Start setup for improved W&B integration (#1948)

* Add helper functions for wandb and artifacts * cleanup * Reorganize files * Update wandb_utils.py * Update log_dataset.py We can remove this code, as the giou hyp has been deprecated for a while now. * Reorganize and update dataloader call * yaml.SafeLoader * PEP8 reformat * remove redundant checks * Add helper functions for wandb and artifacts * cleanup * Reorganize files * Update wandb_utils.py * Update log_dataset.py We can remove this code, as the giou hyp has been deprecated for a while now. * Reorganize and update dataloader call * yaml.SafeLoader * PEP8 reformat * remove redundant checks * Update util files * Update wandb_utils.py * Remove word size * Change path of labels.zip * remove unused imports * remove --rect * log_dataset.py cleanup * log_dataset.py cleanup2 * wandb_utils.py cleanup * remove redundant id_count * wandb_utils.py cleanup2 * rename cls * use pathlib for zip * rename dataloader to dataset * Change import order * Remove redundant code * remove unused import * remove unused imports Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
2021-02-01 21:38:41 -08:00
1 parent 9646ca438a
commit 73a0669930
@@ -0,0 +1,39 @@
+import argparse
+from pathlib import Path
+
+import yaml
+
+from wandb_utils import WandbLogger
+from utils.datasets import LoadImagesAndLabels
+
+WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
+
+
+def create_dataset_artifact(opt):
+    with open(opt.data) as f:
+        data = yaml.load(f, Loader=yaml.SafeLoader)  # data dict
+    logger = WandbLogger(opt, '', None, data, job_type='create_dataset')
+    nc, names = (1, ['item']) if opt.single_cls else (int(data['nc']), data['names'])
+    names = {k: v for k, v in enumerate(names)}  # to index dictionary
+    logger.log_dataset_artifact(LoadImagesAndLabels(data['train']), names, name='train')  # trainset
+    logger.log_dataset_artifact(LoadImagesAndLabels(data['val']), names, name='val')  # valset
+
+    # Update data.yaml with artifact links
+    data['train'] = WANDB_ARTIFACT_PREFIX + str(Path(opt.project) / 'train')
+    data['val'] = WANDB_ARTIFACT_PREFIX + str(Path(opt.project) / 'val')
+    path = opt.data if opt.overwrite_config else opt.data.replace('.', '_wandb.')  # updated data.yaml path
+    data.pop('download', None)  # download via artifact instead of predefined field 'download:'
+    with open(path, 'w') as f:
+        yaml.dump(data, f)
+    print("New Config file => ", path)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--data', type=str, default='data/coco128.yaml', help='data.yaml path')
+    parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
+    parser.add_argument('--project', type=str, default='YOLOv5', help='name of W&B Project')
+    parser.add_argument('--overwrite_config', action='store_true', help='overwrite data.yaml')
+    opt = parser.parse_args()
+
+    create_dataset_artifact(opt)