Improved non-latin Annotator() plotting (#7488)

* Improved non-latin labels Annotator plotting

May resolve https://github.com/ultralytics/yolov5/issues/7460

* Update train.py

* Update train.py

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* add progress arg

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train.py

@@ -48,13 +48,13 @@ from utils.datasets import create_dataloader
 from utils.downloads import attempt_download
 from utils.general import (LOGGER, check_dataset, check_file, check_git_status, check_img_size, check_requirements,
                            check_suffix, check_yaml, colorstr, get_latest_run, increment_path, init_seeds,
-                           intersect_dicts, labels_to_class_weights, labels_to_image_weights, methods, one_cycle,
-                           print_args, print_mutation, strip_optimizer)
+                           intersect_dicts, is_ascii, labels_to_class_weights, labels_to_image_weights, methods,
+                           one_cycle, print_args, print_mutation, strip_optimizer)
 from utils.loggers import Loggers
 from utils.loggers.wandb.wandb_utils import check_wandb_resume
 from utils.loss import ComputeLoss
 from utils.metrics import fitness
-from utils.plots import plot_evolve, plot_labels
+from utils.plots import check_font, plot_evolve, plot_labels
 from utils.torch_utils import EarlyStopping, ModelEMA, de_parallel, select_device, torch_distributed_zero_first
 
 LOCAL_RANK = int(os.getenv('LOCAL_RANK', -1))  # https://pytorch.org/docs/stable/elastic/run.html
@@ -105,6 +105,8 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
     init_seeds(1 + RANK)
     with torch_distributed_zero_first(LOCAL_RANK):
         data_dict = data_dict or check_dataset(data)  # check if None
+        if not is_ascii(data_dict['names']):  # non-latin labels, i.e. asian, arabic, cyrillic
+            check_font('Arial.Unicode.ttf', progress=True)
     train_path, val_path = data_dict['train'], data_dict['val']
     nc = 1 if single_cls else int(data_dict['nc'])  # number of classes
     names = ['item'] if single_cls and len(data_dict['names']) != 1 else data_dict['names']  # class names