Corn and Soybean Mapping model at 30 m resolution from Landsat 8/ Sentinel 2

train.py - trains the model. Make sure the data directory/folder are set correctly. The training data can be exported as TFRecord from Earth Engine. The model expects data as 256x256 samples with the bands and the labels stacked together as channels. (export code in python through earth engine api TBU. Refer to this notebook for reference)

UNETModel.py - The UNET image segmentation model.

deeplabModel.py - The deepLabV3 image segmentation model.

resnet50.py - The ResNet50 backbone for deepLabV3 model.

confusion_matrix.py - includes helper functions to save a confusion matrix image as part of the logs that can be monitored via tensorboard.

requirements.txt - python packages required to run this repo.