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Simplify dataloader tqdm descriptions (#10210) 

* Simplify dataloader tqdm descriptions

@AyushExel this should help our tqdm dataloader messages fit better within a single line in our Colab notebooks and also help avoid confusion about missing/empty labels, now combined into 'backgrounds'.

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

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

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

* Update dataloaders.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
pull/10211/head
Glenn Jocher 2022-11-18 21:18:57 +01:00 committed by GitHub
parent 946765bbc3
commit 74b3886edd
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1 changed files with 5 additions and 5 deletions
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10
utils/dataloaders.py
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@ -31,8 +31,8 @@ from tqdm import tqdm
from utils.augmentations import (Albumentations, augment_hsv, classify_albumentations, classify_transforms, copy_paste,
cutout, letterbox, mixup, random_perspective)
from utils.general import (DATASETS_DIR, LOGGER, NUM_THREADS, check_dataset, check_requirements, check_yaml, clean_str,
colorstr, cv2, is_colab, is_kaggle, segments2boxes, unzip_file, xyn2xy, xywh2xyxy,
xywhn2xyxy, xyxy2xywhn)
cv2, is_colab, is_kaggle, segments2boxes, unzip_file, xyn2xy, xywh2xyxy, xywhn2xyxy,
xyxy2xywhn)
from utils.torch_utils import torch_distributed_zero_first
# Parameters
@ -493,7 +493,7 @@ class LoadImagesAndLabels(Dataset):
# Display cache
nf, nm, ne, nc, n = cache.pop('results') # found, missing, empty, corrupt, total
if exists and LOCAL_RANK in {-1, 0}:
d = f"Scanning '{cache_path}' images and labels... {nf} found, {nm} missing, {ne} empty, {nc} corrupt"
d = f"Scanning {cache_path}... {nf} images, {nm + ne} backgrounds, {nc} corrupt"
tqdm(None, desc=prefix + d, total=n, initial=n, bar_format=BAR_FORMAT) # display cache results
if cache['msgs']:
LOGGER.info('\n'.join(cache['msgs'])) # display warnings
@ -607,7 +607,7 @@ class LoadImagesAndLabels(Dataset):
# Cache dataset labels, check images and read shapes
x = {} # dict
nm, nf, ne, nc, msgs = 0, 0, 0, 0, [] # number missing, found, empty, corrupt, messages
desc = f"{prefix}Scanning '{path.parent / path.stem}' images and labels..."
desc = f"{prefix}Scanning {path.parent / path.stem}..."
with Pool(NUM_THREADS) as pool:
pbar = tqdm(pool.imap(verify_image_label, zip(self.im_files, self.label_files, repeat(prefix))),
desc=desc,
@ -622,7 +622,7 @@ class LoadImagesAndLabels(Dataset):
x[im_file] = [lb, shape, segments]
if msg:
msgs.append(msg)
pbar.desc = f"{desc}{nf} found, {nm} missing, {ne} empty, {nc} corrupt"
pbar.desc = f"{desc} {nf} images, {nm + ne} backgrounds, {nc} corrupt"
pbar.close()
if msgs: