The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7fe70b0ae690>'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/xml/xml.py", line 67, in _generate_tables
with open(file, encoding=self.config.encoding, errors=self.config.encoding_errors) as f:
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 967, in xopen
return open(main_hop, mode, *args, **kwargs)
FileNotFoundError: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7fe70b0ae690>'Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
tags: - object-detection - computer-vision - yolo - utility-meters - ocr - digit-recognition - energy - smart-grid - iot pretty_name: Annotated Mechanical Utility Meter Dials Dataset task_categories: - object-detection size_categories: - 10K<n<100K
📊 Annotated Mechanical Utility Meter Dials Dataset
Solve the "half-digit" problem in automated meter reading.
16,324 expertly labeled images of mechanical utility meters, captured in real-world, in-the-wild conditions across water, gas, electricity, and heat meters from 100+ European manufacturers.
🔍 This is a preview / sample listing. The full dataset, plus a free bonus pre-trained model, is available at utilitymeters.ai.
Dataset Summary
Legacy Automated Meter Reading (AMR) systems rarely fail on clean, static digits — they fail on analog wheels caught mid-rotation. This dataset was purpose-built to close that gap, with dedicated annotation classes for rolling-digit transition states in addition to standard digits.
Key features:
| 🧩 Spinning-drum coverage | 10 dedicated rolling-digit classes (0_1 → 9_0) teach models to resolve overlapping intermediate wheel states |
| 🌍 True in-the-wild robustness | Low basement lighting, flash glare on glass covers, extreme viewing angles, scratched/cracked/dirty devices |
| 🏭 Cross-brand generalization | 100+ European hardware brands prevent overfitting to casing shape or drum color — models learn to read digits, not housings |
| ⚡ VRAM-optimized | All images standardized to 640px on the longest side for efficient GPU memory usage during training |
🎁 Bonus: Free Pre-Trained Model
Every purchase of the full dataset includes a production-ready YOLO model trained on this exact 22-class taxonomy, achieving 94% mAP50-95. Skip months of R&D and deploy straight to production.
Dataset Structure
DS_mech_scor_labeled_v1_2026/
├── Images/ # 16,324 JPG images
├── Labels_YOLO/ # Normalized .txt annotations
├── Labels_PASCAL_VOC/ # Absolute-coordinate .xml annotations
├── classes.txt # 22-class master list
└── README_Documentation.txt
Labels are provided in dual format (YOLO + PASCAL VOC) for drop-in compatibility with Ultralytics and most standard ML pipelines.
Class Taxonomy (22 classes)
- Standard digits:
0–9 - Mid-rotation states:
0_1,1_2, …9_0(10 classes) - Structural anchors:
comma,scoreboard
Use Cases
- Automated meter-reading (AMR/AMI) pipelines
- Smart-grid digitization projects
- Utility billing automation
- Robust digit / object-detection research on analog dial instruments
Licensing
- Dataset (images + annotations): full commercial rights for training proprietary ML/AI applications.
- Bonus pre-trained model: provided under GNU AGPL-3.0.
- Reselling or redistributing raw files is prohibited. See full terms on the source site.
Access the Full Dataset
This preview does not include the full image set. Get the complete 16,324-image dataset plus the free bonus model at utilitymeters.ai.
Additional annotated utility-meter datasets (water, gas, electricity, heat, and display/serial-number taxonomies) are available on the seller's profile https://huggingface.co/utilitimetersai
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