This is a sync of our repo. Here's the summary of the changes:
Added 🎉
New workflow to perform spectral extension. The workflow runs a model to combine information from an RGB drone image with a Sentinel-2 product to generate a high-resolution (0.125m/px) image with 8 Sentinel-2 bands.
New notebook showcasing the spectral extension workflow. The user may provide their own UAV image in order to generate the image.
Two automatic segmentation workflows based on SAM (Segment Anything Model). These will automatically segment entities in Sentinel-2 rasters (farm_ai/segmentation/auto_segment_s2) and BingMaps basemaps (farm_ai/segmentation/auto_segment_basemap) without requiring the user to explictly define a set of prompts (i.e., points and/or bounding box).
Two notebooks showcasing the automatic segmentation workflows over Sentinel-2 rasters and BingMaps basemaps. The notebooks explores several of the workflow parameters, highlighting how they affect the output segmentation masks.
Changed ↪️
[💔 BREAKING CHANGE] We created a new module vibe_notebook with all utility methods that are shared by the example notebooks in FarmVibes.AI. Previously these methods were organized in the notebooks/shared_nb_lib directory, which was imported by the notebooks using them. Because of this, most notebook environments
will need to be updated.
[💔 BREAKING CHANGE] With the new segmentation workflows, we updated scripts/export_sam_models.py so the exported ONNX models can process multiple prompts in a batch. Because of this change, the segmentation workflows (both prompt-based and automatic segmentation) will not work with ONNX models exported prior to this release. Please, make sure to delete the old ONNX models in the onnx_resources folder in your storage, and re-run the exportation script.
We updated scripts/export_sam_models.py to support adding the ONNX models to remote clusters. The script now has a new --cluster parameter to specify the cluster type (local or remote) to which the script will export the model to.
The workflow data_processing/clip/clip now allows hard clip (explicitly clipping the raster to the input geometry) in addition to soft clip (which would only update the geometry metadata of the raster, without actually cropping the raster).
We improved the post request of ADMA by accessing a skip token in the response. This enhancement allows users to download response results in smaller, manageable chunks.
Both the worker and the cache services now use gRPC for internal communication, hopefully reducing latency a bit and improving reliability as well. This should fix #163.
We updated the description of workflows that download Sentinel-1, as well as the documentation page on secrets,
to reflect the need for a Planetary Computer API key.
Fixed ⚒️
Fixed micromamba environment creation on Windows (see #164).
Stopped logging the azurerm provider's key when creating or updating AKS clusters.
This is a sync of our repo. Here's the summary of the changes:
Added 🎉
farm_ai/segmentation/auto_segment_s2) and BingMaps basemaps (farm_ai/segmentation/auto_segment_basemap) without requiring the user to explictly define a set of prompts (i.e., points and/or bounding box).Changed ↪️
vibe_notebookwith all utility methods that are shared by the example notebooks in FarmVibes.AI. Previously these methods were organized in thenotebooks/shared_nb_libdirectory, which was imported by the notebooks using them. Because of this, most notebook environments will need to be updated.scripts/export_sam_models.pyso the exported ONNX models can process multiple prompts in a batch. Because of this change, the segmentation workflows (both prompt-based and automatic segmentation) will not work with ONNX models exported prior to this release. Please, make sure to delete the old ONNX models in theonnx_resourcesfolder in your storage, and re-run the exportation script.scripts/export_sam_models.pyto support adding the ONNX models to remote clusters. The script now has a new--clusterparameter to specify the cluster type (local or remote) to which the script will export the model to.data_processing/clip/clipnow allows hard clip (explicitly clipping the raster to the input geometry) in addition to soft clip (which would only update the geometry metadata of the raster, without actually cropping the raster).Fixed ⚒️
Co-authored-by: Bruno Silva brunosilva@microsoft.com Co-authored-by: Eduardo Rodrigues edrodrigues@microsoft.com Co-authored-by: Naga Bilwanth Gangarapu Naga@zensa.co Co-authored-by: Rafael Padilha rpadilha@microsoft.com Co-authored-by: Renato Luiz de Freitas Cunha renato.cunha@microsoft.com Co-authored-by: Roberto de Moura Estevão Filho robertode@microsoft.com