The TuSimple-Benchmark dataset includes 6,408 road images captured on US highways, each with a resolution of 1280×720. This comprehensive dataset offers a robust resource for training, validation, and testing in various weather conditions.
For the training phase, we provide 3,626 images. These images serve as the foundation for developing machine learning models. Additionally, 358 images are designated for validation, enabling fine-tuning and model optimization. Finally, the dataset includes 2,782 images specifically for testing, known as the TuSimple test set, which challenge the models under diverse weather conditions.
Moreover, this full version of the TuSimple Dataset comes with extra training Segmentation Annotations. These annotations enhance the dataset’s utility, allowing for more detailed and accurate model training.
By incorporating transition words and maintaining an active voice, we ensure clarity and engagement throughout the dataset description. This dataset stands out as a valuable tool for advancing research and development in road image analysis and related fields
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