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SeaStereo dataset containing raw RGB and depth images of diverse underwater scenes with a stereo camera in Blender. Scenes include realistic seafloor environments and submerged everyday objects. Dataset will be used for training a neural network to recognise depth from an image, which is the basis for underwater grasping.
Contains 1176 configurations: 7 camera paths, 4 camera types, 7 water conditions, 2 depths 3 random arranegments of objects, with 40 frames rendered for each configuration.
See https://github.com/ollieturner/Simulated-Underwater-Depth-Dataset-Generation/tree/main for further information regarding generation.
Note: This dataset was generated with a convergence distance of 1.95m, a second dataset is currently being generated with a larger distance.
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