jjldo21/IndustrialDetectionStaticCameras

The IndustrialDetectionStaticCameras dataset has been collected in order to validate the methodology presented in the paper entitled A few-shot learning methodology for improving safety in industrial scenarios through universal self-supervised visual features and dense optical flow. This dataset is divided into five main folders named videoY, where Y=1,2,3,4,5. Each videoY folder contains the following:

• The video of the scene in .mp4 format: videoY.mp4
• A folder with the images of each frame of the video: imgs_videoY
• A folder that includes for each frame a .txt file that holds for each labelled object a line with the annotation in kitti format: annotations_videoY

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Remark: Each label file contains a set of lines, with each line representing the annotation for a single object in the corresponding image. The format of each line is as follows:

<object_type> <truncation> <occlusion> <alpha> <left> <top> <right> <bottom> <height> <width> <length> <x> <y> <z> <rotation_y>,

where only the fields <object_type>, <left>, <top>, <right>, <bottom> and <rotation_y> are considered. The <rotation_y> field has been used to indicate whether the labelled object is a static object in the scene or not -value 1 represents that object is static and value 0 symbolizes that it is not-.

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Install Hugging Face datasets package:

pip install datasets

Download the dataset:

from datasets import load_dataset
dataset = load_dataset("jjldo21/IndustrialDetectionStaticCameras")