Dataset for fifteen types of obstacle detection, Because the data is too large to put in Github, please click the link to get it from Googledriver.Baidu CODE:0521
Classes ["stop_sign","person","bicycle","bus","truck","car","motorbike","reflective_cone","ashcan","warning_column","spherical_roadblock","pole","dog","tricycle","fire_hydrant"] Need to underline the category name
This obstacle dataset follows the format of the VOC dataset, if you are not clear about the VOC data format, please click THERE to view.
The dataset contains xml files in VOC format and .txt files for yolo training,as follows.
-JPEGImages
-Annotations
-ImageSets
--Main
---train.txt
---test.txt
---val.txt
According to pictures and labels,as follows.
img-train for training Contains 5066 images ann-train
img-test for test Contains 1583 images ann-test
img-val for validation Contains 1266 images ann-val
lables #all picture labels<br>
label-train #labels for training<br>
label-test #labels for testing<br>
label-val #labels for validation<br>
This dataset contains images from the VOC dataset, the COCO dataset, and the TT100K dataset,It also contains some pictures collected by the author's team in the field.
Vicente S, Carreira J, Agapito L, Batista J. Reconstructing PASCAL VOC. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2014:41-48.
Lin TY, Maire M, Belongie S, et al. Microsoft COCO: Common objects in context. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics). 2014;8693 LNCS(PART 5):740-755.
Zhu Z, Liang D, Zhang S, Huang X, Li B, Hu S. Traffic-Sign Detection and Classification in the Wild. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2016;2016-December:2110-2118.
if you have any question,You can contact me according to the following email.
E-mail:tangwu0521@gmail.com
The author continues to update this dataset.
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