Comments (3)
Hello @lim-anggun,
thanks for sharing this great work. I have a question about your design architecture / your problem definition. do you use features accross time (temporal features) for segmenting the background and the foreground?
because from your paper, your problem definition seems like semantic segmentation for me.
thank you very much.
best regards,
albert christianto
from fgsegnet_v2.
hi @Wisgon,
num_pixels = (pixel_height, pixel_width)
, where pixel_height
or pixel_width
is the number of pixel that you want to pad your output dimension after 2 times downsampling (2 VGG-16 max-pooling). I rather upscale feature maps instead of zero-pad the feature maps, in my experiment. But you can skip MyUpSampling2D
and use Keras ZeroPadding2D
instead.
More detail: If your input dimension, say 240x320, so after 2 times downsampling by the encoder, your output will be 60x80. So, after 2 times upsampling by the decoder, your output will be 240x320. In this case, you don't need to use ZeroPadding
or MyUpSampling
. But if the output from the encoder, say 60x79, you need to pad 1 width-pixel, e.g. x = MyUpSampling2D(num_pixels=(0, 1), method_name=self.method_name)(x)
from fgsegnet_v2.
OK, I will try it later, thank you very much.
from fgsegnet_v2.
Related Issues (20)
- unable to load the model after adding instance_normalization HOT 3
- multispectral use HOT 1
- how to train my own data? HOT 1
- How to handle real video HOT 3
- Evaluation Code HOT 1
- Can it work well on other dataset?
- the accuracy of a catogery is very low the port_0_17fps : 0.435026037734113 HOT 1
- Memory leak and how to train using a gpu ? HOT 3
- compilation error HOT 1
- Training on real video
- How can I load model? HOT 5
- ImportError: libcublas.so.8.0: cannot open shared object file: No such file or directory
- How can i solve this error? HOT 1
- About the meaning of void_label HOT 1
- License File HOT 1
- foreground segment images HOT 1
- Design of decoder HOT 1
- CDnet Utilities link address is missing HOT 1
- how can I evaluate the segmentation results quantificationally? HOT 3
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 fgsegnet_v2.