Why am I getting compile errors when deploying a matlab function that uses snapshot() from raspberry pi cameraboard together with deep learning?
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I have two sections in my function. First, it captures an image from the raspberry pi camera module. Deploying it on the hardware as standalone was successful. Then I added another set of code — using AlexNet to classify the captured image. After making the necessary changes in coder.DeepLearningConfig() (a new feature in MATLAB 2020a), this error came up during deployment:
error: cannot convert ‘uint64m_T*’ to ‘uint64_t’ for argument ‘1’ to ‘int EXT_CAMERABOARD_snapshot (uint64_t*, uint8_T8*, uint32_T*)’
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recipe for target 'cameraboard.cpp.o' failed
It seems like there was a problem with compiling the cameraboard when using it with deep learning models. To check that there was really no problem with AlexNet, I tried deploying it without the cameraboard and it worked. Are there any fixes for this?
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Reeno Joseph
2020-4-6
Hello Miguel,
This looks like a bug in the cpp codegen for cameraboard. We will fix this issue ASAP.
Meanwhile you can use webcam() API as a workaround.
-Reeno
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Reeno Joseph
2020-4-9
Please try the index to access webcam.
raspiObj = raspi();
cam = webcam(raspiObj,0);
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