Comments (3)
Hi, there will still be some time before we release the training code. If you can't wait you can implement it yourself. Our training code is based on monodepth2 trainer.py, and it is easy to implement since we do not make many modifications. You can refer to the implementation details of our paper.
from lite-mono.
Hi @onthebigtree , the training code has been released.
from lite-mono.
Hi @onthebigtree , the training code has been released.
Absolutely amazing, thank you for your tireless efforts!
from lite-mono.
Related Issues (20)
- Training on Mid-Air Dataset HOT 7
- How the reproduction of the results of the model achieves the results in the paper HOT 2
- About the CDC module and LGFI module HOT 8
- Hi,I've got some new questions HOT 9
- Some question about the result HOT 4
- The edges of the image are foggy and blurry during the training process HOT 4
- Inexplicable "No such file or directory: 'Lite-Mono-main\\kitti_data\\\2011_09_26/2011_09_26_drive_0002_sync\\\image_02/data\\- 000000001.png'" HOT 2
- the CPU utilization has been very high, but the GPU utilization has been very low HOT 2
- training with Nuscenes dataset HOT 39
- About indicator sq_rel HOT 6
- Test outputs is black HOT 8
- I read your paper “For models trained from scratch an initial learning rate of 5e−4 with a cosine learning rate schedule [26] is adopted” But how should I implement it in the code? HOT 4
- How the reproduction of the results of the model achieves the results in the paper HOT 6
- Hello, my reproduction code is exactly the same as the code uploaded by the author of the paper, CUDA11.0, PyTorch 1.7.1. Please check your code and replace your CUDA and pytorch version.
- model reproduction HOT 11
- Hello, I have some questions regarding the model training with the KITTI dataset HOT 4
- Pre-training Weights HOT 1
- about pretrain acc HOT 1
- the results of training are black pictures HOT 5
- test code for pose HOT 2
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 lite-mono.