Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label Russian_Road_Signs_Dataset@4695bed5dcaabdd98eee95c34dd909deff8b6f3a
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2368, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2285, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label Russian_Road_Signs_Dataset@4695bed5dcaabdd98eee95c34dd909deff8b6f3aNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Russian Road Signs Dataset
This dataset is designed for training and evaluating traffic sign detection models for autonomous driving. It covers 61 traffic sign classes following the Russian GOST R 52290-2004 standard - warning signs (1.x), priority signs (2.x), prohibitory signs (3.x), mandatory signs (4.x), information signs (5.x), service signs (6.x), and supplementary plates (8.x) - recorded from four vehicle-mounted cameras across 50 driving sessions in urban and suburban environments.
Classes (61)
Signs classified according to the Russian GOST R 52290-2004 standard, including:
- Speed limits and their end signs —
3_24,3_24_s40_white,3_24_s50,3_24_s60,3_24_s70,3_24_s70_white,3_24_s80,3_24_s90,3_24_s90_white,3_24_s100,3_24_s110,3_24_s130,3_25,3_25_white,3_25_s30_white,3_25_s50,3_25_s50_white,3_25_s60,3_25_s60_white,3_25_s70,3_24_s10_white,3_24_s40 - Priority signs —
2_4(give way),3_31(end of all restrictions) - Mandatory direction signs —
4_1_1(go straight),4_2_1,4_2_2,4_2_3(obstacle avoidance) - Warning signs —
1_8(traffic lights),1_15(slippery road),1_16(rough road),1_18(gravel ejection),1_19(dangerous shoulder),1_20_1,1_20_2,1_20_3(pedestrian crossing ahead),1_21(children),1_33(other hazards) - Information signs —
5_1(motorway),5_2(end of motorway),5_15_2,5_15_4,5_15_5,5_15_6,5_15_7(lane direction) - Supplementary plates —
8_2_3(action zone end),8_22_1,8_22_2,8_22_3(obstacle type) - Miscellaneous —
table(speed bump sign),scoreboard,scoreboard_sign(overhead gantry),unknown_sign
Data Fields
| Field | Type | Description |
|---|---|---|
| bbox_msg_id | VARCHAR | UUID linking to the original bounding box message |
| object_id | BIGINT | Unique object tracking ID |
| label | VARCHAR | Traffic sign class label (GOST R 52290-2004) |
| bbox_coords | DOUBLE[4] | Bounding box [x, y, width, height] in pixel coordinates |
| timestamp_ns | BIGINT | ROS bag timestamp (nanoseconds) |
| image_path | VARCHAR | Relative path to JPEG in train/ or test/ |
Data Splits
| Split | Rows | Images |
|---|---|---|
| train | 39,717 | 5,031 |
| test | 14,564 | 1,409 |
Dataset Structure
road_signs_dataset/
├── annotations.parquet # All annotations (54,281 rows)
├── train/
│ ├── camera_1C0FAF5250E2/ # 3,487 images
│ ├── camera_1C0FAF57D6F8/ # 979 images
│ ├── camera_1C0FAF5CA7B6/ # 464 images
│ └── camera_1C0FAF5CC14D/ # 101 images
└── test/
├── camera_1C0FAF5250E2/ # 793 images
├── camera_1C0FAF57D6F8/ # 149 images
├── camera_1C0FAF5CA7B6/ # 364 images
└── camera_1C0FAF5CC14D/ # 103 images
Usage
import pandas as pd
df = pd.read_parquet("annotations.parquet")
print(f"{len(df)} annotations, {df.image_path.nunique()} unique images")
- Downloads last month
- 47
Source:
Fleet of autonomous vehicles, Russian urban and suburban roads
Sensor:
4x LUCID TRI054S-CC cameras (2880×1860), front/side facing
Coverage:
~54K bounding box annotations, ~6.4K unique images, 61 sign classes
Splits:
Train 70% (39,717 rows, 5,031 images), Test 30% (14,564 rows, 1,409 images) - split by driving session to prevent temporal leakage
Format:
subdirectories
Total file size:
7.03 GB