Update file train.py

yolov5/train.py

@@ -469,7 +469,7 @@ def parse_opt(known=False):
     parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)')
     parser.add_argument('--seed', type=int, default=0, help='Global training seed')
     parser.add_argument('--local_rank', type=int, default=-1, help='Automatic DDP Multi-GPU argument, do not modify')
-    parser.add_argument('--sr', type=str, default='', help='If sound, give the samplerate of the spectrogram')
+    parser.add_argument('--rf', type=str, default='', help='If sound, give the samplerate of the spectrogram')
     parser.add_argument('--duration', type=str, default='', help='If sound, give the duration of the spectrogram')
 
     # Logger arguments
@@ -514,7 +514,7 @@ def main(opt, callbacks=Callbacks()):
             opt.name = Path(opt.cfg).stem  # use model.yaml as name
         project_name = input('Please enter the name of your project : ')
         date_now = date.today().strftime("%Y%m%d")
-        folder_name = '_'.join([project_name, date_now, opt.weights[-4:-3], str(opt.imgsz), opt.optimizer, opt.sr, opt.duration, 'YOLOV5',])
+        folder_name = '_'.join([project_name, date_now, opt.weights[-4:-3], str(opt.imgsz), opt.optimizer, opt.rf, opt.duration, 'YOLOV5',])
         print(f'Your train results will be saved in {folder_name}')
 
         opt.save_dir = str(increment_path(Path(opt.project) / folder_name, exist_ok=opt.exist_ok))