This set of changes is primarily focused on replacing Earth Engine with Descartes for accessing Sentinel data in the core pipeline stages. Listing key changes.
Pixel Classifier:
create_pixel_dataset: DL data pipeline. Operates on polygons, meaning that pixels outside of boundary are masked. Be aware that cloud filtering comes from DL sentinel cloud mask rather than S2 cloudless.
train_pixel_classifier: Some convenience changes and prediction simplification. Models now save with a .txt file listing a classification report and input data.
run_pixel_classifier: Repackaged to use the DL-backed version of nn_predict.py
nn_predict.py: Renamed the GEE version to nn_predict_gee.py. Replaced with a simpler and faster pixel classifier prediction script. Only key change is to specify an end_date rather than num_months as an argument.
Patch Classifier:
create_patch_dataset: DL data pipeline. Patches are now padded or trimmed to be a uniform shape. This was not guaranteed previously.
run_patch_classifier: DL data pipeline. Predictions are no longer made for only a single median patch. Instead, every patch below a threshold of cloudiness is evaluated. All predictions and patches are then stored in a dictionary.
Other
animate_patch: DL data pipeline.
descartes_model_run: Kick off a distributed model evaluation job on Descartes. Once finished, download the files and tile them into a single geotiff.
New sampling sites, including TPA site polygons for confirmed Java dumps.
New models. v1.1.8 is probably the current best?
@eboyda I think you're mostly familiar with these changes since you've been working off of the descartes-data branch. Mostly writing these notes to log what has changed.
eboyda
commented
3 years ago
This set of changes is primarily focused on replacing Earth Engine with Descartes for accessing Sentinel data in the core pipeline stages. Listing key changes.
Pixel Classifier:
create_pixel_dataset: DL data pipeline. Operates on polygons, meaning that pixels outside of boundary are masked. Be aware that cloud filtering comes from DL sentinel cloud mask rather than S2 cloudless.train_pixel_classifier: Some convenience changes and prediction simplification. Models now save with a .txt file listing a classification report and input data.run_pixel_classifier: Repackaged to use the DL-backed version ofnn_predict.pynn_predict.py: Renamed the GEE version tonn_predict_gee.py. Replaced with a simpler and faster pixel classifier prediction script. Only key change is to specify anend_daterather thannum_monthsas an argument.Patch Classifier:
create_patch_dataset: DL data pipeline. Patches are now padded or trimmed to be a uniform shape. This was not guaranteed previously.run_patch_classifier: DL data pipeline. Predictions are no longer made for only a single median patch. Instead, every patch below a threshold of cloudiness is evaluated. All predictions and patches are then stored in a dictionary.Other
animate_patch: DL data pipeline.descartes_model_run: Kick off a distributed model evaluation job on Descartes. Once finished, download the files and tile them into a single geotiff.@eboyda I think you're mostly familiar with these changes since you've been working off of the
descartes-databranch. Mostly writing these notes to log what has changed.