I have been working with and familiarized myself with the GettingStarted applications, most specifically the object detection program found on GitHub: https://github.com/STMicroelectronics/STM32N6-GettingStarted-ObjectDetection
I would like to take the next step and load my own model onto the board, I like the setup the current code has to output the frames and show the inference processing on the LCD screen and would prefer to utilize the current sample code if possible.
My question is this
Am I able to load in my own model I trained using the ModelZoo services, replacing the current model after I convert it to C code. Or will I have to make my own code from scratch to do this Camera->Frame->NN->LCD pipeline
And
Do I have to train the model using a certain resolution? I am currently gathering training images by running code found here: https://github.com/STMicroelectronics/x-cube-n6-camera-capture
The output frame that is captured is 800x480 resolution RGB888, I am then going to annotate and train using those images gathered. I ask this because in the app_config.h the NN_WIDTH and NN_HEIGHT are both set to 480, making me believe it is currently taking in images at 480x480. If so would it be easier to resize/crop images to 480x480 or set the config differently?
All-in-all I'm just wanting to see if there is an easy way to load a custom model and test it on this board. Preferably with code that is already available.
Thanks for your help!
