Update train, val tqdm to fixed width (#5367)

* Update tqdm for fixed width

* Update val.py

* Update val.py

* Try ncols= in train.py

* NCOLS

* NCOLS

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* bar_format

* position 0 leave true

* exp0

* auto

* auto

* Cleanup

* Cleanup

* Cleanup

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

val.py

@@ -26,7 +26,7 @@ ROOT = Path(os.path.relpath(ROOT, Path.cwd()))  # relative
 from models.common import DetectMultiBackend
 from utils.callbacks import Callbacks
 from utils.datasets import create_dataloader
-from utils.general import (LOGGER, box_iou, check_dataset, check_img_size, check_requirements, check_yaml,
+from utils.general import (LOGGER, NCOLS, box_iou, check_dataset, check_img_size, check_requirements, check_yaml,
                            coco80_to_coco91_class, colorstr, increment_path, non_max_suppression, print_args,
                            scale_coords, xywh2xyxy, xyxy2xywh)
 from utils.metrics import ConfusionMatrix, ap_per_class
@@ -162,7 +162,8 @@ def run(data,
     dt, p, r, f1, mp, mr, map50, map = [0.0, 0.0, 0.0], 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
     loss = torch.zeros(3, device=device)
     jdict, stats, ap, ap_class = [], [], [], []
-    for batch_i, (im, targets, paths, shapes) in enumerate(tqdm(dataloader, desc=s)):
+    pbar = tqdm(dataloader, desc=s, ncols=NCOLS, bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}')  # progress bar
+    for batch_i, (im, targets, paths, shapes) in enumerate(pbar):
         t1 = time_sync()
         if pt:
             im = im.to(device, non_blocking=True)