---
language:
- it
- en
license: mit
task_categories:
- object-detection
tags:
- traffic-signs
- autonomous-driving
- adas
- computer-vision
- yolo
- yolov12
pretty_name: Street Sign Set
size_categories:
- 1K<n<10K
---
# Street Sign Set 🚦
This dataset was developed for the **Street Sign Sense** project, which achieved a final grade of **30/30** in the Machine Learning course. It is specifically designed and optimized for training state-of-the-art object detection models, such as **YOLOv12**, for the recognition of Italian and European road signs.
## Dataset Description
The **Street Sign Set** is a comprehensive collection of traffic sign images, annotated in the **YOLO format**. It focuses on real-world driving conditions to ensure robustness in Advanced Driver Assistance Systems (ADAS).
**Street Sign Set** is a dataset with over **7300 images** designed for road sign detection in realistic contexts.
#### 🏷️ Class Structure and Labels
The dataset comprises **63 total classes*…
# Street Sign Set
This dataset was developed for the **Street Sign Sense** project. It is specifically designed and optimized for training state-of-the-art object detection models, such as **YOLO12**, for the recognition of Italian and European road signs.
## Dataset Description
The **Street Sign Set** is a comprehensive collection of traffic sign images, annotated in the **YOLO format**. It focuses on real-world driving conditions to ensure robustness in Advanced Driver Assistance Systems (ADAS).
**Street Sign Set** is a dataset with over **7300 images** designed for road sign detection in realistic contexts.
#### 🏷️ Class Structure and Labels
The dataset comprises **63 total classes**, organized into 5 macro-categories that define the label prefix: **prio** (priority), **forb** (prohibition), **info** (information), **warn** (warning), **mand** (mandatory).
Labeling examples: `prio_give_way`, `forb_speed_over_50`, `info_parking`, `warn_right_curve`, `mand_pass_left_right`.
…
