Replace `path.absolute()` with `path.resolve()` (#4763)

detect.py

@@ -15,7 +15,7 @@ import numpy as np
 import torch
 import torch.backends.cudnn as cudnn
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[0].as_posix())  # add yolov5/ to path
 
 from models.experimental import attempt_load

export.py

@@ -15,7 +15,7 @@ import torch
 import torch.nn as nn
 from torch.utils.mobile_optimizer import optimize_for_mobile
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[0].as_posix())  # add yolov5/ to path
 
 from models.common import Conv

hubconf.py

@@ -33,7 +33,7 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
     from utils.downloads import attempt_download
     from utils.torch_utils import select_device
 
-    file = Path(__file__).absolute()
+    file = Path(__file__).resolve()
     check_requirements(requirements=file.parent / 'requirements.txt', exclude=('tensorboard', 'thop', 'opencv-python'))
     set_logging(verbose=verbose)
 

models/yolo.py

@@ -11,7 +11,7 @@ import sys
 from copy import deepcopy
 from pathlib import Path
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[1].as_posix())  # add yolov5/ to path
 
 from models.common import *

train.py

@@ -26,7 +26,7 @@ from torch.nn.parallel import DistributedDataParallel as DDP
 from torch.optim import Adam, SGD, lr_scheduler
 from tqdm import tqdm
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[0].as_posix())  # add yolov5/ to path
 
 import val  # for end-of-epoch mAP

utils/__init__.py

@@ -4,7 +4,7 @@
 # import torch
 # from PIL import ImageFont
 #
-# FILE = Path(__file__).absolute()
+# FILE = Path(__file__).resolve()
 # ROOT = FILE.parents[1]  # yolov5/ dir
 # if str(ROOT) not in sys.path:
 #     sys.path.append(str(ROOT))  # add ROOT to PATH

utils/datasets.py

@@ -156,7 +156,7 @@ class _RepeatSampler(object):
 
 class LoadImages:  # for inference
     def __init__(self, path, img_size=640, stride=32, auto=True):
-        p = str(Path(path).absolute())  # os-agnostic absolute path
+        p = str(Path(path).resolve())  # os-agnostic absolute path
         if '*' in p:
             files = sorted(glob.glob(p, recursive=True))  # glob
         elif os.path.isdir(p):

utils/general.py

@@ -147,7 +147,7 @@ def is_colab():
 
 def is_pip():
     # Is file in a pip package?
-    return 'site-packages' in Path(__file__).absolute().parts
+    return 'site-packages' in Path(__file__).resolve().parts
 
 
 def is_ascii(s=''):

utils/loggers/wandb/sweep.py

@@ -3,7 +3,7 @@ from pathlib import Path
 
 import wandb
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[3].as_posix())  # add utils/ to path
 
 from train import train, parse_opt

utils/loggers/wandb/wandb_utils.py

@@ -9,7 +9,7 @@ from pathlib import Path
 import yaml
 from tqdm import tqdm
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[3].as_posix())  # add yolov5/ to path
 
 from utils.datasets import LoadImagesAndLabels

val.py

@@ -17,7 +17,7 @@ import numpy as np
 import torch
 from tqdm import tqdm
 
-FILE = Path(__file__).absolute()
+FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[0].as_posix())  # add yolov5/ to path
 
 from models.experimental import attempt_load