The official version will be available at tianmoucv/tianmocv
This is the Python tool for the first complementary vision sensor (CVS), TianMouC.
More details about the project can be found on our project page. Tianmouc Project and Tianmoucv Document
(0) Prepare pytorch environment
Python version should be larger than 3.8 and less than 3.12, recommend 3.10
conda create -n [YOUR ENV NAME] --python=3.10
conda activate [YOUR ENV NAME]
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia(1) from PyPI
pip install tianmoucv(2) Install from source codes (using pip):
git clone [email protected]:Tianmouc/Tianmoucv_preview.git
cd Tianmoucv_preview
sh install.shYou can download a TianMouC data clip in THU-sharelink, and refer to tianmoucv/exmaple/data/test_data_read.ipynb for a trial
a standard TianMouC dataset structure:
├── dataset
│ ├── matchkey
│ │ ├── cone
│ │ ├── info.txt
│ │ ├── xxx.tmdat
│ │ ├── rod
│ │ ├── info.txt
│ │ ├── xxx.tmdat
where matchkey is the sample name used for the TianMouC data reader
For some of the algorithms we've provided the example in tianmoucv/example
Including:
(1) calculating optical flow
(2) reconstruct gray/hdr images
(3) key point matching/tracking
(4) camera calibration
(5) data reeader
These samples can be directly run on jupyter notebook
conda activate [your environment]
pip install jupyter notebook
jupyter notebookThis project exists thanks to all the people who contribute.
GPLv3 © Yihan Lin