remove _init_paths - use module name directly instead

src/demo.py

@@ -2,15 +2,13 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
-
 import logging
 import os
 import os.path as osp
-from opts import opts
-from tracking_utils.utils import mkdir_if_missing
-from tracking_utils.log import logger
-import datasets.dataset.jde as datasets
+from src.lib.opts import opts
+from src.lib.tracking_utils.utils import mkdir_if_missing
+from src.lib.tracking_utils.log import logger
+import src.lib.datasets.dataset.jde as datasets
 from track import eval_seq
 
 

src/detect.py

@@ -2,7 +2,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
 import os
 import os.path as osp
 import cv2
@@ -11,18 +10,17 @@
 import motmetrics as mm
 import numpy as np
 
-from tracker.fusetracker import FuseTracker
-from tracking_utils import visualization as vis
-from tracking_utils.log import logger
-from tracking_utils.timer import Timer
-from tracking_utils.evaluation import Evaluator
-import datasets.dataset.jde as datasets
+from src.lib.tracking_utils import visualization as vis
+from src.lib.tracking_utils.log import logger
+from src.lib.tracking_utils.timer import Timer
+from src.lib.tracking_utils.evaluation import Evaluator
+import src.lib.datasets.dataset.jde as datasets
 import torch
-from tracking_utils.utils import mkdir_if_missing, tlbr2tlwh
-from opts import opts
-from models.decode import mot_decode
-from utils.post_process import ctdet_post_process
-from models.model import create_model, load_model
+from src.lib.tracking_utils.utils import mkdir_if_missing
+from src.lib.opts import opts
+from src.lib.models.decode import mot_decode
+from src.lib.utils.post_process import ctdet_post_process
+from src.lib.models.model import create_model, load_model
 
 
 def write_results_score(filename, results):

src/detection_demo.py

@@ -2,7 +2,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
 import argparse
 import torch
 import json
@@ -12,12 +11,12 @@
 
 import numpy as np
 import torch.nn.functional as F
-import datasets.dataset.jde as datasets
+import src.lib.datasets.dataset.jde as datasets
 from torchvision.transforms import transforms as T
-from models.model import create_model, load_model
-from models.decode import mot_decode
-from models.utils import _tranpose_and_gather_feat
-from utils.post_process import ctdet_post_process
+from src.lib.models.model import create_model, load_model
+from src.lib.models.decode import mot_decode
+from src.lib.models.utils import _tranpose_and_gather_feat
+from src.lib.utils.post_process import ctdet_post_process
 
 
 max_per_image = 500

src/gen_data_path.py

@@ -1,6 +1,5 @@
 import os
 import glob
-import _init_paths
 
 
 def gen_caltech_path(root_path):

src/lib/datasets/dataset/jde.py

@@ -15,9 +15,9 @@
 from torch.utils.data import Dataset
 from torchvision.transforms import transforms as T
 from cython_bbox import bbox_overlaps as bbox_ious
-from opts import opts
-from utils.image import gaussian_radius, draw_umich_gaussian, draw_msra_gaussian
-from utils.utils import xyxy2xywh, generate_anchors, xywh2xyxy, encode_delta
+from src.lib.opts import opts
+from src.lib.utils.image import gaussian_radius, draw_umich_gaussian, draw_msra_gaussian
+from src.lib.utils.utils import xyxy2xywh, generate_anchors, xywh2xyxy, encode_delta
 
 
 class LoadImages:  # for inference

src/lib/datasets/dataset/jde_yolov5.py

@@ -15,9 +15,9 @@
 from torch.utils.data import Dataset
 from torchvision.transforms import transforms as T
 from cython_bbox import bbox_overlaps as bbox_ious
-from opts import opts
-from utils.image import gaussian_radius, draw_umich_gaussian, draw_msra_gaussian
-from utils.utils import xyxy2xywh, generate_anchors, xywh2xyxy, encode_delta
+from src.lib.opts import opts
+from src.lib.utils.image import gaussian_radius, draw_umich_gaussian, draw_msra_gaussian
+from src.lib.utils.utils import xyxy2xywh, generate_anchors, xywh2xyxy, encode_delta
 
