Update README.md

notebooks/README.md

@@ -1,10 +1,12 @@
 ## About the notebooks
 
 * `Apply_CRF.ipynb`: Applies Conditional Random Fields [1] as a post-processing step with the [`pydensecrf` library](https://github.com/lucasb-eyer/pydensecrf). 
-* `Data_Viz.ipynb`: Data visualization notebook.
+* `Data_Viz.ipynb`: Data visualization notebook ([Open in Colab](https://colab.research.google.com/github/sidgan/ETCI-2021-Competition-on-Flood-Detection/blob/main/notebooks/Data_Viz.ipynb)).
 * `Ensemble_Inference.ipynb`: Creates inference with an ensemble. 
 * `Generate_Pseudo.ipynb`: Prepares pseudo labels.
 
+**Note** that apart from the `Data_Viz.ipynb` notebook, we don't recommend running the other notebooks on Google Colab. 
+
 ## References
 
-[1] Philipp Krähenbühl and Vladlen Koltun. 2011. Efficient inference in fully connected CRFs with Gaussian edge potentials. In <i>Proceedings of the 24th International Conference on Neural Information Processing Systems</i> (<i>NIPS'11</i>). Curran Associates Inc., Red Hook, NY, USA, 109–117.
+[1] Philipp Krähenbühl and Vladlen Koltun. 2011. Efficient inference in fully connected CRFs with Gaussian edge potentials. In <i>Proceedings of the 24th International Conference on Neural Information Processing Systems</i> (<i>NIPS'11</i>). Curran Associates Inc., Red Hook, NY, USA, 109–117.