Comments (2)
-Ln 49 and 50 define the color palette in tools/cityscapes_save_predictions.py which is defined for the 18 (stuff and thing classes). You will have to first define a color palette of maybe 256 (or even 30 should be enough depending on the image or you can run np.unique to find the total number of instances+stuff_classes pan_pred has)
-remove lines from 70-71 to 75-83 and 86
modify ln 72 and 73 as
pan_pred = pan_pred.numpy()
panoptic_col[pan_pred==0] = colors.shape[0] - 1
panoptic_col = Image.fromarray(colors[panoptic_col])
(assuming the colors array last row stores the void pixel color)
-replace sem_img with panoptic_col in Ln 85 with panoptic_col
from efficientps.
@mohan1914 Do you have suggestions on how to properly define the palette?
from efficientps.
Related Issues (20)
- kitti subset HOT 2
- not find efficientPS_singlegpu_sample HOT 1
- run on KITTI dataset HOT 1
- Fail to open efficientPS_cityscapes.zip HOT 3
- pre-trained model (cityscape) classes missing? HOT 1
- Issue Inference of EfficientPS not working
- which dataset to download from Cityscapes download directory
- Installation of EfficientPS not working due to dependency inplace_abn (inplace_abn not updated for CUDA Driver Version 11) HOT 1
- Mask dislocation when test
- Convert the model to onnx HOT 3
- Could not download the pretrained models using the links in README HOT 1
- I get a bad kitti segmentation result with kitti pre-trained model. HOT 1
- How to compute mIoU based on results
- A bug about the cityscapes_demo.py
- problem with converting cityscapes HOT 1
- NameError: name ' samples_ per_ gpu' is not defined HOT 2
- Pre-Trained Models is not available
- RuntimeError: CUDA error: invalid device function,The cuda in the environment matches the cuda in mmdetection. Why the error HOT 1
- ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part. HOT 1
- Semantic segmentation metrics are used for evaluation
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 efficientps.