update dataset comments

data/coco.yaml

@@ -1,13 +1,13 @@
 # COCO 2017 dataset http://cocodataset.org
 # Download command: bash yolov5/data/get_coco2017.sh
-# Train command: python train.py --data ./data/coco.yaml
-# Dataset should be placed next to yolov5 folder:
+# Train command: python train.py --data coco.yaml
+# Default dataset location is next to /yolov5:
 #   /parent_folder
 #     /coco
 #     /yolov5
 
 
-# train and val datasets (image directory or *.txt file with image paths)
+# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
 train: ../coco/train2017.txt  # 118k images
 val: ../coco/val2017.txt  # 5k images
 test: ../coco/test-dev2017.txt  # 20k images for submission to https://competitions.codalab.org/competitions/20794

data/coco128.yaml

@@ -1,15 +1,15 @@
 # COCO 2017 dataset http://cocodataset.org - first 128 training images
-# Download command:  python -c "from yolov5.utils.google_utils import gdrive_download; gdrive_download('1n_oKgR81BJtqk75b00eAjdv03qVCQn2f','coco128.zip')"
-# Train command: python train.py --data ./data/coco128.yaml
-# Dataset should be placed next to yolov5 folder:
+# Download command:  python -c "from yolov5.utils.google_utils import *; gdrive_download('1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', 'coco128.zip')"
+# Train command: python train.py --data coco128.yaml
+# Default dataset location is next to /yolov5:
 #   /parent_folder
 #     /coco128
 #     /yolov5
 
 
-# train and val datasets (image directory or *.txt file with image paths)
-train: ../coco128/images/train2017/
-val: ../coco128/images/train2017/
+# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
+train: ../coco128/images/train2017/  # 128 images
+val: ../coco128/images/train2017/  # 128 images
 
 # number of classes
 nc: 80

data/get_coco2017.sh

@@ -1,12 +1,13 @@
 #!/bin/bash
 # COCO 2017 dataset http://cocodataset.org
 # Download command: bash yolov5/data/get_coco2017.sh
-# Train command: python train.py --data ./data/coco.yaml
-# Dataset should be placed next to yolov5 folder:
+# Train command: python train.py --data coco.yaml
+# Default dataset location is next to /yolov5:
 #   /parent_folder
 #     /coco
 #     /yolov5
 
+
 # Download labels from Google Drive, accepting presented query
 filename="coco2017labels.zip"
 fileid="1cXZR_ckHki6nddOmcysCuuJFM--T-Q6L"

data/get_voc.sh

@@ -1,11 +1,12 @@
 # PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC/
 # Download command: bash ./data/get_voc.sh
 # Train command: python train.py --data voc.yaml
-# Dataset should be placed next to yolov5 folder:
+# Default dataset location is next to /yolov5:
 #   /parent_folder
 #     /VOC
 #     /yolov5
 
+
 start=`date +%s`
 
 # handle optional download dir

data/voc.yaml

@@ -1,14 +1,15 @@
 # PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC/
 # Download command: bash ./data/get_voc.sh
 # Train command: python train.py --data voc.yaml
-# Dataset should be placed next to yolov5 folder:
+# Default dataset location is next to /yolov5:
 #   /parent_folder
 #     /VOC
 #     /yolov5
 
-# train and val datasets (image directory or *.txt file with image paths)
-train: ../VOC/images/train/
-val: ../VOC/images/val/
+
+# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
+train: ../VOC/images/train/  # 16551 images
+val: ../VOC/images/val/  # 4952 images
 
 # number of classes
 nc: 20