Closed hannah-rae closed 1 year ago
The labels for validation/test for this have already been completed last year. The data associated with the labels has been exported too, but I think we should re-export them since there have been changes since the last time it was done. @ivanzvonkov do you agree?
Yes you can see the data that is already available here: https://github.com/nasaharvest/crop-mask/blob/74913ceff6b4bc4c3fd88f0aa3a381043108ffc9/data/report.txt#L132
The csv files can be accessed by running the following inside a cloned repo
dvc pull data/datasets
The data has been updated according to various changes over the last year. One outstanding change is using data with nans instead of skipping it. This can be achieved by
First, deleting the csv from data/datasets
Then
git checkout -b'updating-tigray-data'
dvc commit data/datasets
dvc push
git add .
git commit -m'Update data'
git push
This will run the data pipeline and automatically generate new csvs with missing data not skipped.
Model is trained, pending merge of #266
create_map.ipynb
does not indicate that there is more available data.Retrain model without ERA5 data. Middle artifacts present in above seem to be in line with ERA5 sized tiling - Dr. Kerner
Retrained 2020 model without ERA5 data. Changed testing and validation metrics here
@bhyeh is the new map ready for review? Does it have artifacts and/or missing data?
Here is a link for the latest map for 2020. Was having issues with missing predictions the last few tries - but all is well now!
Awesome thanks @bhyeh! Looking at the map, I think it seems a bit worse than the 2021 one, which is also shown in the metrics. I am wondering if we can boost the performance a bit with corrective labeling.
@MsPixels Would you be able to help @bhyeh get a corrective labeling project set up for this map?
Yes @hannah-rae, I can set it up for @bhyeh
@bhyeh, Corrective labeling for Tigray 2020. More resources can also be found here
Next step: @bhyeh to make updated Tigray 2020 map with model updated with corrective labels
Start year: 2020 Start month: February