 
 class LoadImages:  # for inference

src/lib/tracker/matching.py

@@ -5,7 +5,7 @@
 from scipy.spatial.distance import cdist
 
 from cython_bbox import bbox_overlaps as bbox_ious
-from tracking_utils import kalman_filter
+from src.lib.tracking_utils import kalman_filter
 import time
 
 def merge_matches(m1, m2, shape):

src/lib/tracker/multitracker.py

@@ -8,17 +8,17 @@
 import numpy as np
 import torch
 import torch.nn.functional as F
-from models import *
-from models.decode import mot_decode
-from models.model import create_model, load_model
-from models.utils import _tranpose_and_gather_feat
-from tracking_utils.kalman_filter import KalmanFilter
-from tracking_utils.log import logger
-from tracking_utils.utils import *
-from utils.image import get_affine_transform
-from utils.post_process import ctdet_post_process
-
-from tracker import matching
+from src.lib.models import *
+from src.lib.models.decode import mot_decode
+from src.lib.models.model import create_model, load_model
+from src.lib.models.utils import _tranpose_and_gather_feat
+from src.lib.tracking_utils.kalman_filter import KalmanFilter
+from src.lib.tracking_utils.log import logger
+from src.lib.tracking_utils.utils import *
+from src.lib.utils.image import get_affine_transform
+from src.lib.utils.post_process import ctdet_post_process
+
+from src.lib.tracker import matching
 
 from .basetrack import BaseTrack, TrackState
 

src/lib/tracking_utils/evaluation.py

@@ -4,7 +4,7 @@
 import motmetrics as mm
 mm.lap.default_solver = 'lap'
 
-from tracking_utils.io import read_results, unzip_objs
+from src.lib.tracking_utils.io import read_results, unzip_objs
 
 
 class Evaluator(object):

src/lib/tracking_utils/io.py

@@ -2,7 +2,7 @@
 from typing import Dict
 import numpy as np
 
-from tracking_utils.log import logger
+from src.lib.tracking_utils.log import logger
 
 
 def write_results(filename, results_dict: Dict, data_type: str):

src/lib/tracking_utils/nms.py

@@ -1,6 +1,6 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
 # from ._utils import _C
-from tracking_utils import _C
+from src.lib.tracking_utils import _C
 
 nms = _C.nms
 # nms.__doc__ = """

src/lib/trains/base_trainer.py

@@ -5,8 +5,8 @@
 import time
 import torch
 from progress.bar import Bar
-from models.data_parallel import DataParallel
-from utils.utils import AverageMeter
+from src.lib.models.data_parallel import DataParallel
+from src.lib.utils.utils import AverageMeter
 
 
 class ModleWithLoss(torch.nn.Module):

src/lib/trains/mot.py

@@ -11,11 +11,11 @@
 
 from fvcore.nn import sigmoid_focal_loss_jit
 
-from models.losses import FocalLoss, TripletLoss
-from models.losses import RegL1Loss, RegLoss, NormRegL1Loss, RegWeightedL1Loss
-from models.decode import mot_decode
-from models.utils import _sigmoid, _tranpose_and_gather_feat
-from utils.post_process import ctdet_post_process
+from src.lib.models.losses import FocalLoss, TripletLoss
+from src.lib.models.losses import RegL1Loss, RegLoss, NormRegL1Loss, RegWeightedL1Loss
+from src.lib.models.decode import mot_decode
+from src.lib.models.utils import _sigmoid, _tranpose_and_gather_feat
+from src.lib.utils.post_process import ctdet_post_process
 from .base_trainer import BaseTrainer
 
