crop_type_prediction

Implementations of crop type segmentation using U-Net and Convolutional LSTM

The code for Training convolutional LSTM is adopted from :

https://github.com/Orion-AI-Lab/S4A : A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning
https://github.com/Orion-AI-Lab/S4A-Models : Supplementary repo with DL experiments using the Sen4AgriNet dataset
Code for 3D unet is adopted from Bhattiprolu, S. (2023). python_for_microscopists. GitHub. https://github.com/bnsreenu/python_for_microscopists/blob/master

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
3d_unet		3d_unet
model		model
saved_results		saved_results
trained_model_weights/convlstm		trained_model_weights/convlstm
utils		utils
License		License
README.md		README.md
check_dataset.ipynb		check_dataset.ipynb
coco_data_split.py		coco_data_split.py
compute_class_weights.py		compute_class_weights.py
export_medians_multi.py		export_medians_multi.py
input_images.png		input_images.png
oad_experiments.py		oad_experiments.py
object-based-csv.py		object-based-csv.py
pad_experiments.py		pad_experiments.py
patch_aggregation_visualization.ipynb		patch_aggregation_visualization.ipynb
requirements.txt		requirements.txt
results_plotting.py		results_plotting.py
test_notebook.ipynb		test_notebook.ipynb
visualize_predictions.py		visualize_predictions.py

Provide feedback