TRansPose is a large-scale multispectral dataset that combines stereo RGB-D, TIR (TIR) images, and object poses to promote transparent object research. The dataset includes 99 transparent objects, encompassing 43 household items, 27 recyclable trashes, 29 chemical laboratory equivalents, and 12 non-transparent objects. It comprises a vast collection of 333,819 images and 4,000,056 annotations, providing instance-level segmentation masks, ground-truth poses, and completed depth information.
SuperCaustics is a simulation tool made in Unreal Engine for generating massive computer vision datasets that include transparent objects. SuperCaustics is a real-time, open-source simulation of transparent objects designed for deep learning applications. SuperCaustics features extensive modules for stochastic environment creation; uses hardware ray-tracing to support caustics, dispersion, and refraction; and enables generating massive datasets with multi-modal, pixel-perfect ground truth annotations. <p align="center"> <img src="https://github.com/MMehdiMousavi/SuperCaustics/raw/main/Assets/SuperCaustics.gif" alt="drawing" width="600"/> </p>
The dataset contains procedurally generated images of transparent vessels containing liquid and objects . The data for each image includes segmentation maps, 3d depth maps, and normal maps of of the liquid or object inside the transparent vessel, and the vessel. In addition, the properties of the materials inside the containers are given(color/transparency/roughness/metalness). In addition, a natural image benchmark for the 3d/depth estimation of objects inside transparent containers is supplied. 3d models of the objects (GTLF) are also supplied.
This dataset is an extremely challenging set of over 3000+ original Transparent object images such as glasses and mirrors are captured and crowdsourced from over 500+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs. ### Dataset Features - Dataset size : 3000+ - Captured by : Over 500+ crowdsource contributors - Resolution : 99% images HD and above (1920x1080 and above) - Location : Captured with 600+ cities accross India - Diversity : Diversity in object type, lighting, camera type etc. - Device used : Captured using mobile phones in 2020-2022 - Usage : Glass detection | Mirror detection | Transparent Cups detection | Home automation etc. ### Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record To download full datasets or to submit a request for your dataset needs, please ping us at sales@datacluster.ai Visit www.datacluster.ai to know more.Note: All the images are manually captured and verified by a large contributor base on DataCluster platform