This is the code for the following papers:

1. Fully Convolutional Recurrent Networks for Multidate Crop Recognition From Multitemporal Image Sequences
2. "Open Set Semantic Segmentation for Multitemporal Crop Recognition"

Installing the required python packages

Environment can be installed using environment.yml file. Use the following commands:

conda env create -f environment.yml
conda activate tf2

Preparing the input images

Download the input images from the following links.

Campo Verde dataset: https://drive.google.com/drive/folders/1nQT1CgLDcW8aEQSKS0_dNveJRUlBpptv?usp=sharing

LEM dataset: https://drive.google.com/drive/folders/18wV6pSOlqCkURiGYIuq3mV7TCfNFX2-x?usp=sharing

The dataset structure is as follows. Place the sequence of NPY input images in the in_sar/ folder, and the sequence of TIF labels in the labels/ folder.

dataset/  
  dataset/  
    {dataset_folder}/  
      in_sar/  
      labels/  

Where dataset_folder is cv_data for Campo Verde and lm_data for LEM

Closed set training and evaluation

python train_and_evaluate.py

Open Set training and evaluation

python train_and_evaluate_open_set.py