 

src/test_det.py

@@ -2,7 +2,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
 import argparse
 import torch
 import json
@@ -14,12 +13,12 @@
 from scipy import interpolate
 import numpy as np
 from torchvision.transforms import transforms as T
-from models.model import create_model, load_model
-from datasets.dataset.jde import DetDataset, collate_fn
-from utils.utils import xywh2xyxy, ap_per_class, bbox_iou
-from opts import opts
-from models.decode import mot_decode
-from utils.post_process import ctdet_post_process
+from src.lib.models.model import create_model, load_model
+from src.lib.datasets.dataset.jde import DetDataset, collate_fn
+from src.lib.utils.utils import xywh2xyxy, ap_per_class, bbox_iou
+from src.lib.opts import opts
+from src.lib.models.decode import mot_decode
+from src.lib.utils.post_process import ctdet_post_process
 
 
 def post_process(opt, dets, meta):

src/test_emb.py

@@ -2,7 +2,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
 import argparse
 import torch
 import json
@@ -16,13 +15,13 @@
 import numpy as np
 from torchvision.transforms import transforms as T
 import torch.nn.functional as F
-from models.model import create_model, load_model
-from datasets.dataset.jde import JointDataset, collate_fn
-from models.utils import _tranpose_and_gather_feat
-from utils.utils import xywh2xyxy, ap_per_class, bbox_iou
-from opts import opts
-from models.decode import mot_decode
-from utils.post_process import ctdet_post_process
+from src.lib.models.model import create_model, load_model
+from src.lib.datasets.dataset.jde import JointDataset, collate_fn
+from src.lib.models.utils import _tranpose_and_gather_feat
+from src.lib.utils.utils import xywh2xyxy, ap_per_class, bbox_iou
+from src.lib.opts import opts
+from src.lib.models.decode import mot_decode
+from src.lib.utils.post_process import ctdet_post_process
 
 
 def test_emb(

src/track.py

@@ -2,7 +2,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
 import os
 import os.path as osp
 import cv2
@@ -12,15 +11,15 @@
 import numpy as np
 import torch
 
-from tracker.multitracker import JDETracker
-from tracking_utils import visualization as vis
-from tracking_utils.log import logger
-from tracking_utils.timer import Timer
-from tracking_utils.evaluation import Evaluator
-import datasets.dataset.jde as datasets
+from src.lib.tracker.multitracker import JDETracker
+from src.lib.tracking_utils import visualization as vis
+from src.lib.tracking_utils.log import logger
+from src.lib.tracking_utils.timer import Timer
+from src.lib.tracking_utils.evaluation import Evaluator
+import src.lib.datasets.dataset.jde as datasets
 
-from tracking_utils.utils import mkdir_if_missing
-from opts import opts
+from src.lib.tracking_utils.utils import mkdir_if_missing
+from src.lib.opts import opts
 
 
 def write_results(filename, results, data_type):

src/track_half.py

@@ -2,7 +2,6 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
 import os
 import os.path as osp
 import cv2
@@ -12,15 +11,15 @@
 import numpy as np
 import torch
 
-from tracker.multitracker import JDETracker
-from tracking_utils import visualization as vis
-from tracking_utils.log import logger
-from tracking_utils.timer import Timer
-from tracking_utils.evaluation import Evaluator
-import datasets.dataset.jde as datasets
+from src.lib.tracker.multitracker import JDETracker
+from src.lib.tracking_utils import visualization as vis
+from src.lib.tracking_utils.log import logger
+from src.lib.tracking_utils.timer import Timer
+from src.lib.tracking_utils.evaluation import Evaluator
+import src.lib.datasets.dataset.jde as datasets
 
-from tracking_utils.utils import mkdir_if_missing
-from opts import opts
+from src.lib.tracking_utils.utils import mkdir_if_missing
+from src.lib.opts import opts
 
 
 def write_results(filename, results, data_type):

src/train.py

@@ -2,20 +2,18 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
-
 import os
 
 import json
 import torch
 import torch.utils.data
 from torchvision.transforms import transforms as T
-from opts import opts
-from models.model import create_model, load_model, save_model
-from models.data_parallel import DataParallel
-from logger import Logger
-from datasets.dataset_factory import get_dataset
-from trains.train_factory import train_factory
+from src.lib.opts import opts
+from src.lib.models.model import create_model, load_model, save_model
+from src.lib.models.data_parallel import DataParallel
+from src.lib.logger import Logger
+from src.lib.datasets.dataset_factory import get_dataset
+from src.lib.trains.train_factory import train_factory
 
 
 def main(opt):