aitorzip / Keras Icnet
Licence: mit
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Stars: ✭ 85
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Keras-ICNet
[paper]
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress!
Requisites
- Python 3.6.3
- Keras 2.1.1 with Tensorflow backend
- A dataset, such as Cityscapes or Mapillary (Mapillary was used in this case).
Train
Issue ./train --help for options to start a training session, default arguments should work out-of-the-box.
You need to place the dataset following the next directory convention:
.
├── mapillary
| ├── training
| | ├── images # Contains the input images
| | └── instances # Contains the target labels
| ├── validation
| | ├── images
| | └── instances
| └── testing
| | └── images
These are the results of training for 300 epochs ./train --epochs 300
Training
Validation
Test
Issue ./test --help for options to start a testing session, default arguments should work out-of-the-box.
Output examples
TODO
- Perform class weighting
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