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log_dataset.py 809B

Improved W&B integration (#2125) * Init Commit * new wandb integration * Update * Use data_dict in test * Updates * Update: scope of log_img * Update: scope of log_img * Update * Update: Fix logging conditions * Add tqdm bar, support for .txt dataset format * Improve Result table Logger * Init Commit * new wandb integration * Update * Use data_dict in test * Updates * Update: scope of log_img * Update: scope of log_img * Update * Update: Fix logging conditions * Add tqdm bar, support for .txt dataset format * Improve Result table Logger * Add dataset creation in training script * Change scope: self.wandb_run * Add wandb-artifact:// natively you can now use --resume with wandb run links * Add suuport for logging dataset while training * Cleanup * Fix: Merge conflict * Fix: CI tests * Automatically use wandb config * Fix: Resume * Fix: CI * Enhance: Using val_table * More resume enhancement * FIX : CI * Add alias * Get useful opt config data * train.py cleanup * Cleanup train.py * more cleanup * Cleanup| CI fix * Reformat using PEP8 * FIX:CI * rebase * remove uneccesary changes * remove uneccesary changes * remove uneccesary changes * remove unecessary chage from test.py * FIX: resume from local checkpoint * FIX:resume * FIX:resume * Reformat * Performance improvement * Fix local resume * Fix local resume * FIX:CI * Fix: CI * Imporve image logging * (:(:Redo CI tests:):) * Remember epochs when resuming * Remember epochs when resuming * Update DDP location Potential fix for #2405 * PEP8 reformat * 0.25 confidence threshold * reset train.py plots syntax to previous * reset epochs completed syntax to previous * reset space to previous * remove brackets * reset comment to previous * Update: is_coco check, remove unused code * Remove redundant print statement * Remove wandb imports * remove dsviz logger from test.py * Remove redundant change from test.py * remove redundant changes from train.py * reformat and improvements * Fix typo * Add tqdm tqdm progress when scanning files, naming improvements Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
3 anos atrás
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  1. import argparse
  2. from pathlib import Path
  3. import yaml
  4. from wandb_utils import WandbLogger
  5. from utils.datasets import LoadImagesAndLabels
  6. WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
  7. def create_dataset_artifact(opt):
  8. with open(opt.data) as f:
  9. data = yaml.load(f, Loader=yaml.SafeLoader) # data dict
  10. logger = WandbLogger(opt, '', None, data, job_type='Dataset Creation')
  11. if __name__ == '__main__':
  12. parser = argparse.ArgumentParser()
  13. parser.add_argument('--data', type=str, default='data/coco128.yaml', help='data.yaml path')
  14. parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
  15. parser.add_argument('--project', type=str, default='YOLOv5', help='name of W&B Project')
  16. opt = parser.parse_args()
  17. create_dataset_artifact(opt)