Comments (5)
Hi! What do you mean the distribution is too large? If you mean that the values are higher than 1, that is ok, the softmax will squash all values to probabilities-range anyway.
Are you training encoder or the full network (decoder mode)?
For this 7% drop did you do any modification to the network or is it only changing the weights?
You can try the ones that are uploaded in the my erfnet_pytorch code (here):
if (enc): #encoder
weight[0] = 2.3653597831726
weight[1] = 4.4237880706787
weight[2] = 2.9691488742828
weight[3] = 5.3442072868347
weight[4] = 5.2983593940735
weight[5] = 5.2275490760803
weight[6] = 5.4394111633301
weight[7] = 5.3659925460815
weight[8] = 3.4170460700989
weight[9] = 5.2414722442627
weight[10] = 4.7376127243042
weight[11] = 5.2286224365234
weight[12] = 5.455126285553
weight[13] = 4.3019247055054
weight[14] = 5.4264230728149
weight[15] = 5.4331531524658
weight[16] = 5.433765411377
weight[17] = 5.4631009101868
weight[18] = 5.3947434425354
else:
weight[0] = 2.8149201869965 #road
weight[1] = 6.9850029945374 #sidewalk
weight[2] = 3.7890393733978 #building
weight[3] = 9.9428062438965 #wall
weight[4] = 9.7702074050903 #fence
weight[5] = 9.5110931396484 #pole
weight[6] = 10.311357498169 #traffic light
weight[7] = 10.026463508606 #traffic sign
weight[8] = 4.6323022842407 #vegetation
weight[9] = 9.5608062744141 #terrain
weight[10] = 7.8698215484619 #sky
weight[11] = 9.5168733596802 #person
weight[12] = 10.373730659485 #rider
weight[13] = 6.6616044044495 #car
weight[14] = 10.260489463806 #truck
weight[15] = 10.287888526917 #bus
weight[16] = 10.289801597595 #train
weight[17] = 10.405355453491 #motorcycle
weight[18] = 10.138095855713 #bicycle
from erfnet.
Oh,thanks o lot!
I will try yours.
The distribution is too large means that the first class weight is 0.0819 ,and someone is 5.2286,
the 5.2286/0.0819 is too big,please look at my weights.
from erfnet.
Yes, that distribution is a bit weird. What code did you use for calculation? Your weights are basically making the model "ignore" the classes with very small values (0.0819) and boost the ones with very high values. Did you try the weights from the pytorch code?
from erfnet.
I'm closing this but if you have more questions just reopen it. Thanks!
from erfnet.
Hi Eromera, thanks a lot for your wonderful works.
Recently I have been training the ERFnet from scratch with my data. I noticed that you used different class weights for encoder trainning and decoder trainning. Could you please explain the reason behind it ? Is this just because different datasets are used for them?
from erfnet.
Related Issues (13)
- Question about parameter "res" HOT 4
- Processing speed on CPU HOT 2
- Error occurred when I run the eval_cityscapes_server.lua. HOT 1
- Error for Decoder training part
- pretrainedEnc = next(pretrainedEnc.children()).features.encoder
- About the IoU? HOT 5
- Bug when restoring training using "loadEpoch" or "loadLastEpoch"
- About these model's prototxts HOT 1
- About the class weight? HOT 1
- cpu load gpu trained model eval error HOT 1
- Is the inference time of the model related to the parameter quantity of the model? HOT 7
- Using Train Encoder Command HOT 1
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 erfnet.