tsdf-fusion-python
consistent_depth
| tsdf-fusion-python | consistent_depth | |
|---|---|---|
| 2 | 5 | |
| 1,087 | 1,581 | |
| - | 0.6% | |
| 0.0 | 0.0 | |
| about 1 year ago | 9 months ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | MIT License |
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tsdf-fusion-python
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TSDF integration with disparity maps?
i found this https://github.com/andyzeng/tsdf-fusion-python but it uses depth maps in mm which is not what i need
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From Azure Kinect To Hololens2
First, I would suggest looking into https://github.com/andyzeng/tsdf-fusion-python and it’s parent project https://github.com/andyzeng/3dmatch-toolbox as they are pretty good KinectFusion implementations that are under active development and support the Azure Kinect v4.
consistent_depth
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How can I use a monocular camera for distance measurement?
You can try using video stream instead of image (See Consistent Video Depth Estimation from 2020, and its current citations)
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Depth from a monocular camera
You can try this https://github.com/facebookresearch/consistent_depth
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TSDF integration with disparity maps?
its a virtual COLMAP camera, the disparity maps were acquired from https://github.com/facebookresearch/consistent_depth running on a 90 frame video
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how to i get the open3D reconstruction script(s) to work with my depth images?
Hello, i am trying to use the reconstruction scripts to generate point clouds/meshs from the depth output obtained from consistent depth estimation
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3D perspective from a still photo using depth maps
if anyone is looking for an open source version of the depth mapping tool this service appears to be using: https://github.com/facebookresearch/consistent_depth
What are some alternatives?
tinysfm - Structure From Motion in 50 lines using OpenCV
MiDaS - Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
Meshroom - 3D Reconstruction Software
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
quanfima - Quanfima (Quantitative Analysis of Fibrous Materials)
CPPE-Dataset - Code for our paper CPPE - 5 (Medical Personal Protective Equipment), a new challenging object detection dataset
PaddleHub - Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)
aistplusplus_api - API to support AIST++ Dataset: https://google.github.io/aistplusplus_dataset