| # Russian Road Signs Dataset |
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| 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. |
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| ## Dataset Description |
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| - **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:** Parquet (annotations) + JPEG (images) in `train/` and `test/` subdirectories |
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| ### Classes (61) |
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| Signs classified according to the Russian GOST R 52290-2004 standard, including: |
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| - **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` |
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| ### Data Fields |
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| | 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/` | |
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| ### Data Splits |
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| | Split | Rows | Images | |
| |-------|------|--------| |
| | train | 39,717 | 5,031 | |
| | test | 14,564 | 1,409 | |
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| ### Dataset Structure |
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| ``` |
| 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 |
| ``` |
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| ### Usage |
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|
| ```python |
| import pandas as pd |
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| df = pd.read_parquet("annotations.parquet") |
| print(f"{len(df)} annotations, {df.image_path.nunique()} unique images") |
| ``` |
