So I'm having some issues using the trained model as a library in my project.
So far this has been my process:
- I did the data collection using a different board (because I didn't have a QuickFeather at that point). Data was sent to a NodeRED endpoint and stored in a DB.
- I exported said data as CSV.
- I also created a custom SSF file in which I declare a single "sensor" that encapsulates the input variables.
- I added this SSF to Data Capture Lab, which enabled me to import the CSVs and label them for the classification model.
- I trained a model on SensiML analytics studio and exported it as a library, for the Simple Streaming Example.
- The "copy_files" script included in the knowledge pack fails because sml_output.c is not there.
- Once I replace the files in the qf_ssi_ai_app example with the files from the knowledge pack, the application no longer compiles. It fails with the following error:
sml_output.c:49: undefined reference to `sml_get_feature_vector'
Also important:
- I had previously verified that I can successfully compile the qf_ssi_ai_app in recognition mode before I replaced the files with the ones in the KP.
- I know that (according to the README.rst in the qf_ssi_ai_app folder) I need to do other changes for the app to actually parse my data and run the model successfully, but I think the project should at least compile with the files from the knowledge pack, even if it would misbehave at runtime until I fix the definitions.