Kaynağa Gözat

Update `dataset_stats()` (#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)
```
modifyDataloader
Glenn Jocher GitHub 3 yıl önce
ebeveyn
işleme
7a565f130a
Veri tabanında bu imza için bilinen anahtar bulunamadı GPC Anahtar Kimliği: 4AEE18F83AFDEB23
1 değiştirilmiş dosya ile 12 ekleme ve 3 silme
  1. +12
    -3
      utils/datasets.py

+ 12
- 3
utils/datasets.py Dosyayı Görüntüle

@@ -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

Yükleniyor…
İptal
Kaydet