Comments (4)
Yes, you can I use depth map from any architecture to create pseudo lidar points. But if you fine tune your model on the KITTI training set LIDAR points, you will get a better result. But the difference should be less than 5%.
from pseudo_lidar.
My question is how can I create pseudo lidar points, if I don't have velodyne ground truth for the training dataset. I am planning to test on custom dataset. Thanks
from pseudo_lidar.
You need the calib
, image_2
(left image) and image_3
(right image) folders. And you need to generate the calibration files as the same format as KITTI object detection dataset.
from pseudo_lidar.
@mileyan so when using a custom dataset, what transformation matrix should I use for Tr_velo_to_cam
in the absence of any LiDAR device at all?
EDIT:
Sorry, wasn't thinking clearly last night! It's just a rotation and translation matrix. So would need to figure out where my camera would be relative road surface and camera2 on KITTI, then translate it to the KITTI LiDAR position. Correct?
from pseudo_lidar.
Related Issues (20)
- Evaluation with pre-trained frustum pointnet HOT 1
- AVOD pre-trained weights for mono pseudo-lidar HOT 1
- have trouble in Train the stereo model
- pseudo lidar HOT 1
- pseudo lidar gives wrong converted point cloud HOT 1
- Can not install pytorch with Python 2.7 HOT 2
- Training for my own custom data HOT 3
- If you need PSMNet but only want to go with python 3, check this repo then HOT 1
- Why pseudo point cloud results in this proposed method seem too far different from LIDAR? HOT 4
- question about dataloader
- About the calibration problem between the true location and the Pseudo-LiDAR HOT 1
- [Feature requested] Python3 support
- How did you handle calib matrices in mono+depth setting HOT 3
- Why does the nan value appear in loss when training the stereo model?
- Confusion about paper table 5
- visualization code cannot get point cloud output HOT 1
- Visualising Pseudo and Real LiDAR HOT 1
- Training Custom dataset
- Nuscenes dataset application
- can you share the dorn project
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from pseudo_lidar.