Tensorflow implementation of Deep Ordinal Regression Network for Monocular Depth Estimation
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Updated
Jan 29, 2019 - Python
Tensorflow implementation of Deep Ordinal Regression Network for Monocular Depth Estimation
Python CLI for generating depth map from stereoscopic image
Disparity and depth maps GUI with QT and OpenCV with support for classic image files and MPO stereo pairs
Quick tool to visualize a depthmap pixel value
Pytorch Implementation of Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
An example script that uses the objc_util module available in the Pythonista app to extract depth data from Portrait photos.
Monocular depth estimation from ArgoAI's Lidar based Depth dataset - Depth predictions up-to 200m
Minecraft as a real-world hologram. No glasses required.
Use an image segmentation to produce a RGB+D image (image + depthmap). Or use the GUI to view already-made RGB+D images in 3D, there's even an anaglyph mode to perceive depth with red+cyan glasses. Animate the 3D view and export to a series of images to build later an animated image. This nice GUI uses QT, OpenCV and OpenGL
Dense Depth Estimation from Multiple 360-degree Images Using Virtual Depth
A straightforward Siamese network designed for block matching to generate a disparity map
Perform a visibility graph analysis quickly and easily. Visibility calculation done in C.
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