ForestMEvBat is the repository containing the code base produced for the Thomas ANTOINE's master thesis. The project is based on [ForestMEv2-public](https://forge.uclouvain.be/nbrusselmans/forestmev2-public) by Nicolas BRUSSELMANS.
All of the data needed to train the models is available at https://doi.org/10.14428/DVN/92ZO97.
The project is separated between 4 folders:
-[Embedded_sw](Embedded_sw): the STM project to program the board
-[Annotation_generation](Annotation_generation): transform raw binary data into a usable sound clip dataset and generate annotations
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@@ -38,4 +40,4 @@ A typical workflow to use the framework would be:
Most scripts have multiple parameters which can be used to customize execution. Run ```script.py --help``` to see a list with a description.
Note that wavs that compose the dataset will be store in a single "wavs" folder. In our examples, we will use "G:/" as path but any valid path is accepted. In our example, there should thus be a valid "G:/wavs".
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Note that wavs that compose the dataset will be store in a single "wavs" folder. In our examples, we will use "G:/" as path but any valid path is accepted. In our example, there should thus be a valid "G:/wavs".
