 callersMethodsave_checkpoint
(self, state, to_copy, epoch, save_path)
experiments/runner.py:259
↓ 2 callersFunctionscatter_mean
(src: torch.Tensor, index: torch.Tensor, dim: int = -1, out: Optional[torch.Tensor] = None,
models/scatter_utils.py:50
↓ 2 callersMethodsort_lanes_z
(self, lanes)
utils/eval_3D_once.py:278
↓ 2 callersMethodtrain
(self)
experiments/runner.py:76
↓ 2 callersMethodvalidate
(self, model, **kwargs)
experiments/runner.py:272
↓ 1 callersMethodWIP__getitem__
Args: idx (int): Index in list to load image
data/apollo_dataset.py:160
↓ 1 callersMethodWIP__getitem__
Args: idx (int): Index in list to load image
data/Load_Data.py:329
↓ 1 callersMethod__init__
(self, inc, outc, kernel_size=1)
models/ms2one.py:19
↓ 1 callersMethod_get_model_ddp
(self)
experiments/runner.py:545
↓ 1 callersMethod_get_model_from_cfg
(self)
experiments/runner.py:481
↓ 1 callersMethod_get_tgt_permutation_idx
(self, indices)
models/sparse_inst_loss.py:235
↓ 1 callersMethod_get_train_dataset
(self)
experiments/runner.py:530
↓ 1 callersMethod_get_valid_dataset
(self)
experiments/runner.py:621
↓ 1 callersMethod_init_weights
(self)
models/sparse_ins.py:75
↓ 1 callersMethod_init_weights
(self)
models/sparse_ins.py:170
↓ 1 callersMethod_init_weights
(self)
models/latr_head.py:177
↓ 1 callersMethod_load_ckpt_from_workdir
(self, model)
experiments/runner.py:496
↓ 1 callersMethod_log_genlane_eval_info
(self, eval_stats)
experiments/runner.py:699
↓ 1 callersMethod_log_model_info
(self, model)
experiments/runner.py:237
↓ 1 callersMethod_log_training_loss
(self, output, epoch, step, data_loader)
experiments/runner.py:246
↓ 1 callersFunction_onnx_nested_tensor_from_tensor_list
(tensor_list: List[Tensor])
models/sparse_inst_loss.py:54
↓ 1 callersMethod_recal_gpus_val
(self, gather_output, eval_stats)
experiments/runner.py:419
↓ 1 callersFunctionbuild_ms2one
(config)
models/ms2one.py:9
↓ 1 callersFunctionbuild_nn_loss
(loss_cfg)
models/latr_head.py:452
↓ 1 callersMethodcal_mean_dist
:param src_line: gt :param dst_line: pred :return:
utils/eval_3D_once.py:262
↓ 1 callersMethodcal_tp
(self, gt_num, pred_num, gt_lanes, pred_lanes)
utils/eval_3D_once.py:303
↓ 1 callersMethodcalc_iou
:param lane1: :param lane2: :return:
utils/eval_3D_once.py:246
↓ 1 callersMethodcompute_coordinates
(self, x)
models/sparse_ins.py:175
↓ 1 callersFunctioncompute_mask_iou
(inputs, targets)
models/sparse_inst_loss.py:174
↓ 1 callersFunctioncreate_logger
(args)
utils/utils.py:41
↓ 1 callersFunctiondata_aug_rotate
(img)
data/apollo_dataset.py:438
↓ 1 callersFunctiondata_aug_rotate
(img)
data/Load_Data.py:509
↓ 1 callersFunctionddp_init
(args)
experiments/ddp.py:68
↓ 1 callersFunctiondefine_scheduler
(optimizer, args, dataset_size=None)
utils/utils.py:392
↓ 1 callersFunctiondice_loss
(inputs, targets, reduction='sum')
models/sparse_inst_loss.py:194
↓ 1 callersMethodeval
(self)
utils/eval_3D_once.py:286
↓ 1 callersMethodfile_parser
(gt_root_path, pred_root_path)
utils/eval_3D_once.py:58
↓ 1 callersFunctionfirst_run
(save_path)
utils/utils.py:271
↓ 1 callersMethodforward
(self, x, mask, query, query_embed, pos_embed, reference_points=None,
models/transformer_bricks.py:588
↓ 1 callersMethodgen_single_file_json
(self)
data/apollo_dataset.py:110
↓ 1 callersFunctiongenerate_ref_pt
(minx, miny, maxx, maxy, z, nx, ny, device='cuda')
models/transformer_bricks.py:43
↓ 1 callersFunctionget_args
()
main.py:9
↓ 1 callersMethodget_loss
(self, loss, outputs, targets, indices, num_instances, **kwargs)
models/sparse_inst_loss.py:322
↓ 1 callersMethodget_loss
(self, output_dict, input_dict)
models/latr_head.py:347
↓ 1 callersMethodget_project_loss
(self, results, input_dict, h=20, w=30)
models/latr_head.py:308
↓ 1 callersFunctionget_random_state
()
data/transform.py:9
↓ 1 callersFunctionget_rank
()
experiments/gpu_utils.py:4
↓ 1 callersMethodget_reference_points
Get the reference points used in decoder. Args: spatial_shapes (Tensor): The shape of all feature maps, has shape
models/transformer_bricks.py:544
↓ 1 callersMethodget_valid_ratio
Get the valid radios of feature maps of all level.
models/transformer_bricks.py:574
↓ 1 callersMethodget_weight_dict
(self, cfg)
models/sparse_inst_loss.py:216
↓ 1 callersFunctionget_world_size
()
models/sparse_inst_loss.py:141
↓ 1 callersMethodinit_dataset_3D
:param dataset_info_file: :return: image paths, labels in unormalized net input coordinates data processing: ground
data/apollo_dataset.py:312
↓ 1 callersMethodinit_weights
Default initialization for Parameters of Module.
models/transformer_bricks.py:165
↓ 1 callersMethodlane_evaluation
(self, gt_root_path, pred_root_path, config_path, args=None)
utils/eval_3D_once.py:105
↓ 1 callersMethodlog_eval_info
(self)
utils/eval_3D_lane_apollo.py:68
↓ 1 callersMethodloss
output : from self.forward lane_idx_map : instance-level segmentation map, [20, H, W] where 20=max_lanes
models/sparse_ins.py:219
↓ 1 callersFunctionmain
()
main.py:29
↓ 1 callersFunctionmain
Solving an Assignment Problem with MinCostFlow
utils/MinCostFlow.py:99
↓ 1 callersMethodparse_processed_info_dict_apollo
(self, idx)
data/apollo_dataset.py:144
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