Improve classification comments (#8997)

classify/predict.py

@@ -3,7 +3,7 @@
 Run classification inference on images
 
 Usage:
-    $ python classify/predict.py --weights yolov5s-cls.pt --source im.jpg
+    $ python classify/predict.py --weights yolov5s-cls.pt --source data/images/bus.jpg
 """
 
 import argparse

classify/train.py

@@ -2,8 +2,10 @@
 """
 Train a YOLOv5 classifier model on a classification dataset
 Datasets: --data mnist, fashion-mnist, cifar10, cifar100, imagenette, imagewoof, imagenet, or 'path/to/custom/dataset'
+YOLOv5-cls models: --model yolov5n-cls.pt, yolov5s-cls.pt, yolov5m-cls.pt, yolov5l-cls.pt, yolov5x-cls.pt
+Torchvision models: --model resnet50, efficientnet_b0, etc. See https://pytorch.org/vision/stable/models.html
 
-Usage:
+Usage - Single-GPU and Multi-GPU DDP
     $ python classify/train.py --model yolov5s-cls.pt --data cifar100 --epochs 5 --img 128
     $ python -m torch.distributed.run --nproc_per_node 4 --master_port 1 classify/train.py --model yolov5s-cls.pt --data imagenet --epochs 5 --img 224 --device 0,1,2,3
 """

classify/val.py

@@ -3,7 +3,8 @@
 Validate a classification model on a dataset
 
 Usage:
-    $ python classify/val.py --weights yolov5s-cls.pt --data ../datasets/imagenet
+    $ bash data/scripts/get_imagenet.sh --val  # download ImageNet val split (6.3G, 50000 images)
+    $ python classify/val.py --weights yolov5m-cls.pt --data ../datasets/imagenet --img 224  # validate
 """
 
 import argparse