Simplify check_requirements() usage (#4855)

* Simplify `check_requirements()` usage

* remove assert, print()

detect.py

@@ -286,7 +286,7 @@ def parse_opt():
 
 
 def main(opt):
-    check_requirements(requirements=ROOT / 'requirements.txt', exclude=('tensorboard', 'thop'))
+    check_requirements(exclude=('tensorboard', 'thop'))
     run(**vars(opt))
 
 

hubconf.py

@@ -34,7 +34,7 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
     from utils.torch_utils import select_device
 
     file = Path(__file__).resolve()
-    check_requirements(requirements=file.parent / 'requirements.txt', exclude=('tensorboard', 'thop', 'opencv-python'))
+    check_requirements(exclude=('tensorboard', 'thop', 'opencv-python'))
     set_logging(verbose=verbose)
 
     save_dir = Path('') if str(name).endswith('.pt') else file.parent

train.py

@@ -476,7 +476,7 @@ def main(opt, callbacks=Callbacks()):
     if RANK in [-1, 0]:
         print_args(FILE.stem, opt)
         check_git_status()
-        check_requirements(requirements=ROOT / 'requirements.txt', exclude=['thop'])
+        check_requirements(exclude=['thop'])
 
     # Resume
     if opt.resume and not check_wandb_resume(opt) and not opt.evolve:  # resume an interrupted run

utils/autoanchor.py

@@ -127,7 +127,7 @@ def kmean_anchors(dataset='./data/coco128.yaml', n=9, img_size=640, thr=4.0, gen
     print(f'{prefix}Running kmeans for {n} anchors on {len(wh)} points...')
     s = wh.std(0)  # sigmas for whitening
     k, dist = kmeans(wh / s, n, iter=30)  # points, mean distance
-    assert len(k) == n, print(f'{prefix}ERROR: scipy.cluster.vq.kmeans requested {n} points but returned only {len(k)}')
+    assert len(k) == n, f'{prefix}ERROR: scipy.cluster.vq.kmeans requested {n} points but returned only {len(k)}'
     k *= s
     wh = torch.tensor(wh, dtype=torch.float32)  # filtered
     wh0 = torch.tensor(wh0, dtype=torch.float32)  # unfiltered

utils/general.py

@@ -37,6 +37,9 @@ pd.options.display.max_columns = 10
 cv2.setNumThreads(0)  # prevent OpenCV from multithreading (incompatible with PyTorch DataLoader)
 os.environ['NUMEXPR_MAX_THREADS'] = str(min(os.cpu_count(), 8))  # NumExpr max threads
 
+FILE = Path(__file__).resolve()
+ROOT = FILE.parents[1]  # YOLOv5 root directory
+
 
 class Profile(contextlib.ContextDecorator):
     # Usage: @Profile() decorator or 'with Profile():' context manager
@@ -222,7 +225,7 @@ def check_version(current='0.0.0', minimum='0.0.0', name='version ', pinned=Fals
 
 
 @try_except
-def check_requirements(requirements='requirements.txt', exclude=(), install=True):
+def check_requirements(requirements=ROOT / 'requirements.txt', exclude=(), install=True):
     # Check installed dependencies meet requirements (pass *.txt file or list of packages)
     prefix = colorstr('red', 'bold', 'requirements:')
     check_python()  # check python version

val.py

@@ -327,7 +327,7 @@ def parse_opt():
 
 def main(opt):
     set_logging()
-    check_requirements(requirements=ROOT / 'requirements.txt', exclude=('tensorboard', 'thop'))
+    check_requirements(exclude=('tensorboard', 'thop'))
 
     if opt.task in ('train', 'val', 'test'):  # run normally
         run(**vars(opt))