docs: README and docs/index revision (#185)

* separate out the goal and specific current dev for Echoview

* small wording changes

README.md

@@ -5,34 +5,38 @@
 
 ![example workflow](https://github.com/OSOceanAcoustics/echoregions/actions/workflows/pytest.yml/badge.svg)
 
-Echoregions is a tool that interfaces annotations from Echoview and masks for water column sonar data for Machine Learning (ML) developments. Manual annotations from Echoview are widely used in fisheries acoustics community for labeling the presence of different animal species, and the presence of bottoms on echograms. Echoregions is designed to be used as an intermediate software between Echoview annotation data products and conventional Python Machine Learning data products. The end goal for Echoregions is to allow the user to easily go from Echoview -> ML data products, and ML -> Echoview data products. Presently, the Echoview -> ML data products pipeline has been built.
+Echoregions is a tool that interfaces annotations of water column sonar data with Machine Learning (ML) models.
+
+The annotations are typically regions indicating the presence of specific animal species or lines delineating ocean boundaries, such as the seafloor or sea surface, in the "echogram" (sonar images formed by echo returns). The interfacing functionalities operate in two directions:
+- Annotation to ML: Parsing and organizing manual annotations for preparing training and test datasets for ML developments
+- ML to annotation: Generating annotations from ML predictions that can be used for further downstream processing
+
+At present, functionalities in the Annotation to ML direction have been built for interfacing the Echoview software that is widely used in the fisheries acoustics community. We plan to add functionalities in the ML to Annotation direction in the near future.
 
 ## Functionalities
 
 As of now, Echoregions contains functions to:
-- Read, organize, and store Echoview manual annotations
+- Read, organize, and store Echoview manual annotations (regions and lines)
 - Create masks by combining the manual annotations and xarray water column sonar datasets generated by [Echopype](https://github.com/OSOceanAcoustics/echopype)
 
-We plan to add additional functions to build the ML -> Echoview data products pipeline. This will allow the user to create bottom and region annotations from ML predictions and convert to a format that can be easily visualized and manipulated in Echoview.
-
-The underlying annotation data is stored as a Pandas dataframe, which allows users to leverage the powerful indexing and computational tools provided by Pandas.
+Note that in Echoregions, the underlying annotation data is stored as a Pandas dataframe, which allows users to directly leverage the powerful indexing and computing functionalities provided by Pandas.
 
 ## Documentation
 
 Learn more about Echoregions functions in the documentation at https://echoregions.readthedocs.io.
 
 See the [API documentation](https://echoregions.readthedocs.io/en/latest/api.html) for all of the classes and functions available in echoregions.
 
+## Contributors
+
+Echoregions development is currently led by Caesar Tuguinay (@ctuguinay), with inputs from Wu-Jung Lee (@leewujung) and Valentina Staneva (@valentina-s). Kavin Nguyen (@ngkavin) contributed significantly to the initial version.
+
 ## Acknowledgement
 
 We thank the NOAA Northwest Fisheries Science Center (NWFSC) Fisheries Engineering and Acoustics Team (FEAT) for supporting this project.
 
 <img src="docs/source/images/noaa_fisheries_logo.png" alt="NOAA_fisheries_logo" width="200">
 
-## Contributors
-
-Echoregions development is currently led by Caesar Tuguinay (@ctuguinay), with inputs from Wu-Jung Lee (@leewujung) and Valentina Staneva (@valentina-s). Kavin Nguyen (@ngkavin) contributed significantly to the initial version.
-
 ## License
 
 Echoregions is licensed under the open source [Apache 2.0 license](https://opensource.org/licenses/Apache-2.0).

docs/source/index.md

@@ -1,16 +1,24 @@
 # Echoregions
 
-Echoregions is a tool that interfaces annotations from Echoview and masks for water column sonar data for Machine Learning (ML) developments. Manual annotations from Echoview are widely used in fisheries acoustics community for labeling the presence of different animal species, and the presence of bottoms on echograms. Echoregions is designed to be used as an intermediate software between Echoview annotation data products and conventional Python Machine Learning data products. The end goal for Echoregions is to allow the user to easily go from Echoview -> ML data products, and ML -> Echoview data products. Presently, the Echoview -> ML data products pipeline has been built.
+Echoregions is a tool that interfaces annotations of water column sonar data with Machine Learning (ML) models.
+
+The annotations are typically regions indicating the presence of specific animal species or lines delineating ocean boundaries, such as the seafloor or sea surface, in the "echogram" (sonar images formed by echo returns). The interfacing functionalities operate in two directions:
+- Annotation to ML: Parsing and organizing manual annotations for preparing training and test datasets for ML developments
+- ML to Annotation: Generating annotations from ML predictions that can be used for further downstream processing
+
+At present, functionalities in the Annotation to ML direction have been built for interfacing manual annotations from the Echoview software, which is widely used in the fisheries acoustics community. We plan to add functionalities in the ML to Annotation direction in the near future.
 
 ## Functionalities
 
 As of now, Echoregions contains functions to:
-- Read, organize, and store Echoview manual annotations
+- Read, organize, and store Echoview manual annotations (regions and lines)
 - Create masks by combining the manual annotations and xarray water column sonar datasets generated by [Echopype](https://github.com/OSOceanAcoustics/echopype)
 
-We plan to add additional functions to build the ML -> Echoview data products pipeline. This will allow the user to create bottom and region annotations from ML predictions and convert to a format that can be easily visualized and manipulated in Echoview.
+Note that in Echoregions, the underlying annotation data is stored as a Pandas dataframe, which allows users to directly leverage the powerful indexing and computing functionalities provided by Pandas.
 
-The underlying annotation data is stored as a Pandas dataframe, which allows users to leverage the powerful indexing and computational tools provided by Pandas.
+## Contributors
+
+Echoregions development is currently led by Caesar Tuguinay (@ctuguinay), with inputs from Wu-Jung Lee (@leewujung) and Valentina Staneva (@valentina-s). Kavin Nguyen (@ngkavin) contributed significantly to the initial version.
 
 ## Acknowledgement
 
@@ -22,10 +30,6 @@ We thank the NOAA Northwest Fisheries Science Center (NWFSC) Fisheries Engineeri
 ```
 <!-- <img src="docs/source/images/noaa_fisheries_logo.png" alt="NOAA_fisheries_logo" width="200"> -->
 
-## Contributors
-
-Echoregions development is currently led by Caesar Tuguinay (@ctuguinay), with inputs from Wu-Jung Lee (@leewujung) and Valentina Staneva (@valentina-s). Kavin Nguyen (@ngkavin) contributed significantly to the initial version.
-
 ## License
 
 Echoregions is licensed under the open source [Apache 2.0 license](https://opensource.org/licenses/Apache-2.0).