Traffic Light Detection Dataset
This dataset offers artificially annotated images for the detection and classification of traffic lights. It covers 9 different categories with color labels, making it possible to develop recognition models for autonomous vehicles or driver assistance systems.
Approximately 2,600 annotated images with categories and colors, image format (probably JPG/PNG)
CC0: Public Domain
Description
The “Traffic Light Detection Dataset” contains approximately 2,600 images annotated according to 9 categories of traffic lights and their associated colors. These artificial annotations facilitate the formation of models for the accurate recognition of fires in urban contexts.
What is this dataset for?
- Develop vision models for the detection and classification of traffic lights
- Improving driver assistance systems and autonomous vehicles
- Training object recognition algorithms in urban areas
Can it be enriched or improved?
The dataset could be enriched with finer manual annotations, images in various conditions (weather, light), and video sequences for a temporal context. These additions would increase the robustness of the models trained.
🔎 In summary
🧠 Recommended for
- AI vision developers
- Autonomous vehicle projects
- Researchers in the detection of urban objects
🔧 Compatible tools
- TensorFlow
- PyTorch
- OpenCV
- LabelImg
💡 Tip
Combine this dataset with real images to improve robustness under real conditions.
Frequently Asked Questions
Does this dataset contain real or synthetic images?
Annotations are artificial, but images may be real; however, additional verification is recommended.
Can this dataset be used for a commercial project?
Yes, the CC0 license allows commercial use without restrictions.
Does the dataset include images in different lighting or weather conditions?
No, the dataset focuses mainly on annotated images, it lacks environmental variations.
