Use `tqdm.auto` (#7311)

data/Argoverse.yaml

@@ -22,7 +22,7 @@ names: ['person',  'bicycle',  'car',  'motorcycle',  'bus',  'truck',  'traffic
 download: |
   import json
 
-  from tqdm import tqdm
+  from tqdm.auto import tqdm
   from utils.general import download, Path
 
 

data/Objects365.yaml

@@ -60,7 +60,7 @@ names: ['Person', 'Sneakers', 'Chair', 'Other Shoes', 'Hat', 'Car', 'Lamp', 'Gla
 
 # Download script/URL (optional) ---------------------------------------------------------------------------------------
 download: |
-  from tqdm import tqdm
+  from tqdm.auto import tqdm
 
   from utils.general import Path, check_requirements, download, np, xyxy2xywhn
 

data/SKU-110K.yaml

@@ -21,7 +21,7 @@ names: ['object']  # class names
 # Download script/URL (optional) ---------------------------------------------------------------------------------------
 download: |
   import shutil
-  from tqdm import tqdm
+  from tqdm.auto import tqdm
   from utils.general import np, pd, Path, download, xyxy2xywh
 
 

data/VOC.yaml

@@ -29,7 +29,7 @@ names: ['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', '
 download: |
   import xml.etree.ElementTree as ET
 
-  from tqdm import tqdm
+  from tqdm.auto import tqdm
   from utils.general import download, Path
 
 

data/VisDrone.yaml

@@ -24,7 +24,7 @@ download: |
 
   def visdrone2yolo(dir):
       from PIL import Image
-      from tqdm import tqdm
+      from tqdm.auto import tqdm
 
       def convert_box(size, box):
           # Convert VisDrone box to YOLO xywh box

data/xView.yaml

@@ -34,7 +34,7 @@ download: |
 
   import numpy as np
   from PIL import Image
-  from tqdm import tqdm
+  from tqdm.auto import tqdm
 
   from utils.datasets import autosplit
   from utils.general import download, xyxy2xywhn

train.py

@@ -30,7 +30,7 @@ import yaml
 from torch.cuda import amp
 from torch.nn.parallel import DistributedDataParallel as DDP
 from torch.optim import SGD, Adam, AdamW, lr_scheduler
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
 FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # YOLOv5 root directory

utils/autoanchor.py

@@ -8,7 +8,7 @@ import random
 import numpy as np
 import torch
 import yaml
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
 from utils.general import LOGGER, colorstr, emojis
 

utils/datasets.py

@@ -24,7 +24,7 @@ import torch.nn.functional as F
 import yaml
 from PIL import ExifTags, Image, ImageOps
 from torch.utils.data import DataLoader, Dataset, dataloader, distributed
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
 from utils.augmentations import Albumentations, augment_hsv, copy_paste, letterbox, mixup, random_perspective
 from utils.general import (DATASETS_DIR, LOGGER, NUM_THREADS, check_dataset, check_requirements, check_yaml, clean_str,

utils/loggers/wandb/wandb_utils.py

@@ -8,7 +8,7 @@ from pathlib import Path
 from typing import Dict
 
 import yaml
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
 FILE = Path(__file__).resolve()
 ROOT = FILE.parents[3]  # YOLOv5 root directory

val.py

@@ -27,7 +27,7 @@ from threading import Thread
 
 import numpy as np
 import torch
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
 FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # YOLOv5 root directory