Update dataset_stats() (ultralytics#3593)

@kalenmike this is a PR to add image filenames and labels to our stats dictionary and to save the dictionary to JSON. Save location is next to the train labels.cache file. The single JSON contains all stats for entire dataset.

Usage example:
```python
from utils.datasets import *

dataset_stats('coco128.yaml', verbose=True)
```

utils/datasets.py

@@ -2,6 +2,7 @@
 
 import glob
 import hashlib
+import json
 import logging
 import math
 import os
@@ -1105,12 +1106,20 @@ def dataset_stats(path='coco128.yaml', autodownload=False, verbose=False):
             continue
         x = []
         dataset = LoadImagesAndLabels(data[split], augment=False, rect=True)  # load dataset
+        if split == 'train':
+            cache_path = Path(dataset.label_files[0]).parent.with_suffix('.cache')  # *.cache path
         for label in tqdm(dataset.labels, total=dataset.n, desc='Statistics'):
             x.append(np.bincount(label[:, 0].astype(int), minlength=nc))
         x = np.array(x)  # shape(128x80)
-        stats[split] = {'instances': {'total': int(x.sum()), 'per_class': x.sum(0).tolist()},
-                        'images': {'total': dataset.n, 'unlabelled': int(np.all(x == 0, 1).sum()),
-                                   'per_class': (x > 0).sum(0).tolist()}}
+        stats[split] = {'instance_stats': {'total': int(x.sum()), 'per_class': x.sum(0).tolist()},
+                        'image_stats': {'total': dataset.n, 'unlabelled': int(np.all(x == 0, 1).sum()),
+                                        'per_class': (x > 0).sum(0).tolist()},
+                        'labels': {str(Path(k).name): v.tolist() for k, v in zip(dataset.img_files, dataset.labels)}}
+
+    # Save, print and return
+    with open(cache_path.with_suffix('.json'), 'w') as f:
+        json.dump(stats, f)  # save stats *.json
     if verbose:
         print(yaml.dump([stats], sort_keys=False, default_flow_style=False))
+        # print(json.dumps(stats, indent=2, sort_keys=False))
     return stats