CCTSDB2021： https://drive.google.com/drive/folders/14Km2W-5hbixXDfz7WSqW_Rx7O5m8ZMFn?usp=sharing
链接：https://pan.baidu.com/s/1hyGmwLzcPi21XEP1MQsj5Q
提取码：nygx
请帮忙引用：
[1] Jianming Zhang, Yaru Lv, Jiajun Tao, Fengxiang Huang, Jin Zhang. A robust real-time anchor-free traffic sign detector with one-level feature. IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, vol. 8, no.2, pp. 1437-1451. DOI: 10.1109/TETCI.2024.3349464. [2] Jianming Zhang, Xin Zou, Li-Dan Kuang, Jin Wang, R. Simon Sherratt, Xiaofeng Yu. CCTSDB 2021: A more comprehensive traffic sign detection benchmark. Human-centric Computing and Information Sciences, 2022, vol. 12, Article number: 23. DOI: 10.22967/HCIS.2022.12.023. [3] Jianming Zhang, Zhuofan Zheng, Xianding Xie, Yan Gui, Gwang-Jun Kim. ReYOLO: A traffic sign detector based on network reparameterization and features adaptive weighting. Journal of Ambient Intelligence and Smart Environments, 2022, vol. 14, no. 4, pp. 317-334. DOI: 10.3233/AIS-220038. [4] Jianming Zhang, Zi Ye, Xiaokang Jin, Jin Wang, Jin Zhang. Real-time traffic sign detection based on multiscale attention and spatial information aggregator, Journal of Real-Time Image Processing, 2022, vol. 19, no. 6, pp. 1155–1167. DOI: 10.1007/s11554-022-01252-w. [5] Jianming Zhang, Wei Wang, Chaoquan Lu, Jin Wang, Arun Kumar Sangaiah. Lightweight deep network for traffic sign classification. Annals of Telecommunications, 2020, vol. 75, no. 7-8, pp. 369-379. DOI: 10.1007/s12243-019-00731-9. [6] Jianming Zhang, Zhipeng Xie, Juan Sun, Xin Zou, Jin Wang. A cascaded R-CNN with multiscale attention and imbalanced samples for traffic sign detection. IEEE Access, 2020, vol. 8, pp. 29742-29754. DOI: 10.1109/ACCESS.2020.2972338. [7] 李旭东, 张建明, 谢志鹏, 王进. 基于三尺度嵌套残差结构的交通标志快速检测算法. 计算机研究与发展, 2020, 57(5): 1022-1036. DOI: 10.7544/issn1000-1239.2020.20190445. In cctsdb 2021 dataset, there are 17856 images in training set and positive sample test set. The traffic signs in the image are divided into mandatory, prohibitory and warning according to their meanings. There are 16356 training set images numbered 00000-18991. The positive sample test set has 1500 images numbered 18992-20491. The "XML" compressed package stores the XML format annotation files of training set and positive sample test set. The "train_img" compressed package stores the training set images. The "train_labels" compressed package stores the TXT format annotation file of the training set. The "test_img" compressed package stores the positive sample test set image. The "classification based on weather and environment" compressed package stores the XML format annotation file of the positive sample test set classified according to the weather and lighting conditions. The "classification based on size of traffic signs" compressed package stores the XML format annotation file of the positive sample test set classified according to the size of traffic signs in the image. "Negative samples" contains 500 negative sample images.