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Task: CV
Release Date: 5/13/2026
Format: JPEG, JSON
Size: 2.64 GB
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The Pakistan Traffic Signs Dataset is a curated collection of traffic sign images captured under diverse real-world road conditions across Pakistan. The dataset contains multiple categories of regulatory, warning, and informational traffic signs, collected from urban, suburban, and highway environments. Images include variations in lighting, weather, occlusion, viewing angles, motion blur, and background complexity to reflect realistic driving scenarios.
Licensing
Creative Commons Attribution Non Commercial 4.0 International (CC-BY-NC-4.0)
https://spdx.org/licenses/CC-BY-NC-4.0.htmlRestrictions/Special Constraints
This dataset is intended for non-commercial use only and may not be used for commercial purposes.
Forbidden Usage
This dataset must not be used for unlawful surveillance, harmful autonomous systems, or any activity that compromises public safety.
Intended Use
Intended for training, evaluation, and research of computer vision models for Pakistani traffic sign detection, recognition, and classification.
The Pakistani Traffic Sign Dataset is a real-world image collection capturing traffic signs from across Pakistan. The dataset is designed to support computer vision research and the development of AI-powered transportation systems tailored to Pakistan's unique road signage landscape, which features signs in both Urdu and English scripts.
The dataset consists of high-resolution images of traffic signs collected from diverse urban and rural regions across Pakistan, capturing real-world conditions with variations in camera devices, distances, angles, and environmental settings. The collection reflects the authentic signage landscape of Pakistani roads, including both Urdu and English language signs.
Images have undergone standard preprocessing steps including resizing and normalization. Some images intentionally retain natural noise, blur, and occlusions to preserve real-world conditions and improve model generalization in practical deployment scenarios.
A distinguishing feature of this dataset is the inclusion of traffic signs in both Urdu and English, reflecting Pakistan's bilingual road signage system. This makes the dataset particularly valuable for multilingual sign recognition, Urdu OCR, and cross-lingual traffic analysis tasks.
Images are captured under a broad range of environmental and lighting conditions including daytime, nighttime, shadows, varying weather, and complex urban and rural backgrounds, enhancing model robustness across diverse real-world scenarios.
This dataset is well-suited for a range of computer vision and AI tasks, including:
Traffic sign detection and classification
Urdu and English multilingual OCR on road signage
Object detection and localization
Training AI models for intelligent transportation systems (ITS)
Autonomous driving research in South Asian road environments
Certain traffic sign categories may be underrepresented, leading to class imbalance across the dataset.
Some images may contain occlusions, physical damage, or weathering that affects sign visibility.
Users are advised to apply data augmentation or class-balancing techniques depending on their specific use case.
{
"images": [
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{ "id": 2, "file_name": "images/002fa57f-9f0f-475e-9143-abce8a1c9150.jpg", "width": 4536, "height": 8064 },
{ "id": 3, "file_name": "images/9300ae95-2e41-4c7b-a5bd-cc154274f115.jpg", "width": 2268, "height": 4032 },
{ "id": 4, "file_name": "images/18358ac1-feed-48ce-90eb-1743b293fe39.jpg", "width": 4536, "height": 8064 },
{ "id": 5, "file_name": "images/a702d265-7cec-41f1-a919-3ae263fcaa8b.jpg", "width": 4536, "height": 8064 },