Comments (2)
Hi,
Apologize, I commented the model links by mistake in the README.md file. You can now find and download the pre-trained model here.
from ganav-offroad.
Thank You.
from ganav-offroad.
Related Issues (20)
- Check point file HOT 10
- about the training loss become nan HOT 6
- Pre-processing images HOT 2
- AssertionError HOT 8
- Enquiry regarding Performance of Training HOT 14
- Error in ONNX conversion HOT 10
- how to get segmentation cost map from segmentation results? HOT 1
- Conversion of RUGD and Rellis Datasets To Rugd6 Group & Training HOT 4
- Is the onnx file generated by pytorch2onnx.py quantized? HOT 1
- Welcome update to OpenMMLab 2.0 HOT 1
- Use pretrained ResNet50 model (backbone) on ImageNet.
- L1? L2? L3? HOT 2
- checkpoint error HOT 4
- Output image of the model HOT 5
- ModuleNotFoundError: No module named 'mmcv._ext' HOT 4
- Change of backbone HOT 2
- Training on GOOSE Dataset HOT 3
- rellis folder structure
- output quality HOT 2
- User Guide / Usage 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 ganav-offroad.